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Speaker 1: Welcome to the Wired to Hunt podcast, home of the

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Speaker 1: modern white tail hunter and now your host, Mark Kenyon.

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Speaker 1: Welcome to the Wired to Hunt podcast. I'm your host,

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Speaker 1: Mark Kenyon, and today in the show, I am joined

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Speaker 1: by the mad scientist, the greatest of all times, some say,

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Speaker 1: Mark Drury, for an absolute masterclass on the art of

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Speaker 1: patterning bucks. All right, welcome to the Wired to Hunt podcast,

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Speaker 1: brought to you by First Light. It's good to be here.

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Speaker 1: I'm very very excited. We have got a great episode

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Speaker 1: for you today and it is kicking off a series.

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Speaker 1: This has been the year of series. It's been a

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Speaker 1: fun way to organize our months as we've gone throughout

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Speaker 1: the year. And after killing my buck last week in Chigan,

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Speaker 1: I spent some time thinking about what, you know, what

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Speaker 1: led to that success? What was I doing? What was

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Speaker 1: I geeking out about? And it was really patterning. I

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Speaker 1: was having so much fun looking at all the data,

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Speaker 1: thinking through what are these deer doing and why are

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Speaker 1: they doing it? And where are they going to do

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Speaker 1: it again? And when are they going to do it again?

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Speaker 1: And all that was part of what led me to

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Speaker 1: you know, hunting where I did and killing that buck

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Speaker 1: the way that I did, and I got to think

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Speaker 1: there's a whole lot more we could be discussing on

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Speaker 1: this idea of patterning bucks, and the month of October

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Speaker 1: is a great month to pattern a buck. So October

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Speaker 1: is the month of the pattern and we're going to

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Speaker 1: kick that off. If we don't include last week's which

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Speaker 1: was kind of like a soft kickoff today, the real

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Speaker 1: kickoff of this month is this masterclass with Mark Drewy.

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Speaker 1: You should all know Mark. He's been the podcast many times.

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Speaker 1: He's one of the co founders of Drewy Outdoors, host

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Speaker 1: of many different deer hunting TV shows. You can find

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Speaker 1: him on the deer Cast app, the Dury Outdoors YouTube channel,

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Speaker 1: all over the place, and he is an absolute wealth

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Speaker 1: of information. And there's two things that I think he

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Speaker 1: specializes in, maybe three, but one of them is really

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Speaker 1: dissecting and deep dive understanding how environmental and weather factors

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Speaker 1: impact dear movement. We've talked to him several times deep

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Speaker 1: on that topic. But another one that we haven't gone

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Speaker 1: quite deep on in the past is patterning deer. How

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Speaker 1: he kind of collects and analyzes data about specific deer

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Speaker 1: and then helps develop a pattern of what they're gonna

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Speaker 1: do and when they're gonna do it, so he can

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Speaker 1: be there to get a shot when they do. And

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Speaker 1: that is our topic today. We go into all facets

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Speaker 1: of patterning deer, everything from how he collects the data

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Speaker 1: to how he correlates different factors with his observations and pictures,

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Speaker 1: all the way to how he chooses when to actually

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Speaker 1: act on that stuff and try to take a shot

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Speaker 1: at these deer. We talk early season patterning, we talked

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Speaker 1: learning during the rut, we talk late season, all sorts

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Speaker 1: of stuff in between. This is a banger episode. And

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Speaker 1: if you want to kill a deer this month in October,

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Speaker 1: shoot even if you want to kill in November or December,

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Speaker 1: you're gonna learn something today that will help you do it.

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Speaker 1: I loved it. I think you will too. I want

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Speaker 1: to give you a couple of quick updates before I

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Speaker 1: let you go. H one. The final episode of my

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Speaker 1: show Deer Country drops this week, so if you haven't yet,

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Speaker 1: headed over to the Meteor YouTube channel and check out.

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Speaker 1: Deer Country is the six episode series that documented my

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Speaker 1: hunts last year as I traveled the country, met with

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Speaker 1: different regional experts, sent spent one day learning from them

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Speaker 1: in their neck of the woods, and then I spent

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Speaker 1: the next three days to seeing if I could replicate

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Speaker 1: their style in their general area and pull it off myself.

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Speaker 1: This last episode was all about looking behind the curtain

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Speaker 1: of how you know folks in the Midwest managed for

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Speaker 1: Big Deer and actually in this case run an outfitting situation.

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Speaker 1: Very interesting, very new kind of situation for me. I

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Speaker 1: would love it if you could check it out. So

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Speaker 1: that's number one. Number two. This is a big one

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Speaker 1: this week. If you're listening to this when we dropped

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Speaker 1: this episode, this episode is coming out October. If you're

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Speaker 1: listening on October two or the next couple of days afterwards,

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Speaker 1: I want you to know that this week is meat

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Speaker 1: Eaters white Tail Week. We got a whole lot of

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Speaker 1: exciting stuff happening when it comes to white tails at Metator.

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Speaker 1: One of them his first Lights white Tail Sale, all

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Speaker 1: of first Lights white Tail gear. Inspector is off off

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Speaker 1: any of that first Light white Tail stuff you might need,

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Speaker 1: the Catalyst, the Solitude, whatever. Check it out if you're

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Speaker 1: in need of some last minute stuff. Twenty off Number

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Speaker 1: two Phelps game Calls. It is the game call company

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Speaker 1: that's part of metator right. They've done duck calls, they've

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Speaker 1: done elk calls, they've done turkey calls. This week they're

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Speaker 1: launching year calls. We've got a bunch of new grunt

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Speaker 1: tubes Fond Distress call bleats uh I personally have really

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Speaker 1: been liking and using the Beta Pro and the Alpha

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Speaker 1: I believe in the names of these two grunt tubes.

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Speaker 1: I've gotten to test them so far this year. I

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Speaker 1: really like the sound. There's some really good things with them.

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Speaker 1: I'll get into more detail in these calls in the future,

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Speaker 1: but just a heads up. Phelps has got new grunt tubes.

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Speaker 1: If you need a grunt tube, this is worth checking out.

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Speaker 1: More to come later. If you have been thinking about

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Speaker 1: this kind of stuff, this is probably going to be

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Speaker 1: one of the best opportunities. You've got to do it

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Speaker 1: to get it for cheap, so heads up on those

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Speaker 1: type of things. There's several of the Deer's deals from

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Speaker 1: timber Ninja, there's discounts on our white tail logo where

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Speaker 1: there's uh she, some deals from f HF. There's a

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Speaker 1: lot going on. I don't want to drag us out anymore,

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Speaker 1: but Mediator Whitetail Week is going on to October six.

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Speaker 1: Heading over to the mediator dot com, go to the

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Speaker 1: Mediator store, go to first let dot com. You're gonna

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Speaker 1: find it all their good stuff. And that's it for me.

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Speaker 1: That's my only other update. We got a master class

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Speaker 1: to get too, folks. So enough of me jabbering on

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Speaker 1: h I love patterning bocks. I love this stuff. I

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Speaker 1: love nording out on the data on what these deer

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Speaker 1: we're doing and what they might do, on where I

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Speaker 1: should be to maybe take advantage of it. It's so

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Speaker 1: much fun. And Mark Jury is just one of my favorites.

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Speaker 1: I love this guy. I love his approach. Uh, I

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Speaker 1: have nothing else to say. Let's get to it. Mark

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Speaker 1: Jury on the podcast master Class Patterning Box one. Dud.

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Speaker 1: They go all right back with me. We have the

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Speaker 1: great privilege of having Mr Mark Drury on this show. Mark,

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Speaker 1: thank you for coming back on the show. It's my pleasure.

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Speaker 1: Thank you for having me. How are you doing this morning, Mark?

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Speaker 1: I'm really good. I'm really good. I fill the bucktagon

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Speaker 1: Michigan opening night. I went to Ohio and did some

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Speaker 1: scouting yesterday, so I'm I'm just basking in the glory

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Speaker 1: of deer season, man, pick here you in the family.

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Speaker 1: I mean that that really put a smile on my face.

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Speaker 1: And I know your smile is probably still there from

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Speaker 1: that moment. That was pretty awesome, dude. It was it

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Speaker 1: was the first time that the whole family could be

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Speaker 1: together for that and um my, my the first track

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Speaker 1: job for my youngest So I'm a two year old,

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Speaker 1: so so yeah, super cool. And it was funny after

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Speaker 1: we recovered that. Buck, We're all sitting there together, and

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Speaker 1: my oldest son ever, he's four, he kind of turns

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Speaker 1: and looks at the family and he like shouts, like

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Speaker 1: really loud. He says, it's our first family Buck. I

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Speaker 1: loved it. I just loved you. That's a true statement,

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Speaker 1: those bucks. You know, the family allows you the time

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Speaker 1: and allows you to have the passion you allow right

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Speaker 1: that you have. So that's a cool thing when they

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Speaker 1: get who you are and embrace it. Uh, it's a

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Speaker 1: beautiful thing. When they don't, it's it's a rough, rough

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Speaker 1: time for most others. Because I've known guys like that

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Speaker 1: and I'm sure you do too, where the bouse or

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Speaker 1: the children and probably maybe get a little jealous over

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Speaker 1: the time and the selfishness that we all have when

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Speaker 1: it comes to this time of the year. So you're

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Speaker 1: blessed to have a family that is aware of your

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Speaker 1: passion and embraces it. Yeah, very very very true. Uh,

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Speaker 1: speaking of things worth celebrating, I saw that you had

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Speaker 1: a pretty exciting night last night too, and probably late night.

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Speaker 1: So I gotta thank you again for for hopping on

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Speaker 1: the phone here this morning after what seemed like a

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Speaker 1: pretty uh eventful night. Can you uh, can you fill

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Speaker 1: us in on what happened? Dude? It was such a

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Speaker 1: cool day yesterday. I did an interview in the Blind

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Speaker 1: and I had intel on a really nice dear that

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Speaker 1: I was in on last night, Wade, which is the

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Speaker 1: one you're referring to. I had intel on him, and

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Speaker 1: Terry had intel on a giant. So all three of

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Speaker 1: these deer like one plus type deer, and all three

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Speaker 1: of them were on them. And I did this interview

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Speaker 1: and I told Harry, I said, I don't ever recall

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Speaker 1: all where we had intel and all three of us

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Speaker 1: are on giants the same night, And I said, I

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Speaker 1: feel really good. Somebody's gonna kill And I said, I

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Speaker 1: think it's gonna be weighed because that buck. We had

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Speaker 1: a self picture of his going to bed that morning

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Speaker 1: at eight oh nine something like that, and he was

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Speaker 1: he was heading south out of the field or a

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Speaker 1: south wind, and the access to that spot is very good.

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Speaker 1: In fact, I don't know if you recall the deer

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Speaker 1: that I killed Leicester December twentieth. We called him the

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Speaker 1: fork buck, and he grows a little over one ninety. Well,

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Speaker 1: the last time that blind was sat was that night

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Speaker 1: December twenty, and then last night and then Wade killed

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Speaker 1: eight out of it. So the hit was just a

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Speaker 1: little bit back but quartering away. So I got opinions

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Speaker 1: from tracker John and Bobby Coverts in the same two

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Speaker 1: guys that are in deer cast track, you know, giving

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Speaker 1: me advice in there on track jobs. And we waited

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Speaker 1: the appropriate time and then took up the trail. And

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Speaker 1: you're right. It was a late night. The deer travel

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Speaker 1: about five or six hundred yards, but we found him

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Speaker 1: dead in this first bed on a really good blood trail.

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Speaker 1: It went stomach, liver, lung, and uh, the celebration began

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Speaker 1: and then all the of course, all the work begins.

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Speaker 1: So I went to bed about about two thirty and

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Speaker 1: I was I still saw three o'clock UM last night,

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Speaker 1: and then I woke up this morning about six thirty

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Speaker 1: the normal times, so it was it was a sharp night.

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Speaker 1: But you know what, that's what, that's what we do,

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Speaker 1: and we love it. We live for those nights, you know,

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Speaker 1: we live for those because no sleep nights. You know,

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Speaker 1: who cares about a night where you get seven or

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Speaker 1: eight hours? I'll take those two our rights every time.

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Speaker 1: That's what. That's the good problem to have right there.

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Speaker 1: You you want to have reason to miss sleep this

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Speaker 1: time of year, big time, big time. And it was

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Speaker 1: Wade's biggest deer. It was a main frame eight point

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Speaker 1: and it had ten kickers, so it had eight team

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Speaker 1: total score for points. It was a six and a

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Speaker 1: half year old deer. And the cool thing about this deer,

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Speaker 1: and it really really kind of blends into what we're

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Speaker 1: talking about today. When this deer was four and a

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Speaker 1: half in two thousand and twenty, I had a few

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Speaker 1: pictures of him scattered throughout the fall on this tractor ground.

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Speaker 1: This farm is about four acres. It's right on a

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Speaker 1: major highway. I lose deer to the highway and um

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Speaker 1: I had a sprinkling of pictures, So I didn't consider

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Speaker 1: him like one of those dear you know how it is.

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Speaker 1: You could get him every day and you're like, hey,

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Speaker 1: it's a homeboy. And I never considered homeboy. Last year

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Speaker 1: and that year he was probably a hundred high thirties

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Speaker 1: type eight point, but he wore it well. He had

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Speaker 1: that white friend. Last year he was probably high forties,

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Speaker 1: low fifties. Had him all summer. I got one hard

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Speaker 1: hearted pick and he vanished, I mean gone. And all

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Speaker 1: year I kept waiting to get a picture of him,

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Speaker 1: had more cameras out, couldn't get him. And all of

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Speaker 1: a sudden, late December, he shows back up, and I

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Speaker 1: was like that son of a gun, he left the

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Speaker 1: entire fall, at least presumably left. I didn't have I

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Speaker 1: didn't have photography of him. We hunted the farm a

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Speaker 1: good bit that was where the four buck lived lived,

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Speaker 1: and I never saw the buck, never encountered him. I

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Speaker 1: just assumed he was dead from the highway or another hunter.

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Speaker 1: There's a lot of pressure around that farm. And then

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Speaker 1: he shows back up late December. So this summer, when

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Speaker 1: he showed up in Velvet, we knew he was a giant,

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Speaker 1: you know, right away I guess the deer in the

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Speaker 1: one eighties somewhere and I'm like, oh, that's that's the

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Speaker 1: deer that disappeared last year. And uh, you know, this

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Speaker 1: year he shed his velvet. I got more pictures and

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Speaker 1: I'm like, he's sticking around. But in my heart, I

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Speaker 1: was like, this year is gonna again transferred to a

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Speaker 1: fall range in my opinion, which I I eventually talked

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Speaker 1: to a gentleman that that had the buck off all

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Speaker 1: and they passed him, uh because because he was an

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Speaker 1: eight point and they were on another different target deer.

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Speaker 1: That farm is probably a mile all mile and a

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Speaker 1: half east of mind. So my assumption was he was

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Speaker 1: again going to switch home ranges this year or fall ranges,

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Speaker 1: and that's why when he stuck around, we made an

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Speaker 1: extra effort to get on with cell cams and and

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Speaker 1: the food plots that he was using went back to

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Speaker 1: when he was for researched where he was the most,

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Speaker 1: and ended up killing him in one of those two

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Speaker 1: fields where he was at the most what he was

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Speaker 1: there during this period. So it really speaks to exactly

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Speaker 1: what we're talking about, how patentable they can be when

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Speaker 1: their home range overlays from one year to the next,

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Speaker 1: they really do a lot of the same things. So yeah,

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Speaker 1: so this is a this is a great example, and

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Speaker 1: maybe we can kind of dial in on a few

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Speaker 1: things with this story. You know, the focus I really

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Speaker 1: am hoping to dive into is just everything on how

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Speaker 1: you pattern these bucks mark And the first thing I'm

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Speaker 1: wondering with with a buck like this or any deer,

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Speaker 1: when do you start the patterning process? Like when does

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Speaker 1: a buck show up on your radar and you say, okay,

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Speaker 1: this is what we have to you know, we're gonna

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Speaker 1: label him as X, or we're gonna create a folder,

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Speaker 1: or we're gonna you know, when does that start? Are

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Speaker 1: these two year old bucks a three year old bucks? Like?

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Speaker 1: When does the the file start getting developed? You know?

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Speaker 1: I have a lot of trail cameras, as you know,

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Speaker 1: and I run probably nine cells and another hundred and

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Speaker 1: fifty normal reconics cameras annually. Now that's across three states,

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Speaker 1: has crossed a lot of different farms and leases and

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Speaker 1: so and so forth. And I will answer that question

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Speaker 1: by this. I have a a file of photos that

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Speaker 1: starts in two thousand and seven that includes every racked

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Speaker 1: buck I've ever taken a photo of and every photo

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Speaker 1: of that rack buck from the time that they are

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Speaker 1: two and a half until they disappear or we kill

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Speaker 1: them or whatever. So I try to start putting a

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Speaker 1: pattern on them the moment they have a decent rap

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Speaker 1: and if it's a year and a half old, that

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Speaker 1: that shows real promise. You know, you know, I don't

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Speaker 1: keep spikes in four corns and six points and that stuff.

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Speaker 1: But if it's a year and a half, that shows

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Speaker 1: real promise. I keep files on them as well. So

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Speaker 1: you know, my my entire fall is just swallowed up

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Speaker 1: looking at photography. I don't know how many pictures I'm

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Speaker 1: at now. I mean, I used to always feel like

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Speaker 1: I was at a million, but I'll bet you i'm

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Speaker 1: one point five to two million photos annually. Of that,

290
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Speaker 1: I'll keep maybe a hunter thousand. And I've got those

291
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Speaker 1: all stored in in my computer and in hard drives

292
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Speaker 1: from OS seven through present day. Oh that's a lot

293
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Speaker 1: I've got. I've got like nine different directions we could

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Speaker 1: go with this, and I'm not sure where where I

295
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Speaker 1: want to. I'm like, I'm like the child that's addicted

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Speaker 1: to candy that goes to Willy Wonka's candy shop, you know,

297
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Speaker 1: and just sees every thing all around him that he

298
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Speaker 1: wants to that he wants to have. I wanted this

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Speaker 1: is like the thing I nerd out about the most too,

300
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Speaker 1: So I guess, I guess let's just jump into something

301
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Speaker 1: you just said right there, which was you have a

302
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Speaker 1: hundred thousand pictures that you might be keeping, and you

303
00:16:15,360 --> 00:16:19,200
Speaker 1: are keeping photos of bucks from the time they're noticeably

304
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Speaker 1: you know, unique, So maybe oftentimes that's two and a

305
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Speaker 1: half years old. When you get a deer like this

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Speaker 1: one that Wade was on, and you realize, okay, this

307
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Speaker 1: was a buck that you know, we noticed last year,

308
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Speaker 1: we passed him. Now this year he's back and he's

309
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Speaker 1: he's definitely want to shoot. How do you go about

310
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Speaker 1: sorting through everything you had, Like, how do you make

311
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Speaker 1: how do you find all the past pictures of his?

312
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Speaker 1: How do you have it organized so you can then see, Okay,

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Speaker 1: here's all the photos of this buck. Here's the way

314
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Speaker 1: I'm going to think through pictures from last year versus

315
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Speaker 1: this year. How are you able to find it, compile

316
00:16:57,600 --> 00:16:59,640
Speaker 1: it in a way you can actually analyze and then

317
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Speaker 1: make the scissions from Given the fact that you have

318
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Speaker 1: just so much out there already to sort through. I

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Speaker 1: guess my big big questions, how do you sort through

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Speaker 1: and find the most important pieces within a haypile. It's

321
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Speaker 1: it's it is a haypop because it's a time consuming

322
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Speaker 1: deal to go through and and and find him again.

323
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Speaker 1: Because I have in Iowa, I probably have you know,

324
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Speaker 1: fifty different locations within reconics buckfew. And that's the program

325
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Speaker 1: I've used in so seven and it it has served

326
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Speaker 1: me quite well. Um, and you know, so I will

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Speaker 1: I would designate a farm, call it the the this farm,

328
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Speaker 1: for instance, call it the two seven, all right, because

329
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Speaker 1: this track was two fifty seven. I eventually I bought it,

330
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Speaker 1: uh and attached it to a one sixties that I owned,

331
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Speaker 1: So now it's four seventeen. But this particular pieces two

332
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Speaker 1: seven acres, So I have it in there as the

333
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Speaker 1: two seven. I have a long bottom file. I have

334
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Speaker 1: to fifty seven ridge. I've got every different can camera

335
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Speaker 1: on that farm label accordingly. And then as I look

336
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Speaker 1: at the cards and as I look at the pictures,

337
00:18:07,560 --> 00:18:11,119
Speaker 1: I am shuffling them into all those different files so

338
00:18:11,359 --> 00:18:14,760
Speaker 1: I can go back, you know, to thirteen, fourteen, fifteen

339
00:18:14,840 --> 00:18:19,399
Speaker 1: whatever year it is, and and look at that particular

340
00:18:19,480 --> 00:18:23,879
Speaker 1: camera area and see how the how the deer deer moved,

341
00:18:23,920 --> 00:18:26,919
Speaker 1: and then I can start finding that buck once he

342
00:18:26,960 --> 00:18:30,359
Speaker 1: appeared within that farm and find out what days he

343
00:18:30,560 --> 00:18:33,440
Speaker 1: daylight and when he was there, so and so forth.

344
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Speaker 1: So I don't then peel him out and create a

345
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Speaker 1: following him. Sometimes I do, but that's not the file

346
00:18:40,119 --> 00:18:43,520
Speaker 1: I'm looking at. I'm looking at all the other aspects

347
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Speaker 1: that might affect a deer's movement during daylight, So I'm

348
00:18:48,400 --> 00:18:52,840
Speaker 1: looking for other deer um. I have notes within deer

349
00:18:52,880 --> 00:18:57,560
Speaker 1: cast our app as to what the uh crop rotation

350
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Speaker 1: was on that field or in that area, not only

351
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Speaker 1: on my farm, but on the outlying farms. I have

352
00:19:05,040 --> 00:19:09,240
Speaker 1: files of the weather data from those years, so that

353
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Speaker 1: if I find a daylight picture, call it when he

354
00:19:13,280 --> 00:19:15,439
Speaker 1: was four and a half years old and two thousand

355
00:19:15,480 --> 00:19:18,160
Speaker 1: and twenty, and I find two or three in a row,

356
00:19:18,680 --> 00:19:22,040
Speaker 1: I can go back and research what was the weather like,

357
00:19:22,600 --> 00:19:25,240
Speaker 1: what was the food like, what was the mass crop like,

358
00:19:25,720 --> 00:19:28,640
Speaker 1: what was the rainfall like, and then start to put

359
00:19:28,680 --> 00:19:32,240
Speaker 1: together why he did what he did. So it's it's

360
00:19:32,320 --> 00:19:35,200
Speaker 1: data at a fairly high level, but that's how we're

361
00:19:35,240 --> 00:19:38,080
Speaker 1: killing them. And I do these deep guys. When we

362
00:19:38,119 --> 00:19:40,480
Speaker 1: get a target buck, I go backwards in my file.

363
00:19:40,600 --> 00:19:44,359
Speaker 1: So that's why it's important that I keep every single

364
00:19:44,520 --> 00:19:48,240
Speaker 1: rack Buck photo because you're building that buck's history and

365
00:19:48,320 --> 00:19:51,919
Speaker 1: that buck's life. And then when he if he stays

366
00:19:51,960 --> 00:19:53,840
Speaker 1: around and if he gets the five or six, and

367
00:19:53,960 --> 00:19:57,120
Speaker 1: if he becomes a target, which by and large most

368
00:19:57,160 --> 00:20:00,000
Speaker 1: do not. They fall off the map at age three

369
00:20:00,280 --> 00:20:03,000
Speaker 1: h four eag. You know, through time, you lose a

370
00:20:03,000 --> 00:20:06,080
Speaker 1: lot or they they're there here today, gone tomorrow. They're

371
00:20:06,080 --> 00:20:08,320
Speaker 1: on a walk about outside of their home range. You

372
00:20:08,359 --> 00:20:11,159
Speaker 1: get pictures and I keep them just in case they

373
00:20:11,160 --> 00:20:13,520
Speaker 1: walk about again. But a deer that is a semi

374
00:20:13,600 --> 00:20:16,919
Speaker 1: homeboy like this, I had some pretty good data points

375
00:20:16,960 --> 00:20:19,440
Speaker 1: that I could go back on and and and figure

376
00:20:19,520 --> 00:20:22,320
Speaker 1: him out. So and he really wasn't that hard to

377
00:20:22,320 --> 00:20:26,359
Speaker 1: figure out because he was so so confined. Two spots

378
00:20:27,160 --> 00:20:33,920
Speaker 1: that were in both years, uh we're bean fields. Actually

379
00:20:34,240 --> 00:20:36,080
Speaker 1: in two thousand and twenty, he who was on a

380
00:20:36,119 --> 00:20:39,800
Speaker 1: bean field that I did a green to green transfer,

381
00:20:39,880 --> 00:20:41,280
Speaker 1: and then he did it again this year and that's

382
00:20:41,320 --> 00:20:43,960
Speaker 1: where he killed him. The other field where Wade and

383
00:20:44,040 --> 00:20:45,760
Speaker 1: counteredy mat the end of the night, which is only

384
00:20:45,760 --> 00:20:48,239
Speaker 1: about two yards from where he killed him, is a

385
00:20:48,280 --> 00:20:50,879
Speaker 1: big ridge field that they love to go bed on

386
00:20:50,880 --> 00:20:53,080
Speaker 1: this north face on hot days. That's the other thing

387
00:20:53,119 --> 00:20:56,239
Speaker 1: I learned about the farm. And then this bug. And

388
00:20:56,359 --> 00:20:59,520
Speaker 1: right below that there was a big giant bean field

389
00:20:59,520 --> 00:21:02,199
Speaker 1: and twenty and its beans again this year, so you know,

390
00:21:02,280 --> 00:21:04,560
Speaker 1: perhaps the crop rotation had something to do. And it

391
00:21:04,640 --> 00:21:06,840
Speaker 1: was also a good acrn near in twenty and two.

392
00:21:07,040 --> 00:21:10,760
Speaker 1: So all of those things come into play um when

393
00:21:10,800 --> 00:21:13,120
Speaker 1: it when it comes time to kill a deer, So

394
00:21:13,440 --> 00:21:17,560
Speaker 1: it's not about the deer always, it's also about the

395
00:21:17,680 --> 00:21:20,119
Speaker 1: environment and that's one of the reasons we did the

396
00:21:20,160 --> 00:21:23,080
Speaker 1: things we did within deer cast. You know, we we've

397
00:21:23,119 --> 00:21:26,159
Speaker 1: always had the predictive bottle. We extended that to fourteen

398
00:21:26,240 --> 00:21:28,600
Speaker 1: days this year. But this year we came up with

399
00:21:28,680 --> 00:21:32,159
Speaker 1: our mapping solutions. Well within that, we have the wind,

400
00:21:32,240 --> 00:21:35,560
Speaker 1: and we have mass crop, and we have overall rain

401
00:21:35,640 --> 00:21:39,560
Speaker 1: with our rain stations, all the things that people really

402
00:21:39,600 --> 00:21:42,160
Speaker 1: need to focus in on, I think to help them

403
00:21:42,160 --> 00:21:44,800
Speaker 1: take their game to the next level. So you know,

404
00:21:44,840 --> 00:21:47,600
Speaker 1: there's there's better mapping solutions out there. In my opinion,

405
00:21:47,640 --> 00:21:49,960
Speaker 1: I think there's absolute better mass. But I don't think

406
00:21:50,000 --> 00:21:52,679
Speaker 1: there's any out there with better tools to help you

407
00:21:52,760 --> 00:21:54,760
Speaker 1: kill a white tail than than what deer cast is.

408
00:21:54,800 --> 00:21:57,720
Speaker 1: We stayed in our lane and focus directly on the

409
00:21:57,720 --> 00:22:00,439
Speaker 1: white tail deer and the hunter and the armor that

410
00:22:00,480 --> 00:22:02,840
Speaker 1: they lived in. Yeah, that's some pretty cool stuff. I

411
00:22:02,880 --> 00:22:06,040
Speaker 1: love that rain gage feature. That is that one just

412
00:22:06,119 --> 00:22:08,240
Speaker 1: jumped out to me as gosh, I would die to

413
00:22:08,280 --> 00:22:10,879
Speaker 1: have that kind of information for over over the years

414
00:22:10,880 --> 00:22:14,880
Speaker 1: of food plots and whatnot, exactly like it's it's so

415
00:22:14,920 --> 00:22:20,000
Speaker 1: important to not only like our success. Like okay, basics.

416
00:22:20,320 --> 00:22:22,320
Speaker 1: I put the sea in the ground, I don't get rain,

417
00:22:22,359 --> 00:22:24,200
Speaker 1: it doesn't grow. I put the seed in the ground,

418
00:22:24,520 --> 00:22:27,680
Speaker 1: I get two tents of inch of rain. The seed swells,

419
00:22:27,720 --> 00:22:30,960
Speaker 1: it doesn't grow. I get a two inch rain. Holy cow,

420
00:22:31,040 --> 00:22:33,080
Speaker 1: I've got the best looking food plot I've ever had.

421
00:22:33,119 --> 00:22:36,239
Speaker 1: So that in it's the way we look at it,

422
00:22:36,480 --> 00:22:40,040
Speaker 1: you know, on the surfaces, like that's important to my success. Well,

423
00:22:40,520 --> 00:22:44,879
Speaker 1: what happened in April, May and June that this deer

424
00:22:45,160 --> 00:22:49,120
Speaker 1: grew forty five inches versus the last two years when

425
00:22:49,119 --> 00:22:51,080
Speaker 1: he was a one forty one fifty and all of

426
00:22:51,080 --> 00:22:55,120
Speaker 1: a sudden this year he's you know, well, guess what,

427
00:22:55,160 --> 00:22:58,240
Speaker 1: we had a wet spring. What happened five years ago?

428
00:22:58,720 --> 00:23:01,720
Speaker 1: We had a wet spring, and when he was a fawn,

429
00:23:02,160 --> 00:23:03,639
Speaker 1: he was off to a good start because we had

430
00:23:03,680 --> 00:23:07,400
Speaker 1: a tremendous acorn crop that year. So rainfall is so

431
00:23:07,440 --> 00:23:09,879
Speaker 1: important to the overall health of the herd. You know

432
00:23:09,920 --> 00:23:12,000
Speaker 1: what happens when we don't get the right amount of

433
00:23:12,040 --> 00:23:14,159
Speaker 1: rainfall here at the right times of the year, All

434
00:23:14,200 --> 00:23:16,399
Speaker 1: of a sudden you have the h D and that

435
00:23:16,560 --> 00:23:20,400
Speaker 1: affects overall daylight pictures and overall daylight movement. So I

436
00:23:20,440 --> 00:23:24,639
Speaker 1: think outside of just the um, the trail photos that

437
00:23:24,720 --> 00:23:28,479
Speaker 1: you keep, the notes you keep about your environment also

438
00:23:28,640 --> 00:23:33,160
Speaker 1: help you put patterns together through the decades because as

439
00:23:33,320 --> 00:23:35,920
Speaker 1: things occur. Now, Terry and I have been hunting long enough.

440
00:23:35,920 --> 00:23:38,640
Speaker 1: I'm fifty five. I started hunting when I was fifteen.

441
00:23:39,200 --> 00:23:42,560
Speaker 1: Terry sixty five. Well, we've seen many falls come and go.

442
00:23:43,080 --> 00:23:46,200
Speaker 1: We've seen great acorn crops, we've seen terrible ones. We've

443
00:23:46,200 --> 00:23:50,280
Speaker 1: seen crops fail, we've seen them succeed to the point

444
00:23:50,320 --> 00:23:53,040
Speaker 1: that they're two hundred bushel corn and you know, seventy

445
00:23:53,040 --> 00:23:56,480
Speaker 1: bushel beams. We've you know, we've seen it all before,

446
00:23:56,640 --> 00:23:59,879
Speaker 1: so therefore when it repeats, we have a better understanding

447
00:24:00,119 --> 00:24:02,800
Speaker 1: how to succeed. And and a lot of this is

448
00:24:02,840 --> 00:24:05,240
Speaker 1: mental notes, but a lot of it is written notes

449
00:24:05,280 --> 00:24:07,760
Speaker 1: and stuff that I've I've journaled through the years about

450
00:24:08,359 --> 00:24:11,720
Speaker 1: what happened when the weather was like this, and that's

451
00:24:11,720 --> 00:24:13,880
Speaker 1: how we came up with the algorithm for deercast. So

452
00:24:14,520 --> 00:24:17,200
Speaker 1: it's just really paying attention to every detail. But it's

453
00:24:17,200 --> 00:24:18,960
Speaker 1: gonna be a time stuck for you if you want

454
00:24:18,960 --> 00:24:21,280
Speaker 1: to take it to that level, like it's it's almost

455
00:24:21,880 --> 00:24:24,840
Speaker 1: seven throughout the entire fall to really hone in on

456
00:24:24,880 --> 00:24:27,840
Speaker 1: all these different things I'm talking about, because the environment

457
00:24:27,880 --> 00:24:30,679
Speaker 1: and the food sources are just as important to the

458
00:24:30,760 --> 00:24:34,760
Speaker 1: deer ultimately his health and how he's going to move,

459
00:24:35,040 --> 00:24:37,760
Speaker 1: you know, daylight versus nighttime that year, there's a lot

460
00:24:37,760 --> 00:24:40,879
Speaker 1: of different factors that to plug in on. Yeah, you

461
00:24:41,000 --> 00:24:45,360
Speaker 1: really gotta love it. I was for now, I don't

462
00:24:45,359 --> 00:24:47,479
Speaker 1: know what's two nights before opening day here in Michigan.

463
00:24:47,520 --> 00:24:49,320
Speaker 1: I was sitting at like eleven o'clock at night at

464
00:24:49,320 --> 00:24:52,159
Speaker 1: my computer, had both monitors up, and I had a

465
00:24:52,200 --> 00:24:55,920
Speaker 1: spreadsheet with all of my daylight trail camera photos of

466
00:24:56,000 --> 00:25:00,000
Speaker 1: my main target buck and all the different weather factors, YadA, YadA, YadA,

467
00:25:00,000 --> 00:25:02,080
Speaker 1: all the different data points there that I had a

468
00:25:02,080 --> 00:25:05,359
Speaker 1: note document open where I had listed out everything this

469
00:25:05,480 --> 00:25:09,040
Speaker 1: buck had done in within like a ten day window

470
00:25:09,080 --> 00:25:11,680
Speaker 1: of opening day. And then I had everything he'd done

471
00:25:11,720 --> 00:25:14,359
Speaker 1: this year so far for the last three weeks, and

472
00:25:14,359 --> 00:25:17,399
Speaker 1: then I had notes on the two locations I was

473
00:25:17,440 --> 00:25:19,960
Speaker 1: considering and what other deer had been in there last

474
00:25:20,040 --> 00:25:21,760
Speaker 1: year and this year. And was looking at all this

475
00:25:21,800 --> 00:25:23,800
Speaker 1: stuff and I'm having the time of my life. And

476
00:25:23,840 --> 00:25:25,920
Speaker 1: I texted some of my buddies in my group chat

477
00:25:26,160 --> 00:25:28,240
Speaker 1: and they're like, oh my god, that looks miserable. You're

478
00:25:28,240 --> 00:25:30,320
Speaker 1: a nut job. And in my head, I thought, this

479
00:25:30,359 --> 00:25:32,960
Speaker 1: is the best part of it. This is the best

480
00:25:33,480 --> 00:25:36,560
Speaker 1: You really got to love that. I agree. I love data,

481
00:25:36,800 --> 00:25:39,760
Speaker 1: you know, and I love stats, you know, and it's

482
00:25:39,800 --> 00:25:43,200
Speaker 1: it's pretty cool because they are potable, but you've got

483
00:25:43,200 --> 00:25:45,879
Speaker 1: to have the pieces of the pie to pattern them. Yeah.

484
00:25:46,160 --> 00:25:49,080
Speaker 1: So you mentioned, you know, keeping track of the environmental

485
00:25:49,240 --> 00:25:52,240
Speaker 1: factors and all the other things outside of just pictures.

486
00:25:52,760 --> 00:25:55,760
Speaker 1: And this is one thing that I have struggled with

487
00:25:55,800 --> 00:25:58,000
Speaker 1: actually over the years and not done a good enough

488
00:25:58,119 --> 00:26:00,359
Speaker 1: job of that. Is like keeping track of all of

489
00:26:00,400 --> 00:26:06,280
Speaker 1: those outside things. Um, I've I've started and stopped multiple

490
00:26:06,359 --> 00:26:08,600
Speaker 1: hunting journals where I'm every year I'm like, okay, I'm

491
00:26:08,600 --> 00:26:10,280
Speaker 1: gonna keep track of everything. And I do it for

492
00:26:10,320 --> 00:26:12,640
Speaker 1: a few days or a few weeks, and then I

493
00:26:12,640 --> 00:26:16,000
Speaker 1: lose I lose it. Uh what does that look like

494
00:26:16,080 --> 00:26:20,280
Speaker 1: for you? Do you keep a consistent journal? Do you,

495
00:26:20,280 --> 00:26:22,200
Speaker 1: you know, do track stuff just during the hunting season

496
00:26:22,320 --> 00:26:24,960
Speaker 1: or are you writing something down online or in a

497
00:26:25,040 --> 00:26:28,000
Speaker 1: book or you know, how do you personally do that?

498
00:26:29,280 --> 00:26:31,720
Speaker 1: I keep a lot of notes within deercast because we

499
00:26:31,800 --> 00:26:34,600
Speaker 1: allow for it, you know, within the different way points

500
00:26:34,640 --> 00:26:37,439
Speaker 1: and whatnot. But a lot of it is honestly in

501
00:26:37,480 --> 00:26:39,320
Speaker 1: my mind. Like I don't know. I think I was

502
00:26:39,800 --> 00:26:42,240
Speaker 1: lucky that I have a mind that Like I think

503
00:26:42,240 --> 00:26:45,120
Speaker 1: it's because I'm so hyper focused on killing them, Like

504
00:26:45,480 --> 00:26:47,879
Speaker 1: I know how important it is, so therefore I remember it,

505
00:26:48,080 --> 00:26:52,040
Speaker 1: if that makes sense. Like I can't remember. My wife

506
00:26:52,080 --> 00:26:54,040
Speaker 1: can bring up ten subjects in a row and I'll

507
00:26:54,040 --> 00:26:58,040
Speaker 1: have barely a memory of any of them. But when

508
00:26:58,040 --> 00:27:00,960
Speaker 1: it comes but it comes to a d R the

509
00:27:01,000 --> 00:27:04,400
Speaker 1: barametric pressure, the wind speed, the wind direction, I mean,

510
00:27:04,680 --> 00:27:06,320
Speaker 1: there's not a deer I've ever killed that. I couldn't

511
00:27:06,320 --> 00:27:08,240
Speaker 1: spit it out if you ask me, you know, I mean,

512
00:27:08,280 --> 00:27:11,440
Speaker 1: I just I've been very lucky to have it. And again,

513
00:27:11,480 --> 00:27:14,359
Speaker 1: I think that's probably a selfishness on my part because

514
00:27:14,359 --> 00:27:18,439
Speaker 1: I'm so obsessed with them. Uh, you know, so a

515
00:27:18,480 --> 00:27:22,359
Speaker 1: lot of it is just memory. Now, yeah, I can't,

516
00:27:22,920 --> 00:27:25,240
Speaker 1: I can't say I have that same memory. So jealous

517
00:27:25,240 --> 00:27:27,080
Speaker 1: of that, I've got to figure out a better way

518
00:27:27,119 --> 00:27:30,520
Speaker 1: to lock the stuff down on paper. Um, we'll see

519
00:27:30,520 --> 00:27:31,760
Speaker 1: if this is the year I can finally do a

520
00:27:31,800 --> 00:27:35,080
Speaker 1: better job of it. Here. Here's something I'm curious about,

521
00:27:36,720 --> 00:27:40,280
Speaker 1: historical weather data. Right, that's something that, of course you've

522
00:27:40,320 --> 00:27:43,120
Speaker 1: mentioned as being something you'd like to take a look

523
00:27:43,160 --> 00:27:45,640
Speaker 1: at and see, you know, how it correlates with daylight

524
00:27:45,880 --> 00:27:49,040
Speaker 1: pictures in the past or daylight observations. This is a

525
00:27:49,040 --> 00:27:51,320
Speaker 1: two part question, and one part maybe you don't want

526
00:27:51,320 --> 00:27:52,720
Speaker 1: to answer, and if you don't want to answer, you

527
00:27:52,720 --> 00:27:55,679
Speaker 1: don't need to. Second part you can tell me. But

528
00:27:55,920 --> 00:28:00,600
Speaker 1: part A is can we get historical other data in

529
00:28:00,680 --> 00:28:03,159
Speaker 1: deer cast someday? Because I would love it if I

530
00:28:03,160 --> 00:28:06,040
Speaker 1: could see that right in my dear cast app firsts

531
00:28:06,080 --> 00:28:08,040
Speaker 1: having to go to a different website. That's part day,

532
00:28:08,040 --> 00:28:10,679
Speaker 1: and then part two is where do you personally go

533
00:28:10,840 --> 00:28:15,160
Speaker 1: to get your historical weather data. I've created my own okay,

534
00:28:15,200 --> 00:28:20,080
Speaker 1: so two answers. Deer Cast looks at the future and

535
00:28:20,160 --> 00:28:24,080
Speaker 1: the past. Okay, So on a on a daily basis,

536
00:28:24,359 --> 00:28:27,320
Speaker 1: if it's giving you a prediction, it's looking backwards and

537
00:28:27,359 --> 00:28:31,199
Speaker 1: it's looking forward. So say you wanted to rewind the

538
00:28:31,240 --> 00:28:36,000
Speaker 1: clock five years, it would have to look backwards several

539
00:28:36,080 --> 00:28:41,040
Speaker 1: days and look forward several days to recreate the prediction

540
00:28:41,160 --> 00:28:44,640
Speaker 1: for that day. That was an algorithm and the cost

541
00:28:44,680 --> 00:28:47,680
Speaker 1: of an API that was cost prohibitive by not by

542
00:28:47,720 --> 00:28:51,200
Speaker 1: a little, but by a lot, like put puts got

543
00:28:51,200 --> 00:28:53,400
Speaker 1: a business, you know, when we asked the question, can

544
00:28:53,440 --> 00:28:55,800
Speaker 1: we do this because we have an ap I like

545
00:28:56,000 --> 00:28:59,720
Speaker 1: weather is for the most part, a predictive model in

546
00:28:59,760 --> 00:29:03,280
Speaker 1: an itself. So the API comes in, we pipe that

547
00:29:03,360 --> 00:29:06,560
Speaker 1: into our algorithm and it all works right because it's

548
00:29:06,560 --> 00:29:09,200
Speaker 1: all recent, it's all right there in their computers to

549
00:29:09,320 --> 00:29:12,720
Speaker 1: go back and dig it up. Was they're They're like, well,

550
00:29:12,720 --> 00:29:14,880
Speaker 1: no one's ever asked for that before, you know, and

551
00:29:14,880 --> 00:29:17,920
Speaker 1: and other words, it was impossible and the quote was

552
00:29:18,240 --> 00:29:21,520
Speaker 1: cost prohibitive. So I do it myself. I screenshot my

553
00:29:21,560 --> 00:29:23,320
Speaker 1: dear cast every day and I keep a file and

554
00:29:23,360 --> 00:29:25,520
Speaker 1: I have since it came out, so I've got every

555
00:29:25,600 --> 00:29:28,840
Speaker 1: day's weather data for where I hunt since the start

556
00:29:28,880 --> 00:29:34,040
Speaker 1: of it. So that's the best way to do it, Okay, Well,

557
00:29:34,080 --> 00:29:38,200
Speaker 1: I uh, because then it's is all there. If you

558
00:29:38,200 --> 00:29:40,480
Speaker 1: look at our screen, everything you want to know is

559
00:29:40,520 --> 00:29:44,320
Speaker 1: all on on that hourly forecast. Put it at you know, noon,

560
00:29:44,440 --> 00:29:47,680
Speaker 1: or put it at eight am or six pm, and

561
00:29:47,760 --> 00:29:50,600
Speaker 1: screenshot it, and you've got every single readout you want.

562
00:29:51,000 --> 00:29:55,120
Speaker 1: But going back and doing it is just absolutely cost prohibitive. Yeah,

563
00:29:55,160 --> 00:29:58,840
Speaker 1: I can see that. Uh, well, I can dream, I guess,

564
00:30:00,120 --> 00:30:04,280
Speaker 1: and it's cost prohibitive because of how many days equal

565
00:30:04,360 --> 00:30:07,200
Speaker 1: into the prediction for that moment. Right, We're giving you

566
00:30:07,400 --> 00:30:10,320
Speaker 1: an hour by our forecast, but in reality, it's looking

567
00:30:10,320 --> 00:30:12,760
Speaker 1: forward and looking backwards to give you that hour, and

568
00:30:12,880 --> 00:30:14,840
Speaker 1: then if you wanted to rewind the clock five years,

569
00:30:14,840 --> 00:30:18,280
Speaker 1: it's it's almost it's so tangled up you can't do it. Yeah,

570
00:30:18,360 --> 00:30:22,960
Speaker 1: that's a doozy. Well back to back to pictures then, Um,

571
00:30:23,120 --> 00:30:25,240
Speaker 1: one of the things I don't want to spend a

572
00:30:25,240 --> 00:30:26,800
Speaker 1: ton of time on, but I do want to just

573
00:30:27,080 --> 00:30:30,360
Speaker 1: run by you real quick. We've had previous conversations over

574
00:30:30,360 --> 00:30:32,719
Speaker 1: the years about how you use trail cameras, how you

575
00:30:32,760 --> 00:30:36,200
Speaker 1: place them, Um, you know, when you're checking them, when

576
00:30:36,200 --> 00:30:38,840
Speaker 1: they're when you're moving them, stuff like that. But when

577
00:30:38,840 --> 00:30:41,560
Speaker 1: it comes specifically to patterning bucks, like not just getting

578
00:30:41,560 --> 00:30:44,360
Speaker 1: a basic inventory in the summer, uh, not just trying

579
00:30:44,400 --> 00:30:47,080
Speaker 1: to get you know, what's around, but when you are

580
00:30:47,160 --> 00:30:50,400
Speaker 1: actively trying to pattern a specific buck like this deer

581
00:30:51,000 --> 00:30:53,200
Speaker 1: for example, that way just killed when he showed back

582
00:30:53,280 --> 00:30:54,960
Speaker 1: up and you realized, oh wow, we've got a chance

583
00:30:55,000 --> 00:30:56,800
Speaker 1: of this dear, but we gotta figure him out asap

584
00:30:57,160 --> 00:31:02,600
Speaker 1: before he disappears. How does your camera placement change, if

585
00:31:02,640 --> 00:31:04,720
Speaker 1: at all, in that kind of situation when you're like,

586
00:31:04,880 --> 00:31:07,760
Speaker 1: we need to learn this deer and put together a pattern. Now,

587
00:31:08,560 --> 00:31:10,479
Speaker 1: just do things change or do you always have your

588
00:31:10,480 --> 00:31:12,400
Speaker 1: cameras in the same places and they just stay there.

589
00:31:13,360 --> 00:31:16,520
Speaker 1: They are historical cameras everywhere that stay there, that are

590
00:31:16,600 --> 00:31:20,280
Speaker 1: on great travel routes or hubscrapes or places. You know,

591
00:31:20,320 --> 00:31:23,040
Speaker 1: when you watch a farm or watch a field and

592
00:31:23,040 --> 00:31:25,480
Speaker 1: you're hunting it, you go, I need a camera right there,

593
00:31:25,560 --> 00:31:27,600
Speaker 1: and then it always produces for you you know, and

594
00:31:27,920 --> 00:31:31,000
Speaker 1: you watch a certain food plot and that's got the movement.

595
00:31:31,000 --> 00:31:33,600
Speaker 1: The rest of the plot's got twenty right, so you know,

596
00:31:33,680 --> 00:31:36,560
Speaker 1: but then when we find a target, then we might

597
00:31:36,640 --> 00:31:42,120
Speaker 1: go from three broad looking cameras in that area to ten.

598
00:31:42,520 --> 00:31:45,480
Speaker 1: I call it the blitz creeg with with cams. So

599
00:31:45,920 --> 00:31:48,239
Speaker 1: you know you're going you're trying to win the war, right,

600
00:31:48,320 --> 00:31:51,040
Speaker 1: everybody knows from history that the term blitz grieg. Well,

601
00:31:51,040 --> 00:31:52,840
Speaker 1: you're going there. You gotta be wise about it. You

602
00:31:52,880 --> 00:31:55,000
Speaker 1: can't run him out of there. Got to be smart

603
00:31:55,160 --> 00:31:57,480
Speaker 1: and get as much intel as you can. And you know,

604
00:31:58,160 --> 00:32:00,400
Speaker 1: you know, six seven years ago, before the advent of

605
00:32:00,440 --> 00:32:02,719
Speaker 1: the cell cams, you didn't have real time information. Now

606
00:32:02,800 --> 00:32:08,120
Speaker 1: you do. So my my methods have changed from strictly

607
00:32:08,200 --> 00:32:11,680
Speaker 1: looking at historical patterns and trying to predict the future

608
00:32:12,080 --> 00:32:16,680
Speaker 1: to that coupled with real time in the now um

609
00:32:16,880 --> 00:32:20,040
Speaker 1: information through cell cams, and it's uh. I can tell

610
00:32:20,080 --> 00:32:23,560
Speaker 1: you those subcams are are a deadly deadly tool. When

611
00:32:23,680 --> 00:32:27,480
Speaker 1: coupled with historical infusion from a file that you've you've

612
00:32:27,560 --> 00:32:29,840
Speaker 1: kept on a deer, it is a one to punch

613
00:32:29,920 --> 00:32:34,160
Speaker 1: that is unbeatable for mature bucks, particularly particularly in phases

614
00:32:34,240 --> 00:32:36,720
Speaker 1: like this one on on Greener Pastors were in phase

615
00:32:36,800 --> 00:32:39,760
Speaker 1: two from our show start team, and they're just not

616
00:32:39,880 --> 00:32:41,640
Speaker 1: moving very far. If you put a buck to bed

617
00:32:42,200 --> 00:32:45,640
Speaker 1: and you've got a decent deercast prediction that afternoon, chances

618
00:32:45,640 --> 00:32:48,320
Speaker 1: are you going to see when you do this blitz

619
00:32:48,360 --> 00:32:51,480
Speaker 1: creek and you go and you increase the concentration of cameras.

620
00:32:53,000 --> 00:32:55,000
Speaker 1: What are what are the kinds of places you're going

621
00:32:55,040 --> 00:32:57,760
Speaker 1: to place those extra cameras, and how are you doing

622
00:32:57,880 --> 00:33:01,360
Speaker 1: it so that you don't mess up you know, your

623
00:33:01,400 --> 00:33:03,720
Speaker 1: chances of still seeing him. What's what's the best way

624
00:33:03,760 --> 00:33:05,560
Speaker 1: to do that in a low impact way where you

625
00:33:05,680 --> 00:33:10,000
Speaker 1: get enough information that's relevant but not so much so

626
00:33:10,240 --> 00:33:14,840
Speaker 1: that you never see him again. It changes throughout the year.

627
00:33:15,120 --> 00:33:17,280
Speaker 1: This time of the year, they're not moving very far

628
00:33:17,400 --> 00:33:20,320
Speaker 1: because they're on food source. They haven't started expanding their

629
00:33:20,360 --> 00:33:23,680
Speaker 1: home range hardly at all. And I'm on entry and

630
00:33:23,720 --> 00:33:25,520
Speaker 1: exit trails in and around a food source that I'm

631
00:33:25,560 --> 00:33:28,120
Speaker 1: trying to take the deer, or I'm on an acorn

632
00:33:28,200 --> 00:33:31,280
Speaker 1: flat that has a bunch of you know, acorns falling,

633
00:33:31,920 --> 00:33:33,800
Speaker 1: and I'm trying to figure out where he's coming from,

634
00:33:33,840 --> 00:33:36,160
Speaker 1: where he's been, and I probably have an idea based

635
00:33:36,240 --> 00:33:39,720
Speaker 1: on historical you know, hunting of the farm, and I'm

636
00:33:39,880 --> 00:33:42,360
Speaker 1: I'm trying to kill him in and around that food

637
00:33:42,440 --> 00:33:46,200
Speaker 1: source of an afternoon, unless by chance I get a

638
00:33:46,240 --> 00:33:48,200
Speaker 1: strong north wind, then I'll try him of the morning.

639
00:33:48,560 --> 00:33:51,360
Speaker 1: First north is always gold, and we've talked about that

640
00:33:51,440 --> 00:33:54,280
Speaker 1: before on your podcast. I love the first morning the

641
00:33:54,320 --> 00:33:56,160
Speaker 1: winds out of the north Tomorrow morning? Is that for

642
00:33:56,320 --> 00:33:59,080
Speaker 1: us here? So, um, if we don't have too many

643
00:33:59,120 --> 00:34:01,520
Speaker 1: cocktails when Matt us here tonight, we might have to mark.

644
00:34:01,640 --> 00:34:04,680
Speaker 1: If not that we'll be out there tomorrow afternoon. But um,

645
00:34:05,280 --> 00:34:08,160
Speaker 1: I love that. Now that will change as you get

646
00:34:08,239 --> 00:34:11,640
Speaker 1: into late October. Then I'm I'm on scrapes, man. I've

647
00:34:11,680 --> 00:34:15,440
Speaker 1: got every scrape covered that I can find in what

648
00:34:15,600 --> 00:34:19,240
Speaker 1: I anticipate to be his home core. And then suddenly,

649
00:34:19,320 --> 00:34:22,480
Speaker 1: instead of the blitz Creek being very concentrated on a

650
00:34:22,560 --> 00:34:27,080
Speaker 1: small area, it expands as I anticipate the home range

651
00:34:27,160 --> 00:34:29,920
Speaker 1: is going to expand. In other words, Wade's deer was

652
00:34:30,000 --> 00:34:33,840
Speaker 1: fairly fairly consistent two hundred yards apart two major fields.

653
00:34:34,120 --> 00:34:36,280
Speaker 1: He was daylighting on both of them in the evenings.

654
00:34:36,640 --> 00:34:38,319
Speaker 1: Very rare for a six and af year old deer

655
00:34:38,760 --> 00:34:42,719
Speaker 1: to do. But you get into late October, all of

656
00:34:42,760 --> 00:34:45,520
Speaker 1: a sudden, home range is gonna expand, and you've got

657
00:34:45,640 --> 00:34:47,520
Speaker 1: to have a lot more scrapes covered to figure out

658
00:34:47,560 --> 00:34:49,680
Speaker 1: where he's gonna because that's what he's hitting at that time.

659
00:34:50,080 --> 00:34:53,640
Speaker 1: Right now, he's hitting food source. Late October, early November,

660
00:34:53,760 --> 00:34:57,160
Speaker 1: he's hitting scrapes. Get back through the rut, then I'm

661
00:34:57,239 --> 00:34:59,920
Speaker 1: on just where the heck is he gonna be at

662
00:35:00,000 --> 00:35:02,560
Speaker 1: a lot of randomness, so I'm on trails oftentimes then

663
00:35:03,000 --> 00:35:05,960
Speaker 1: and then late November I'm back into scrapes and food sources.

664
00:35:06,040 --> 00:35:08,960
Speaker 1: So you know, as we transition through the season, these

665
00:35:09,040 --> 00:35:11,600
Speaker 1: light switch events that we talked about in thirteen and

666
00:35:11,840 --> 00:35:14,839
Speaker 1: in Deer Season twenty two, then you know you can

667
00:35:15,000 --> 00:35:17,680
Speaker 1: you can adjust your tactics and all of this is

668
00:35:17,760 --> 00:35:19,839
Speaker 1: laid out in Deercast, like we talked, we break these

669
00:35:19,880 --> 00:35:23,200
Speaker 1: phases down, um, you know, as as deeply as we

670
00:35:23,320 --> 00:35:25,920
Speaker 1: can to help people understand what the deer doing at

671
00:35:25,960 --> 00:35:28,080
Speaker 1: different times of the year. Well, if you adjust your

672
00:35:28,120 --> 00:35:31,400
Speaker 1: camera strategy to what they're doing, you're gonna be so

673
00:35:31,560 --> 00:35:33,719
Speaker 1: much more effective. If you find a target buck, put

674
00:35:33,719 --> 00:35:35,839
Speaker 1: a lot of cameras on him, you're gonna up your

675
00:35:35,880 --> 00:35:41,200
Speaker 1: eyes for killing definitely seeing possibly killing him. Where does

676
00:35:41,600 --> 00:35:46,399
Speaker 1: where does glassing or observation fit into your data kind

677
00:35:46,440 --> 00:35:49,520
Speaker 1: of mix these days? Is that something you do much

678
00:35:49,600 --> 00:35:52,000
Speaker 1: still or with the advent of sell Kam's, do not

679
00:35:52,160 --> 00:35:54,320
Speaker 1: need to do that as much? I still do a

680
00:35:54,400 --> 00:35:57,680
Speaker 1: lot of it, a lot because a camera only shows

681
00:35:57,719 --> 00:36:00,879
Speaker 1: you one little spot right like they tell you a lot.

682
00:36:01,440 --> 00:36:04,359
Speaker 1: But they also don't tell you a lot if you will.

683
00:36:04,880 --> 00:36:11,239
Speaker 1: And that gets especially true in terrain and country that

684
00:36:11,600 --> 00:36:15,760
Speaker 1: is more difficult to anticipate and interpret. In other words,

685
00:36:15,880 --> 00:36:19,680
Speaker 1: like big open country throws hunters for a curve because

686
00:36:20,360 --> 00:36:24,080
Speaker 1: there they can be anywhere everywhere. You know tall grass,

687
00:36:24,200 --> 00:36:28,040
Speaker 1: big swampy areas that's all the same, all flat river bottoms,

688
00:36:28,400 --> 00:36:32,919
Speaker 1: big crp expanses, big tillable, those types of examples where

689
00:36:32,960 --> 00:36:38,040
Speaker 1: the it's really really big cover, they oftentimes are much

690
00:36:38,080 --> 00:36:41,840
Speaker 1: more random within and they're far much more difficult to pattern.

691
00:36:42,200 --> 00:36:46,280
Speaker 1: Contrast that with where we were last night, brushy, brushy,

692
00:36:47,000 --> 00:36:50,279
Speaker 1: heavy security cover, food right next to it. He's not

693
00:36:50,360 --> 00:36:52,920
Speaker 1: moving very far, he's got bet, he's got food, he's

694
00:36:52,920 --> 00:36:56,800
Speaker 1: got water. When that gets big, it's much more difficult

695
00:36:56,840 --> 00:37:00,920
Speaker 1: to pattern them. So I spread out and I watched that. Oftentimes,

696
00:37:00,960 --> 00:37:04,440
Speaker 1: as opposed to depend on cell cams, sometimes cell cams

697
00:37:04,840 --> 00:37:08,800
Speaker 1: or cameras in general will almost lock you into a

698
00:37:09,080 --> 00:37:11,359
Speaker 1: pattern and handcuff you or put you in a straight

699
00:37:11,440 --> 00:37:13,920
Speaker 1: jacket to where you can't make a good decision. And

700
00:37:14,040 --> 00:37:16,399
Speaker 1: sometimes you've got to get back out there, put eyes

701
00:37:16,400 --> 00:37:18,200
Speaker 1: on the ground, boots on the ground, and figured out

702
00:37:18,280 --> 00:37:20,279
Speaker 1: that way. So it really depends on the environment that

703
00:37:20,320 --> 00:37:23,200
Speaker 1: I'm dealing with. Yeah, and like when would you do

704
00:37:23,360 --> 00:37:25,880
Speaker 1: that kind of thing? Is that like, let's say you're

705
00:37:25,880 --> 00:37:28,600
Speaker 1: an environment or situation where you realize that I need

706
00:37:28,680 --> 00:37:30,839
Speaker 1: this additional intel, I need to go out and watch.

707
00:37:31,640 --> 00:37:33,239
Speaker 1: Are you just doing that on the nights and the

708
00:37:33,280 --> 00:37:35,800
Speaker 1: conditions aren't right to actually go in for a strike

709
00:37:35,880 --> 00:37:37,400
Speaker 1: and for a kill And you're like, well, there's not

710
00:37:37,520 --> 00:37:39,560
Speaker 1: a great opportunity to kill something right now, so I'm

711
00:37:39,600 --> 00:37:41,960
Speaker 1: going to sit back and watch. Or are you doing

712
00:37:42,080 --> 00:37:44,640
Speaker 1: this every morning in October when you're not hunting? Or

713
00:37:45,000 --> 00:37:48,480
Speaker 1: what does that actually look like? You hit two nails

714
00:37:48,520 --> 00:37:50,920
Speaker 1: on the head. Both of those examples are exactly when

715
00:37:50,960 --> 00:37:54,640
Speaker 1: I do it, and then I do it when the

716
00:37:55,360 --> 00:37:58,879
Speaker 1: camera reports and the cell cams have me scratching my head.

717
00:37:59,360 --> 00:38:02,839
Speaker 1: In other words, is like this buck was here last year,

718
00:38:03,200 --> 00:38:06,120
Speaker 1: but I'm not getting him this year. Did he switch

719
00:38:06,239 --> 00:38:08,760
Speaker 1: to one part of the field, you know as buck's age.

720
00:38:08,840 --> 00:38:11,400
Speaker 1: That's another part of the equation and another part of

721
00:38:11,920 --> 00:38:14,960
Speaker 1: of pattering a deer. What they do at age three

722
00:38:15,520 --> 00:38:18,040
Speaker 1: varies differently from four or five, and then when they

723
00:38:18,080 --> 00:38:21,520
Speaker 1: get to six or seven, suddenly things start to shrink.

724
00:38:21,560 --> 00:38:24,120
Speaker 1: If you took a circle, and it would be very

725
00:38:24,239 --> 00:38:27,239
Speaker 1: large at age three, it's slowly but truly shrinks. As

726
00:38:27,280 --> 00:38:29,239
Speaker 1: a deer age is you get into six, seven or eight,

727
00:38:29,560 --> 00:38:31,279
Speaker 1: if you could find where he's at, you could kill

728
00:38:31,320 --> 00:38:33,880
Speaker 1: it because he's not moving very far. They get slow.

729
00:38:33,960 --> 00:38:36,759
Speaker 1: Their metabolism slows way down. They get almost a little

730
00:38:36,760 --> 00:38:40,640
Speaker 1: bit lazy. I oftentimes use an analogy of an older

731
00:38:40,760 --> 00:38:43,840
Speaker 1: pet and older dog as you watch them age through life.

732
00:38:44,160 --> 00:38:47,040
Speaker 1: Take a cat, you know that's you know, age one

733
00:38:47,160 --> 00:38:49,920
Speaker 1: or two. That thing's bouncing off the walls half today.

734
00:38:50,000 --> 00:38:53,000
Speaker 1: You know, by this time that's ten or twelve, it's

735
00:38:53,120 --> 00:38:55,920
Speaker 1: laying around, sleeping all day. And dogs are are very

736
00:38:56,000 --> 00:38:59,399
Speaker 1: much the same. Puppy versus you know a dog that's ten,

737
00:38:59,440 --> 00:39:02,759
Speaker 1: eleven or two, well and deer are this exact same way,

738
00:39:03,160 --> 00:39:05,520
Speaker 1: So you have to always keep in mind what age

739
00:39:05,600 --> 00:39:08,279
Speaker 1: is he and water His mannerism is gonna be like,

740
00:39:08,520 --> 00:39:10,560
Speaker 1: and am I off of him just a little bit?

741
00:39:11,120 --> 00:39:13,759
Speaker 1: Is he here but my cameras aren't seeing him? I

742
00:39:13,880 --> 00:39:17,000
Speaker 1: need to go watch from afar if it's possible, and

743
00:39:17,160 --> 00:39:19,200
Speaker 1: perhaps try to find him, and that that has worked

744
00:39:19,400 --> 00:39:22,480
Speaker 1: many times for me. So it's it really comes down

745
00:39:22,560 --> 00:39:25,200
Speaker 1: to the environment and the age of the deer now

746
00:39:25,400 --> 00:39:29,400
Speaker 1: and and the weather right like we're in this terrible

747
00:39:29,440 --> 00:39:32,120
Speaker 1: pattern two years in a row of these every day

748
00:39:32,200 --> 00:39:34,680
Speaker 1: it's ten degrees above normal temperatures. I don't know if

749
00:39:34,680 --> 00:39:36,440
Speaker 1: it's like that three oup in Michigan, but it has

750
00:39:36,520 --> 00:39:39,560
Speaker 1: been for us here. And it's like the Law Ninia

751
00:39:39,640 --> 00:39:42,040
Speaker 1: force that's out in the Pacific has set a new

752
00:39:42,160 --> 00:39:45,080
Speaker 1: normal to the to the deer movement. What used to

753
00:39:45,120 --> 00:39:47,560
Speaker 1: be a poor on deer cast is now really and

754
00:39:47,680 --> 00:39:51,160
Speaker 1: okay because the deer have adjusted to these warmer temperatures.

755
00:39:51,280 --> 00:39:53,439
Speaker 1: That's gonna switch in March or April when it turns

756
00:39:53,480 --> 00:39:56,160
Speaker 1: over to to an l Nno. But the Law Union

757
00:39:56,239 --> 00:39:58,920
Speaker 1: has really smoked us here in the Midwest, both in

758
00:39:59,160 --> 00:40:02,480
Speaker 1: overall rainfall an overall average temperature the last couple of seasons.

759
00:40:02,520 --> 00:40:05,520
Speaker 1: And we've gone through these before, um you know, in

760
00:40:05,680 --> 00:40:07,480
Speaker 1: years past, so we kind of know how to adjust

761
00:40:07,480 --> 00:40:09,319
Speaker 1: to it. I don't have you been above norm there

762
00:40:09,600 --> 00:40:12,520
Speaker 1: where you live. It's been pretty warm throughout the summer. Yeah,

763
00:40:12,880 --> 00:40:15,000
Speaker 1: we're in a little bit of a better place the

764
00:40:15,120 --> 00:40:19,120
Speaker 1: last like seven eight, nine, ten days. It's finally can't

765
00:40:19,160 --> 00:40:23,799
Speaker 1: drop down. Finally got two normal, right exactly, So now

766
00:40:24,239 --> 00:40:26,360
Speaker 1: normal is the new coal front. It hasn't get for

767
00:40:26,400 --> 00:40:29,600
Speaker 1: the last seasons. It's it's crazy. And that's all through

768
00:40:29,680 --> 00:40:32,160
Speaker 1: that Londini's effect on us out there in the Pacific.

769
00:40:32,239 --> 00:40:37,320
Speaker 1: It's it has a huge effect on overall environment rainfall

770
00:40:37,600 --> 00:40:55,719
Speaker 1: and thus, dear moment. That's interesting, this this situation in

771
00:40:55,800 --> 00:40:58,160
Speaker 1: which we realize that we need to get more intel

772
00:40:58,280 --> 00:41:01,400
Speaker 1: and we need to go out and actually watch. The

773
00:41:01,480 --> 00:41:04,840
Speaker 1: perfect situation, I think is is where you can drive

774
00:41:05,239 --> 00:41:07,440
Speaker 1: to somewhere and sit in your truck and glass from

775
00:41:07,440 --> 00:41:10,560
Speaker 1: a hill, let's say, a super safe, great view. You've

776
00:41:10,600 --> 00:41:12,920
Speaker 1: got an opening you can looking down down into. That

777
00:41:13,080 --> 00:41:16,200
Speaker 1: sounds easy, like that's an easy option. But what about

778
00:41:16,239 --> 00:41:19,759
Speaker 1: a situation where you don't have that hill that you

779
00:41:19,840 --> 00:41:22,399
Speaker 1: can safely get up on top of and you if

780
00:41:22,440 --> 00:41:24,279
Speaker 1: you wanted to learn more about what this deer is

781
00:41:24,600 --> 00:41:27,480
Speaker 1: is doing, you would have to get in there and

782
00:41:27,560 --> 00:41:29,759
Speaker 1: climb up into a tree or something. Do you ever

783
00:41:29,920 --> 00:41:32,320
Speaker 1: do that kind of thing anymore, like an actual observation

784
00:41:32,480 --> 00:41:35,880
Speaker 1: sit And if so, how do you do that in

785
00:41:35,920 --> 00:41:37,759
Speaker 1: a way that you feel confident you can get the

786
00:41:37,840 --> 00:41:41,120
Speaker 1: intel you need without damaging things? Is that you know?

787
00:41:41,400 --> 00:41:44,920
Speaker 1: What's your thoughts on that? I actually absolutely do it,

788
00:41:45,320 --> 00:41:48,719
Speaker 1: and um I did it on the nine of October two.

789
00:41:48,920 --> 00:41:51,680
Speaker 1: I was sharing that story with you before we started recording.

790
00:41:51,880 --> 00:41:53,680
Speaker 1: There was a buck that I had pictures of them

791
00:41:53,719 --> 00:41:57,120
Speaker 1: in brand new spot, and you know, I went in there.

792
00:41:57,239 --> 00:42:00,040
Speaker 1: We have a blind kind of set up where we

793
00:42:00,200 --> 00:42:02,480
Speaker 1: think we can kill him, but we're also like, we're

794
00:42:02,560 --> 00:42:04,200
Speaker 1: probably gonna have to move this or go to a

795
00:42:04,239 --> 00:42:06,680
Speaker 1: different tree or whatever, so let's go have to sit

796
00:42:06,760 --> 00:42:08,279
Speaker 1: there and see if we see him. And what do

797
00:42:08,360 --> 00:42:10,120
Speaker 1: you know, he walks in twenty five yards and I

798
00:42:10,560 --> 00:42:12,440
Speaker 1: goofed the whole situation up and I don't even get

799
00:42:12,480 --> 00:42:14,440
Speaker 1: my bow draw because I was in a bad position.

800
00:42:14,560 --> 00:42:16,239
Speaker 1: I kind of had my head out of the game,

801
00:42:16,320 --> 00:42:19,160
Speaker 1: and I got very excited, very quickly, and I really

802
00:42:19,480 --> 00:42:22,800
Speaker 1: really botched it up and and just screwed up on

803
00:42:23,160 --> 00:42:25,480
Speaker 1: a really big deer. But I was doing it that night.

804
00:42:25,719 --> 00:42:28,840
Speaker 1: So I do a lot of observation sits. And I

805
00:42:28,960 --> 00:42:31,920
Speaker 1: think one of those situations would be, you know, like

806
00:42:32,160 --> 00:42:34,960
Speaker 1: say it's a big timber track and it's just lots

807
00:42:35,000 --> 00:42:36,680
Speaker 1: of timber, and you know the deer in there, but

808
00:42:37,160 --> 00:42:40,160
Speaker 1: you know outside of camera photos, or you're not gonna

809
00:42:40,160 --> 00:42:42,480
Speaker 1: observe that timber because you can't see him there. You've

810
00:42:42,560 --> 00:42:45,120
Speaker 1: just got to be very wise about the days you'll

811
00:42:45,160 --> 00:42:47,480
Speaker 1: go in there and where you're gonna sit and how

812
00:42:47,520 --> 00:42:51,239
Speaker 1: you're gonna set up. Like I love. I love high

813
00:42:51,320 --> 00:42:54,920
Speaker 1: pressure days thirty point give me thirty point one and rising,

814
00:42:55,360 --> 00:42:58,120
Speaker 1: and I feel much more confident going into a timber

815
00:42:58,320 --> 00:43:03,320
Speaker 1: and affecting less then on a point eight with cloud

816
00:43:03,440 --> 00:43:06,640
Speaker 1: cover and swirly winds, where you're gonna affect a lot

817
00:43:06,719 --> 00:43:09,879
Speaker 1: of stuff. So be wise about the weather conditions when

818
00:43:09,920 --> 00:43:12,760
Speaker 1: you choose to go do it, and be wise about

819
00:43:12,800 --> 00:43:16,480
Speaker 1: your access and then affect less. I don't walk and

820
00:43:16,600 --> 00:43:20,160
Speaker 1: scout a tremendous a lot tremendous amount during the season.

821
00:43:20,520 --> 00:43:22,520
Speaker 1: I do all of that in the off season, I

822
00:43:22,640 --> 00:43:25,600
Speaker 1: walk the you know, leather off the bottom of the

823
00:43:25,680 --> 00:43:29,760
Speaker 1: shoes shed hunting and the off season, but come season,

824
00:43:30,160 --> 00:43:33,840
Speaker 1: I am really cautious about getting in there and scouting

825
00:43:34,040 --> 00:43:37,240
Speaker 1: an area unless the weather is just absolutely pristine and perfect,

826
00:43:37,280 --> 00:43:41,160
Speaker 1: because I think the worst thing you can do as

827
00:43:41,200 --> 00:43:44,200
Speaker 1: a hunter is bounce a deer out of where you're

828
00:43:44,200 --> 00:43:46,520
Speaker 1: trying to kill him. I mean, unless you just don't care,

829
00:43:46,719 --> 00:43:48,960
Speaker 1: you know, unless you're you know, like you know, I'm

830
00:43:49,000 --> 00:43:50,840
Speaker 1: not in it trying to pattern the bucket. I'm in

831
00:43:50,920 --> 00:43:53,160
Speaker 1: it to go and enjoy myself, and I want to

832
00:43:53,239 --> 00:43:55,680
Speaker 1: go cover some ground on this track of ground today

833
00:43:55,719 --> 00:43:57,879
Speaker 1: and see what the deer sign looks like and jump

834
00:43:57,960 --> 00:44:00,600
Speaker 1: into tree saddle and see if I kill one that's okay.

835
00:44:01,000 --> 00:44:02,880
Speaker 1: The great thing about deer hunting, there's a lot of

836
00:44:02,960 --> 00:44:06,360
Speaker 1: different techniques where you can kill them. My personal technique

837
00:44:06,400 --> 00:44:10,719
Speaker 1: and my personal desire is to never affect the deer

838
00:44:10,840 --> 00:44:12,720
Speaker 1: and try not to let them know they're being haunted.

839
00:44:12,800 --> 00:44:15,040
Speaker 1: That's because that's worked for me in the past. So

840
00:44:15,160 --> 00:44:18,239
Speaker 1: therefore I'm very cautious about those days that I'll go

841
00:44:18,440 --> 00:44:21,399
Speaker 1: do that that technique where I'm actually trying to gain

842
00:44:21,480 --> 00:44:24,600
Speaker 1: intel by going into their world, if you will. Yeah,

843
00:44:25,320 --> 00:44:29,320
Speaker 1: So when you're doing an observation sit or you're glassing,

844
00:44:30,600 --> 00:44:35,800
Speaker 1: what specifically, And I'm sure the answer is everything, but

845
00:44:36,320 --> 00:44:38,760
Speaker 1: I guess I'm looking for a little bit more nuanced

846
00:44:38,760 --> 00:44:41,040
Speaker 1: as far as what specifically are you looking for? Like

847
00:44:41,160 --> 00:44:43,680
Speaker 1: what are the things like you sit, you see the

848
00:44:43,719 --> 00:44:47,080
Speaker 1: buck pop out in your mind? What are the key

849
00:44:47,239 --> 00:44:51,480
Speaker 1: data points that you need to preserve from that observation? Uh?

850
00:44:51,880 --> 00:44:53,880
Speaker 1: And how do you then do that? So you you

851
00:44:54,080 --> 00:44:56,560
Speaker 1: you see the buck, let's say, do you go home?

852
00:44:56,680 --> 00:44:58,160
Speaker 1: Do you go pull up deer cast and put in

853
00:44:58,200 --> 00:44:59,759
Speaker 1: the notes like Okay, I saw him and he came

854
00:44:59,800 --> 00:45:01,759
Speaker 1: from here and he did X and and all that,

855
00:45:02,000 --> 00:45:05,160
Speaker 1: or how do you take advantage of a sighting and

856
00:45:06,040 --> 00:45:08,279
Speaker 1: squeeze that for as much as possible? Maybe That's what

857
00:45:08,360 --> 00:45:12,240
Speaker 1: I'm getting at. It definitely goes back into that overall

858
00:45:13,200 --> 00:45:17,160
Speaker 1: data bank, if you will, of what's the crop rotation,

859
00:45:17,560 --> 00:45:19,279
Speaker 1: what phase are we in, what time of the year

860
00:45:19,360 --> 00:45:23,200
Speaker 1: is it, what is the weather like today? What made

861
00:45:23,320 --> 00:45:27,399
Speaker 1: him move during daylight? Where did he come from? Where

862
00:45:27,480 --> 00:45:30,279
Speaker 1: is he going? It's really as simple as what I

863
00:45:30,360 --> 00:45:33,719
Speaker 1: just said right there, Where did he bed? Where is

864
00:45:33,719 --> 00:45:36,719
Speaker 1: he heading to feed? Or if it's a later and

865
00:45:36,880 --> 00:45:39,120
Speaker 1: I'm speaking in terms of where I'm at right now

866
00:45:39,160 --> 00:45:41,719
Speaker 1: in the season, which is you know, early October, and

867
00:45:41,760 --> 00:45:44,560
Speaker 1: they're they're on food patterns. That's going to change drastically

868
00:45:44,640 --> 00:45:47,720
Speaker 1: coming up here because the home ranges are going to expand.

869
00:45:47,760 --> 00:45:50,520
Speaker 1: And then in November it's you know, bar the door there,

870
00:45:50,640 --> 00:45:53,560
Speaker 1: they're all over the Dad Come place. So all of

871
00:45:53,640 --> 00:45:57,920
Speaker 1: those different factors have to be either journals are remembered,

872
00:45:58,280 --> 00:46:01,560
Speaker 1: are put into that overall data bag of of your

873
00:46:02,000 --> 00:46:06,680
Speaker 1: personal dear memory slash history, slash predictive model, whatever that

874
00:46:06,840 --> 00:46:08,960
Speaker 1: is for you as a person. It has to be

875
00:46:09,080 --> 00:46:12,359
Speaker 1: documented some way so that you can and eight years,

876
00:46:12,440 --> 00:46:17,520
Speaker 1: ten years, seven years, go back, not necessarily to reflect

877
00:46:17,640 --> 00:46:20,920
Speaker 1: on that dear, but reflect on what the dear in

878
00:46:21,040 --> 00:46:25,120
Speaker 1: general do with those conditions when they repeat, because when

879
00:46:25,200 --> 00:46:30,000
Speaker 1: weather conditions repeat and mass crop repeats and crop rotation repeats,

880
00:46:30,560 --> 00:46:33,439
Speaker 1: the dear in general will most likely act and bed

881
00:46:33,600 --> 00:46:36,319
Speaker 1: the same way that they are when you made that observation.

882
00:46:37,880 --> 00:46:42,320
Speaker 1: So something you said there made me. It triggered a

883
00:46:42,440 --> 00:46:47,120
Speaker 1: situation that I've oftentimes found myself in wondering about UH,

884
00:46:47,239 --> 00:46:49,839
Speaker 1: and I think it has it's tied to this kind

885
00:46:49,840 --> 00:46:52,480
Speaker 1: of observation type situation where you see a deer do

886
00:46:52,680 --> 00:46:55,279
Speaker 1: something and then you think about, Okay, what was the

887
00:46:55,320 --> 00:46:58,719
Speaker 1: wind doing on at that particular time, and why did

888
00:46:58,800 --> 00:47:00,520
Speaker 1: he come from where he came from, and why was

889
00:47:00,560 --> 00:47:03,840
Speaker 1: he going where he was going. One of the dilemmas

890
00:47:03,880 --> 00:47:07,920
Speaker 1: I oftentimes find myself is that I'm looking at a

891
00:47:08,080 --> 00:47:11,479
Speaker 1: daylight photo or I'm looking at some piece of data

892
00:47:11,520 --> 00:47:14,440
Speaker 1: that says, okay, that buck was in here on this day.

893
00:47:14,520 --> 00:47:17,640
Speaker 1: What was the wind you know that day? And I'll say, okay,

894
00:47:17,680 --> 00:47:21,320
Speaker 1: it's a northwest or whatever. But then maybe it was

895
00:47:21,360 --> 00:47:24,880
Speaker 1: different in the morning versus the evening. And I guess

896
00:47:25,480 --> 00:47:29,239
Speaker 1: I'm curious, what do you think matters more when it

897
00:47:29,320 --> 00:47:31,360
Speaker 1: comes to predicting what a buck's going to do? Is

898
00:47:31,520 --> 00:47:33,799
Speaker 1: is the wind in the morning when he went back

899
00:47:33,840 --> 00:47:36,960
Speaker 1: to bed the most important thing to predict what he's

900
00:47:36,960 --> 00:47:39,680
Speaker 1: gonna do? Or is it the wind in the evening

901
00:47:40,120 --> 00:47:43,040
Speaker 1: when he comes out to his food source, like which

902
00:47:43,120 --> 00:47:47,160
Speaker 1: is influencing his behavior more? Um, I don't know if

903
00:47:47,160 --> 00:47:49,120
Speaker 1: I'm explaining this question, what does that make sense? Mark?

904
00:47:49,760 --> 00:47:52,400
Speaker 1: Are you? Are you talking in terms of speed or direction?

905
00:47:52,680 --> 00:47:56,680
Speaker 1: I was thinking direction, but both of the interesting um,

906
00:47:58,040 --> 00:48:02,560
Speaker 1: wind speed is what I pay most attention to. I

907
00:48:02,719 --> 00:48:08,120
Speaker 1: pay almost no attention to win direction as it pertains

908
00:48:08,200 --> 00:48:12,000
Speaker 1: to a bucks paninable and predictive movements as much as

909
00:48:12,040 --> 00:48:18,279
Speaker 1: I do speed. Um, I am not one that conforms

910
00:48:18,360 --> 00:48:23,520
Speaker 1: to the thought that the direction of wind will dictate

911
00:48:25,560 --> 00:48:28,400
Speaker 1: a lot for a deer. I'm sure it does, but

912
00:48:28,560 --> 00:48:33,160
Speaker 1: I don't think it's as important as as I as

913
00:48:33,239 --> 00:48:36,359
Speaker 1: I think some people think it is. If that makes sense,

914
00:48:36,440 --> 00:48:39,120
Speaker 1: just that's just based on my observations. I'm much more

915
00:48:39,239 --> 00:48:43,440
Speaker 1: interested in the speed and his overall demeanor, which I

916
00:48:43,520 --> 00:48:46,319
Speaker 1: think speed has a great deal to do with. Then

917
00:48:46,400 --> 00:48:49,520
Speaker 1: I am the direction of the wind, So tell me

918
00:48:49,520 --> 00:48:51,440
Speaker 1: a little bit more about that then. So if if

919
00:48:51,760 --> 00:48:55,080
Speaker 1: the speed is really what might be influencing, I mean,

920
00:48:55,120 --> 00:48:56,960
Speaker 1: are you saying my influence whether or not a buck

921
00:48:57,000 --> 00:48:59,520
Speaker 1: were to come out in daylight again, or if you

922
00:48:59,560 --> 00:49:03,719
Speaker 1: know he's will be more active? Absolutely? Yeah. And that's

923
00:49:04,360 --> 00:49:07,200
Speaker 1: combined with a lot of other weather factors, and when

924
00:49:07,400 --> 00:49:10,479
Speaker 1: when a lot of them optimize, that's when you see

925
00:49:10,920 --> 00:49:14,359
Speaker 1: those magical days. It's like, holy shoot. So three shooters tonight,

926
00:49:14,440 --> 00:49:17,840
Speaker 1: you know, or I saw thirty deer, But you know,

927
00:49:18,360 --> 00:49:20,520
Speaker 1: the other night I set the same place, and I

928
00:49:20,600 --> 00:49:23,239
Speaker 1: saw three deer, and you know, a lot of things

929
00:49:23,280 --> 00:49:26,680
Speaker 1: were similar, but all of a sudden when several things optimized,

930
00:49:26,719 --> 00:49:29,279
Speaker 1: like we're about to do that tomorrow and the next

931
00:49:29,360 --> 00:49:32,399
Speaker 1: day at least here in the Midwest, there's a bunch

932
00:49:32,440 --> 00:49:37,120
Speaker 1: of weather factors that are optimizing, and we're we're very

933
00:49:37,200 --> 00:49:40,000
Speaker 1: anxious for this this next three or four day period here,

934
00:49:40,600 --> 00:49:43,200
Speaker 1: can you can you in a way that won't you know,

935
00:49:43,280 --> 00:49:45,920
Speaker 1: give away too much information? Would you be willing to

936
00:49:46,120 --> 00:49:50,279
Speaker 1: walk me through you know what you're how you're gonna

937
00:49:50,320 --> 00:49:52,680
Speaker 1: take advantage of this optimal set of conditions, and how

938
00:49:52,840 --> 00:49:56,160
Speaker 1: you are going to you know, pattern or try to

939
00:49:56,280 --> 00:49:58,320
Speaker 1: take advantage of a pattern that you've been developing with

940
00:49:58,440 --> 00:49:59,920
Speaker 1: with the buck of your own. Is there in the

941
00:50:00,000 --> 00:50:02,600
Speaker 1: example you could share of like this is what he's

942
00:50:02,640 --> 00:50:04,960
Speaker 1: done in the history, this is what the pictures tell me. Now,

943
00:50:05,160 --> 00:50:08,080
Speaker 1: this is how this lines up with the current weather pattern.

944
00:50:08,200 --> 00:50:10,440
Speaker 1: And is there a case study that we have here

945
00:50:10,480 --> 00:50:17,440
Speaker 1: that might work to discuss Uh? No, because of the

946
00:50:17,920 --> 00:50:20,399
Speaker 1: three of the I shouldn't answer it that way. Yes

947
00:50:20,440 --> 00:50:24,560
Speaker 1: there is, but in this year this instance, three of

948
00:50:24,680 --> 00:50:27,680
Speaker 1: the bucks that I'm hunting are bucks that don't home

949
00:50:27,800 --> 00:50:30,239
Speaker 1: core on my farms, like I'm waiting for them to

950
00:50:30,280 --> 00:50:31,920
Speaker 1: show and then I'm gonna go hunt them, and none

951
00:50:31,960 --> 00:50:36,000
Speaker 1: of them are on there right now, so because I

952
00:50:36,400 --> 00:50:40,360
Speaker 1: hunt a lot of small parcels and therefore I'm just

953
00:50:40,560 --> 00:50:43,239
Speaker 1: off oftentimes, so i gotta wait for them to come in.

954
00:50:44,080 --> 00:50:48,319
Speaker 1: Um So, in direct answer to your question, and then

955
00:50:48,400 --> 00:50:50,719
Speaker 1: the other one that I'm hunting, I've really got four

956
00:50:50,920 --> 00:50:53,440
Speaker 1: targets that I'm hunting this year, and the other one

957
00:50:53,680 --> 00:50:56,279
Speaker 1: I think does live there a lot. However, the wind

958
00:50:56,360 --> 00:50:59,080
Speaker 1: direction is completely wrong to hunting over the next few days.

959
00:50:59,320 --> 00:51:02,400
Speaker 1: So um So, that's why my simple answer was no.

960
00:51:02,800 --> 00:51:07,080
Speaker 1: In terms of who I'm hunting right now. However, Mattson

961
00:51:07,440 --> 00:51:10,200
Speaker 1: Perry's got a tag. So there are other bucks that

962
00:51:10,320 --> 00:51:13,680
Speaker 1: I think are going to play quite well through these conditions,

963
00:51:14,000 --> 00:51:17,120
Speaker 1: and that's looking at historical data. They're bucks that have

964
00:51:17,239 --> 00:51:20,560
Speaker 1: been there at their lives and the conditions are lining up.

965
00:51:20,960 --> 00:51:23,439
Speaker 1: If we can put them to bed, we should see

966
00:51:23,480 --> 00:51:25,600
Speaker 1: them and possibly kill them. It's exactly what we did

967
00:51:25,719 --> 00:51:29,359
Speaker 1: last night with Wades. So and the reason I say

968
00:51:29,400 --> 00:51:33,440
Speaker 1: that is because I've had many days over the past

969
00:51:33,680 --> 00:51:36,719
Speaker 1: ten days where I've had a buck early morning on

970
00:51:36,760 --> 00:51:40,360
Speaker 1: a sub cam and go he's not coming out tonight.

971
00:51:40,400 --> 00:51:43,600
Speaker 1: The weather conditions aren't right. I don't think he's gonna

972
00:51:43,640 --> 00:51:45,759
Speaker 1: daylight tonight, and therefore we choose not to go in there,

973
00:51:45,760 --> 00:51:48,600
Speaker 1: and more often than not, he did not. That's going

974
00:51:48,640 --> 00:51:52,000
Speaker 1: to change um here with this weather front, we're gonna

975
00:51:52,040 --> 00:51:55,880
Speaker 1: be below normal temperatures. We've got cold north winds, and

976
00:51:56,600 --> 00:52:00,439
Speaker 1: these weather fronts, I will say that through an union,

977
00:52:00,480 --> 00:52:03,640
Speaker 1: when you get them, they're that much more important because

978
00:52:04,280 --> 00:52:07,560
Speaker 1: we get so few. When you get one, Holy cow, man,

979
00:52:07,680 --> 00:52:10,200
Speaker 1: they're all on the feet, and they're moving a little

980
00:52:10,200 --> 00:52:12,600
Speaker 1: bit further than moving earlier than moving a little farther,

981
00:52:12,920 --> 00:52:15,239
Speaker 1: it's pretty cool. What's about to happen here in the

982
00:52:15,280 --> 00:52:18,520
Speaker 1: middle of So that raises another question. Then we've got

983
00:52:18,719 --> 00:52:22,040
Speaker 1: maybe three main categories of data. I guess you could

984
00:52:22,080 --> 00:52:24,640
Speaker 1: say that might help us make a decision. One of

985
00:52:24,680 --> 00:52:29,280
Speaker 1: those categories is historical data, so past sightings, past pictures.

986
00:52:30,080 --> 00:52:32,640
Speaker 1: This The next thing is like our recent intel. So

987
00:52:32,800 --> 00:52:34,839
Speaker 1: what are our cell cameras are telling us right now?

988
00:52:35,360 --> 00:52:37,399
Speaker 1: Or what is the regular camera that we checked within

989
00:52:37,480 --> 00:52:39,560
Speaker 1: the last few days tell us right now? That's the

990
00:52:39,600 --> 00:52:42,360
Speaker 1: second category, and the third category is all of the

991
00:52:42,520 --> 00:52:48,440
Speaker 1: weather conditioned environment type stuff that might impact something. Now

992
00:52:48,560 --> 00:52:50,919
Speaker 1: that we have that recent you know, now that cell

993
00:52:51,000 --> 00:52:55,040
Speaker 1: cameras have entered the picture, how is that? You know,

994
00:52:55,360 --> 00:52:58,000
Speaker 1: how has that changed the value of one of the

995
00:52:58,880 --> 00:53:02,480
Speaker 1: those different categories. Is historical patterns? Is that less important

996
00:53:02,520 --> 00:53:06,360
Speaker 1: now because you've got this recent intel or is it?

997
00:53:06,520 --> 00:53:08,640
Speaker 1: Is it still on equal plant Is it in equal

998
00:53:08,680 --> 00:53:13,800
Speaker 1: playing field? It just makes it that much more effective

999
00:53:13,840 --> 00:53:18,440
Speaker 1: and validates what your assumptions are much quicker for you, right,

1000
00:53:19,560 --> 00:53:23,239
Speaker 1: are invalidates right? So Raconics has a saying, see what

1001
00:53:23,320 --> 00:53:26,080
Speaker 1: you've been missing? Well, South Camp's also you have what

1002
00:53:26,280 --> 00:53:30,560
Speaker 1: you haven't been missing, Like I've got suitors that we

1003
00:53:30,719 --> 00:53:33,800
Speaker 1: had summer to intel on that I have anticipated to

1004
00:53:33,840 --> 00:53:35,920
Speaker 1: show up on certain forms that they just haven't yet.

1005
00:53:36,440 --> 00:53:38,480
Speaker 1: So it tells you not to go there until they do.

1006
00:53:39,320 --> 00:53:42,920
Speaker 1: So the fourth piece of that, you name three very

1007
00:53:42,960 --> 00:53:45,680
Speaker 1: important ones. I would divide the weather in the environment

1008
00:53:46,120 --> 00:53:50,239
Speaker 1: literally into those two categories. So weather data guess and

1009
00:53:50,360 --> 00:53:53,920
Speaker 1: then environment which I always look at prop rotation and mascots,

1010
00:53:53,960 --> 00:53:56,640
Speaker 1: so food source. You know, weather is going to affect

1011
00:53:56,680 --> 00:53:59,560
Speaker 1: how they feed, what's planted where, and what the mass

1012
00:53:59,600 --> 00:54:04,399
Speaker 1: crop is going to affect where they feed. So those

1013
00:54:04,440 --> 00:54:08,160
Speaker 1: two things in combination can help you get ahead of

1014
00:54:08,239 --> 00:54:11,600
Speaker 1: where he's going to be as as opposed to behind. Yeah,

1015
00:54:12,560 --> 00:54:16,000
Speaker 1: what about when some of these things conflict? So what

1016
00:54:16,239 --> 00:54:25,240
Speaker 1: if you have a uh, what if the weather is lousy,

1017
00:54:25,800 --> 00:54:27,200
Speaker 1: if it's not as good as it should be, but

1018
00:54:27,360 --> 00:54:29,520
Speaker 1: you have a two year in a row kind of

1019
00:54:29,560 --> 00:54:32,880
Speaker 1: annual pattern that this buck always starts cruising through here

1020
00:54:32,920 --> 00:54:36,759
Speaker 1: the last week of October and he's been rock solid here,

1021
00:54:37,239 --> 00:54:41,319
Speaker 1: you know, going crazy the last two years, and now

1022
00:54:41,440 --> 00:54:43,919
Speaker 1: that arrives this year and you're just not loving the weather.

1023
00:54:44,080 --> 00:54:46,240
Speaker 1: But you know the historically he's been moving in daylight

1024
00:54:46,360 --> 00:54:49,120
Speaker 1: during that time period. In that kind of example or

1025
00:54:49,200 --> 00:54:52,279
Speaker 1: some other example where two or or three of these

1026
00:54:52,320 --> 00:54:56,000
Speaker 1: different things don't all line up, do you, dude, which

1027
00:54:56,040 --> 00:54:58,000
Speaker 1: do you trust? Like do you always fall back and say, well,

1028
00:54:58,160 --> 00:54:59,759
Speaker 1: history says he's going to start moving through here, so

1029
00:54:59,800 --> 00:55:01,839
Speaker 1: I to give it a shot, or do you now

1030
00:55:02,040 --> 00:55:05,399
Speaker 1: wait until the cell cameras confirm it? You know, irrefutably,

1031
00:55:06,600 --> 00:55:08,320
Speaker 1: it's it depends on the time of the year. So

1032
00:55:08,560 --> 00:55:12,160
Speaker 1: in answer to that question, at I'm hunting him whether

1033
00:55:12,239 --> 00:55:16,239
Speaker 1: it's great weather or not, because his testosterones at a

1034
00:55:16,320 --> 00:55:19,400
Speaker 1: level it's gonna kind of trump the weather a little bit.

1035
00:55:19,480 --> 00:55:22,759
Speaker 1: You don't need nearly as great a weather to kill

1036
00:55:22,840 --> 00:55:25,040
Speaker 1: them then as you do now. When they're in a

1037
00:55:25,120 --> 00:55:27,560
Speaker 1: food pattern and moving the hundred yards from their bed

1038
00:55:27,600 --> 00:55:30,160
Speaker 1: to their feed each day, even though it's less of

1039
00:55:30,200 --> 00:55:33,440
Speaker 1: a distance, it takes much better conditions for them to daylight.

1040
00:55:33,560 --> 00:55:36,080
Speaker 1: And I'm I'm speaking in terms of older deer. That

1041
00:55:36,360 --> 00:55:38,560
Speaker 1: doesn't mean that a year and a half or two

1042
00:55:38,600 --> 00:55:40,279
Speaker 1: and a half won't do it. But if you're hunting

1043
00:55:40,360 --> 00:55:42,600
Speaker 1: five or six year old deer, man, things better be

1044
00:55:42,840 --> 00:55:45,920
Speaker 1: awfully perfect to get that sucker up and seem during daylight,

1045
00:55:45,960 --> 00:55:49,719
Speaker 1: because they're walking slow, they stand up, they stretch, they

1046
00:55:49,800 --> 00:55:53,840
Speaker 1: browse around. They're just late moving during daylight, you know.

1047
00:55:53,920 --> 00:55:57,680
Speaker 1: And it's it's very difficult to get close enough to

1048
00:55:57,840 --> 00:56:02,200
Speaker 1: see a deer of age six of an evening or

1049
00:56:02,280 --> 00:56:05,880
Speaker 1: of a morning. It's extremely difficult to get in that

1050
00:56:06,160 --> 00:56:09,440
Speaker 1: short period are a short distance that they're going to

1051
00:56:09,520 --> 00:56:12,279
Speaker 1: move during daylight. It's much easier to do so in

1052
00:56:12,400 --> 00:56:16,719
Speaker 1: late October earlier November, when the distance increases and when

1053
00:56:16,840 --> 00:56:21,400
Speaker 1: testosterone is higher and they're actually moving moving better. You know,

1054
00:56:21,520 --> 00:56:24,399
Speaker 1: they just move better this time of the year. They're finicky. Man,

1055
00:56:24,520 --> 00:56:26,719
Speaker 1: it's got to be all the all systems have to

1056
00:56:26,800 --> 00:56:29,600
Speaker 1: be green light to really expect to see a deer

1057
00:56:29,640 --> 00:56:33,560
Speaker 1: of that age class. So I answered that a little long,

1058
00:56:33,800 --> 00:56:38,960
Speaker 1: but I believe that's the correct answer to your question. Yeah, yeah,

1059
00:56:38,960 --> 00:56:42,520
Speaker 1: I follow you kind of back to the annual pattern thing.

1060
00:56:42,880 --> 00:56:45,400
Speaker 1: One other thing, I'm curious about how cell cameras have

1061
00:56:47,120 --> 00:56:49,080
Speaker 1: I guess you kind of said it. Sometimes they confirm

1062
00:56:49,160 --> 00:56:51,800
Speaker 1: what you what you believe, or you confirm your assumptions.

1063
00:56:51,880 --> 00:56:56,680
Speaker 1: But how has your thoughts on annual patterns evolved over

1064
00:56:56,719 --> 00:56:59,320
Speaker 1: the years, especially now that you maybe we can confirm

1065
00:56:59,400 --> 00:57:03,440
Speaker 1: them or or disprove them more accurately. Do you do

1066
00:57:03,520 --> 00:57:06,520
Speaker 1: you still see this to be a a pretty consistent

1067
00:57:06,680 --> 00:57:11,719
Speaker 1: thing that you can plan on. And how how tight

1068
00:57:12,320 --> 00:57:15,399
Speaker 1: of a repeat have you, you know, now seen things

1069
00:57:15,480 --> 00:57:17,080
Speaker 1: to be. Do you look at this and think, ma'am,

1070
00:57:17,560 --> 00:57:19,800
Speaker 1: if they did it the last year, they're likely to

1071
00:57:19,840 --> 00:57:22,400
Speaker 1: do it again on the same day, the same week,

1072
00:57:22,760 --> 00:57:28,040
Speaker 1: the same condition. Like what, I guess give me more

1073
00:57:28,040 --> 00:57:31,280
Speaker 1: on any better? I hear you and I get where

1074
00:57:31,320 --> 00:57:35,720
Speaker 1: you're going. And yes, I still believe that with every

1075
00:57:35,840 --> 00:57:40,400
Speaker 1: fiber of my being. However, there are factors that affected slightly.

1076
00:57:40,920 --> 00:57:43,440
Speaker 1: And I've mentioned in a few times in our conversation

1077
00:57:44,240 --> 00:57:48,840
Speaker 1: the environment with mass crop and and overall. You know,

1078
00:57:49,040 --> 00:57:53,000
Speaker 1: crop rotation affects it, cover affects it. You know, a

1079
00:57:53,080 --> 00:57:56,600
Speaker 1: farmer cutting a field one year, here's a great example,

1080
00:57:57,480 --> 00:58:00,400
Speaker 1: um brush got out of control on the CRP farm

1081
00:58:01,160 --> 00:58:03,720
Speaker 1: and that's where the buck was betting. And ff A

1082
00:58:03,840 --> 00:58:06,440
Speaker 1: got on that farmer's tail and said, you've got to

1083
00:58:06,480 --> 00:58:09,560
Speaker 1: clean that brusho off of their Last year it was

1084
00:58:09,600 --> 00:58:12,919
Speaker 1: all six but tall. This year it is seven inches tall.

1085
00:58:13,360 --> 00:58:17,720
Speaker 1: Those types of factors affect deer's bed and behavior greatly.

1086
00:58:17,840 --> 00:58:22,200
Speaker 1: So your overall awareness to your environment is just as

1087
00:58:22,240 --> 00:58:24,920
Speaker 1: important to the patterning of a deer as it is

1088
00:58:25,080 --> 00:58:27,720
Speaker 1: sitting in a computer and writing down all your notes

1089
00:58:27,760 --> 00:58:30,560
Speaker 1: and then looking at the notes and then looking backwards,

1090
00:58:30,920 --> 00:58:34,840
Speaker 1: like I always say, why, no matter whether it's a

1091
00:58:34,920 --> 00:58:38,400
Speaker 1: picture or a siting or anything else, why is he

1092
00:58:38,560 --> 00:58:41,080
Speaker 1: doing what he's doing today, whether that be direction of travel,

1093
00:58:41,120 --> 00:58:45,360
Speaker 1: whether that be moving, whether that be not moving, whether

1094
00:58:45,520 --> 00:58:47,320
Speaker 1: that be a neighbor saying, hey, I just saw this

1095
00:58:47,400 --> 00:58:49,120
Speaker 1: certain deer and you go, wait a minute, that's the

1096
00:58:49,160 --> 00:58:51,240
Speaker 1: deer I'm hunting over here. You know, I always go

1097
00:58:51,440 --> 00:58:56,000
Speaker 1: why what made things happen, whether that be something that

1098
00:58:56,160 --> 00:59:00,960
Speaker 1: happened consistently or whether it's something that changed. So, yes,

1099
00:59:01,080 --> 00:59:03,120
Speaker 1: I believe it with every fiber of my being, but

1100
00:59:03,680 --> 00:59:06,240
Speaker 1: you also have to be very nimble in the moment

1101
00:59:06,480 --> 00:59:10,560
Speaker 1: to accept change and go, dang it, my plan that

1102
00:59:10,640 --> 00:59:13,520
Speaker 1: I made in July in August is not coming to fruition.

1103
00:59:14,240 --> 00:59:16,520
Speaker 1: Why is it not coming to fruition? I had all

1104
00:59:16,600 --> 00:59:18,240
Speaker 1: this laid out, Man, I was gonna kill him on

1105
00:59:18,320 --> 00:59:21,720
Speaker 1: October the five. Well, why aren't you killing him? Um?

1106
00:59:22,760 --> 00:59:26,960
Speaker 1: There there's reasons because they it's the chess match that

1107
00:59:27,400 --> 00:59:32,480
Speaker 1: I think people get so addicted to. UM. So if

1108
00:59:32,560 --> 00:59:34,520
Speaker 1: you figure out the wise, and the more of the

1109
00:59:34,600 --> 00:59:37,160
Speaker 1: wise that you figure out, the more dear and the

1110
00:59:37,200 --> 00:59:41,800
Speaker 1: more mature dear you're you're gonna kill. So so let's

1111
00:59:41,840 --> 00:59:45,560
Speaker 1: go back to a little bit of the um, you know,

1112
00:59:45,680 --> 00:59:51,240
Speaker 1: the analyzing of all this data. So there's these different

1113
00:59:51,320 --> 00:59:54,600
Speaker 1: categories of data we've we've been discussing, and then there's

1114
00:59:54,640 --> 00:59:57,280
Speaker 1: what's gonna happen tomorrow or what's gonna happen next week,

1115
00:59:57,320 --> 00:59:59,280
Speaker 1: and we're trying to decide, okay, based on all this

1116
00:59:59,400 --> 01:00:01,840
Speaker 1: data we have of what's he gonna do tomorrow? And

1117
01:00:01,880 --> 01:00:06,480
Speaker 1: where stead I hunt? There's these different pieces of data

1118
01:00:06,480 --> 01:00:09,520
Speaker 1: that we can connect back to, back to history. So

1119
01:00:09,680 --> 01:00:12,440
Speaker 1: back to the picture we got yesterday, or back to

1120
01:00:12,520 --> 01:00:16,040
Speaker 1: the pattern he had last year. How tight of a

1121
01:00:16,400 --> 01:00:18,680
Speaker 1: connection or how many of these things have to line

1122
01:00:18,760 --> 01:00:20,760
Speaker 1: up before you were to go in there. And so

1123
01:00:20,960 --> 01:00:24,680
Speaker 1: my example would be, let's say you're trying to decide

1124
01:00:24,680 --> 01:00:26,800
Speaker 1: where to hunt the first week in October. Let's let's

1125
01:00:26,800 --> 01:00:29,600
Speaker 1: say later we'll say that, you know, last week of October,

1126
01:00:30,240 --> 01:00:33,920
Speaker 1: and you have daylight pictures of him, you know, yesterday

1127
01:00:33,960 --> 01:00:37,000
Speaker 1: and the day before with a certain wind speed and

1128
01:00:37,760 --> 01:00:41,440
Speaker 1: you know, good cold front kind of conditions that came

1129
01:00:41,480 --> 01:00:43,840
Speaker 1: passing through. Now you're saying, what should I do the

1130
01:00:43,920 --> 01:00:45,880
Speaker 1: next day? If the next day, if if you don't

1131
01:00:45,960 --> 01:00:49,760
Speaker 1: have that same condition, the same set of conditions in place,

1132
01:00:50,360 --> 01:00:52,400
Speaker 1: do you still move on it? Or do you want

1133
01:00:52,440 --> 01:00:55,600
Speaker 1: to have like Okay, I want the same location matched

1134
01:00:55,640 --> 01:00:58,160
Speaker 1: up with the same conditions before I jump in there

1135
01:00:58,200 --> 01:01:02,640
Speaker 1: and try to kill him again. I generally it's more

1136
01:01:02,720 --> 01:01:05,880
Speaker 1: often than not, you know, it's it's really about the weather.

1137
01:01:06,000 --> 01:01:08,480
Speaker 1: For me, Like, as you know, I am a slave

1138
01:01:08,600 --> 01:01:10,160
Speaker 1: to it. And I mean it's why we create a

1139
01:01:10,240 --> 01:01:13,600
Speaker 1: deer cast. Like I firmly believe that there are windows

1140
01:01:13,640 --> 01:01:17,320
Speaker 1: of opportunity each year that you're given with a daylight opportunity,

1141
01:01:17,480 --> 01:01:21,439
Speaker 1: and that all revolves around the weather and how close

1142
01:01:21,520 --> 01:01:24,480
Speaker 1: you can get to that dear's bed depending on the

1143
01:01:24,600 --> 01:01:27,400
Speaker 1: time of the year and and how far they're moving

1144
01:01:27,440 --> 01:01:31,920
Speaker 1: at that time of the year. So I'm pretty pretty

1145
01:01:31,960 --> 01:01:34,600
Speaker 1: discipline when it comes to making sure it's the right

1146
01:01:34,640 --> 01:01:38,480
Speaker 1: opportunity because I go back to my statement earlier saying

1147
01:01:39,040 --> 01:01:41,240
Speaker 1: I never want them to know that they're being hunted

1148
01:01:41,280 --> 01:01:44,200
Speaker 1: like that's I just I don't want them to kill

1149
01:01:44,280 --> 01:01:47,200
Speaker 1: me right like I'm trying to kill them. So in

1150
01:01:47,360 --> 01:01:51,520
Speaker 1: my mind, it's this me against them game of chess,

1151
01:01:52,280 --> 01:01:55,000
Speaker 1: and I want to be the one saying checkmate. I

1152
01:01:55,120 --> 01:01:58,280
Speaker 1: want to be the one. I don't want him to

1153
01:01:58,320 --> 01:02:01,560
Speaker 1: smell me, because to me, if a deer smells me

1154
01:02:01,640 --> 01:02:04,480
Speaker 1: and figures me out like it's it's just dangner over

1155
01:02:04,560 --> 01:02:06,680
Speaker 1: every time. I don't know if you've noticed that through time,

1156
01:02:06,720 --> 01:02:09,560
Speaker 1: but when they when they get you, they got you,

1157
01:02:10,040 --> 01:02:13,440
Speaker 1: So don't let them get you. Said, that's that should

1158
01:02:13,440 --> 01:02:17,720
Speaker 1: be a tee shirt when they get the gut because man,

1159
01:02:17,800 --> 01:02:20,200
Speaker 1: when they figured you out. Buddy, they're a lot better.

1160
01:02:20,480 --> 01:02:22,160
Speaker 1: They're a lot better at this than we are. And

1161
01:02:22,200 --> 01:02:24,760
Speaker 1: they're good at living. I said all the time. They

1162
01:02:24,800 --> 01:02:27,560
Speaker 1: are good at living, and they're terrible at dying. I mean,

1163
01:02:27,640 --> 01:02:30,240
Speaker 1: it is hard to kill a mature dear. And if

1164
01:02:30,320 --> 01:02:34,400
Speaker 1: you mess up and goof him up man alive, does

1165
01:02:34,440 --> 01:02:36,920
Speaker 1: it make him tougher that year and years years in

1166
01:02:36,960 --> 01:02:40,920
Speaker 1: the future. So I'm always I'm always betting on the

1167
01:02:41,000 --> 01:02:45,360
Speaker 1: come and betting terms. So I'm waiting, I'm waiting, I'm waiting,

1168
01:02:45,400 --> 01:02:47,960
Speaker 1: and I try to strike when when things line up,

1169
01:02:48,000 --> 01:02:50,280
Speaker 1: I want optimized everything to go in there and try

1170
01:02:50,320 --> 01:02:55,280
Speaker 1: and kill that deer. That's just me um. So you know,

1171
01:02:55,920 --> 01:02:59,160
Speaker 1: other days I'm out shooting those other days I'm filming someone.

1172
01:02:59,280 --> 01:03:02,040
Speaker 1: But if it's a specific target that I'm trying to hunt,

1173
01:03:02,720 --> 01:03:05,959
Speaker 1: I actually hunt him very few days, if that makes sense.

1174
01:03:06,040 --> 01:03:08,280
Speaker 1: I think back to the deer I've killed over the

1175
01:03:08,360 --> 01:03:12,640
Speaker 1: last few years. I've spent very few days actually where

1176
01:03:12,800 --> 01:03:16,920
Speaker 1: I thought I was going to kill him. You got

1177
01:03:17,000 --> 01:03:20,560
Speaker 1: a target buck that shows up, you get sell picture

1178
01:03:20,600 --> 01:03:23,120
Speaker 1: of him. Let's say two days in a row with

1179
01:03:24,120 --> 01:03:29,040
Speaker 1: north wind, nice good weather, and for whatever reason, you

1180
01:03:29,200 --> 01:03:32,160
Speaker 1: you couldn't be out hunting in this location because you

1181
01:03:32,320 --> 01:03:34,800
Speaker 1: went to Texas or you were somewhere else. But he's

1182
01:03:34,880 --> 01:03:39,160
Speaker 1: day letting twice in a row, day three totally different

1183
01:03:39,200 --> 01:03:42,920
Speaker 1: conditions though not as good, but he was daylight two

1184
01:03:43,000 --> 01:03:47,400
Speaker 1: days in a row. Are you Are you saying drop wind, speed,

1185
01:03:47,520 --> 01:03:52,280
Speaker 1: dropped clouds, rolled in, Yeah, or I may not go

1186
01:03:52,440 --> 01:03:54,640
Speaker 1: try him, but you're already behind a little bit like

1187
01:03:55,320 --> 01:03:58,640
Speaker 1: that's have you ever noticed about a mature buck? They

1188
01:03:58,880 --> 01:04:03,760
Speaker 1: seldom almost never daylight every single day for a week, right,

1189
01:04:04,320 --> 01:04:07,000
Speaker 1: If you you know you'll get a day here and

1190
01:04:07,080 --> 01:04:09,600
Speaker 1: a day there, there's some randomness to win their daylight.

1191
01:04:09,960 --> 01:04:12,800
Speaker 1: And that again, it's another reason we did our predicted model.

1192
01:04:13,200 --> 01:04:15,760
Speaker 1: It's like, why why did you day Oh? There, it

1193
01:04:15,920 --> 01:04:17,240
Speaker 1: is there, it is there, it is You put it

1194
01:04:17,320 --> 01:04:20,400
Speaker 1: all together in an algorithm with thirteen different variables, and

1195
01:04:21,000 --> 01:04:23,640
Speaker 1: we try to help people predict when the best movement's

1196
01:04:23,680 --> 01:04:26,160
Speaker 1: going to be when the optimized conditions are there. So

1197
01:04:26,560 --> 01:04:29,480
Speaker 1: I'm trying to pick those days for me personally, and

1198
01:04:29,520 --> 01:04:33,400
Speaker 1: I'm using historical data that I've compiled on that deer,

1199
01:04:33,640 --> 01:04:36,840
Speaker 1: on that farm, on the crops, everything all combined together

1200
01:04:37,280 --> 01:04:39,840
Speaker 1: to go there it is. There's the day. Here's where

1201
01:04:39,840 --> 01:04:43,280
Speaker 1: I'm gonna try and just try to be right more

1202
01:04:43,360 --> 01:04:45,760
Speaker 1: than you are wrong. But I'm still wrong a heck

1203
01:04:45,840 --> 01:04:47,600
Speaker 1: of a lot more than I'm right. I still I

1204
01:04:47,720 --> 01:04:50,800
Speaker 1: make a lot of bad judgments. We all are right,

1205
01:04:50,880 --> 01:04:53,520
Speaker 1: you know, like in in baseball they say you're very

1206
01:04:53,560 --> 01:04:55,880
Speaker 1: successful if you get you know, you're about two fifty.

1207
01:04:55,920 --> 01:04:59,000
Speaker 1: Your your successful one fourth at the time. Well, and

1208
01:04:59,240 --> 01:05:01,560
Speaker 1: in hunting, what would it be it was one hundreds

1209
01:05:01,560 --> 01:05:05,480
Speaker 1: of a time. You know, it's you're batting, you're batting

1210
01:05:05,560 --> 01:05:07,760
Speaker 1: under a hundred. I know that for a mature buck,

1211
01:05:07,920 --> 01:05:11,960
Speaker 1: you're batting way under average, very low. If you just

1212
01:05:12,400 --> 01:05:16,360
Speaker 1: what do you get the whole season? Maybe a chance

1213
01:05:16,480 --> 01:05:20,680
Speaker 1: to a chance to two or three and that's you know,

1214
01:05:20,800 --> 01:05:23,200
Speaker 1: that's hunting a lot. You don't get many chances. So

1215
01:05:24,080 --> 01:05:26,480
Speaker 1: when you take your shot, you know you need to

1216
01:05:26,520 --> 01:05:28,360
Speaker 1: try and have everything in your favor that you can.

1217
01:05:29,000 --> 01:05:32,000
Speaker 1: And that's one side of the equation. The other side

1218
01:05:32,040 --> 01:05:36,480
Speaker 1: of the equation is persistence and the numbers game does

1219
01:05:36,560 --> 01:05:39,560
Speaker 1: come up, there's a d factor and everything. In fact

1220
01:05:39,840 --> 01:05:41,960
Speaker 1: that night that I sat there and I saw that target.

1221
01:05:42,000 --> 01:05:45,280
Speaker 1: In my pre hunt interview, I talked about I haven't

1222
01:05:45,280 --> 01:05:47,520
Speaker 1: had a daylight photo of this deer. I've had one

1223
01:05:47,600 --> 01:05:50,040
Speaker 1: in the last month since he shut his velvet. I

1224
01:05:50,080 --> 01:05:52,720
Speaker 1: had had one daylight photo of him. And I said,

1225
01:05:53,280 --> 01:05:55,640
Speaker 1: but I believe he's here because I'm getting nighttime photos

1226
01:05:56,040 --> 01:05:58,120
Speaker 1: and there is a dow factor in hunting, and he's

1227
01:05:58,120 --> 01:06:01,440
Speaker 1: gonna daylight again soon. Sure enough, he daylighted that night

1228
01:06:01,520 --> 01:06:03,680
Speaker 1: and I goofed it up. I jacked it up terribly.

1229
01:06:04,080 --> 01:06:06,560
Speaker 1: But the two factor does come into play. But I

1230
01:06:06,680 --> 01:06:10,040
Speaker 1: have a locked in, freaking access. I had a perfect

1231
01:06:10,120 --> 01:06:13,320
Speaker 1: wind speed, I had a perfect wind direction to access it,

1232
01:06:13,600 --> 01:06:15,840
Speaker 1: so I felt safely that I could get there and

1233
01:06:15,880 --> 01:06:18,840
Speaker 1: then leave into that what is kind of a quasi

1234
01:06:19,280 --> 01:06:22,520
Speaker 1: observation set. Yet I might still kill him here. Well,

1235
01:06:22,880 --> 01:06:25,840
Speaker 1: it worked, but I goofed it up. So there's one

1236
01:06:25,880 --> 01:06:28,240
Speaker 1: of my chances this year. I know that I knew

1237
01:06:28,400 --> 01:06:31,240
Speaker 1: when it happened, got out there, I'm like, that's one

1238
01:06:31,320 --> 01:06:33,960
Speaker 1: of my few opportunities I'll have. And he's he's a

1239
01:06:34,200 --> 01:06:36,280
Speaker 1: he's a whopper man. This steer is really really big,

1240
01:06:36,400 --> 01:06:40,240
Speaker 1: and I jacked it up. I left there that night

1241
01:06:40,480 --> 01:06:43,080
Speaker 1: thinking I'll probably not have that chance again this year.

1242
01:06:43,240 --> 01:06:47,160
Speaker 1: That was my exact thoughts. So when you have this

1243
01:06:47,320 --> 01:06:49,240
Speaker 1: is this is off topic, but I can't help it.

1244
01:06:49,320 --> 01:06:53,680
Speaker 1: Ask like, when you have something like that happened, even

1245
01:06:54,080 --> 01:06:56,960
Speaker 1: someone has experienced and who has had as much success

1246
01:06:57,000 --> 01:07:01,160
Speaker 1: as you have, how do you, like says, deal with

1247
01:07:01,360 --> 01:07:03,240
Speaker 1: that and move on from it? Like, how how did

1248
01:07:03,280 --> 01:07:05,480
Speaker 1: you handle that night sitting and sitting in bed at

1249
01:07:05,520 --> 01:07:07,880
Speaker 1: home after you had this monster within range and you

1250
01:07:08,000 --> 01:07:13,040
Speaker 1: couldn't pull it together? What what do you do? Closer?

1251
01:07:13,080 --> 01:07:15,720
Speaker 1: In baseball's mentality, I have a lot of baseball analogies

1252
01:07:15,760 --> 01:07:18,280
Speaker 1: because I I watched every single pitch of every Cardinal

1253
01:07:18,360 --> 01:07:21,120
Speaker 1: game since I was like Ted right, I'd love baseball.

1254
01:07:21,440 --> 01:07:25,520
Speaker 1: So closer's mentality really terrible memory. Get over it quickly

1255
01:07:25,680 --> 01:07:27,920
Speaker 1: and move on. That's the best thing you can do

1256
01:07:28,720 --> 01:07:31,720
Speaker 1: um when it happens, because if you if you wear it,

1257
01:07:31,840 --> 01:07:33,560
Speaker 1: if it's in your mind and it's working on you,

1258
01:07:33,840 --> 01:07:35,520
Speaker 1: you're gonna goose the next one up and the next

1259
01:07:35,560 --> 01:07:37,760
Speaker 1: one up. Like you have to get over it within

1260
01:07:37,880 --> 01:07:41,000
Speaker 1: seconds and move on. That's all you can do. It happened,

1261
01:07:41,360 --> 01:07:44,240
Speaker 1: It's ancient history. Now use it to better yourself in

1262
01:07:44,280 --> 01:07:50,320
Speaker 1: the next situation. But get eliminate emotion from making mistakes.

1263
01:07:50,880 --> 01:07:52,880
Speaker 1: You have to or it will eat you up the

1264
01:07:52,960 --> 01:07:56,120
Speaker 1: full season. You're gonna goof it up. Trust me on experience,

1265
01:07:56,120 --> 01:07:58,640
Speaker 1: because when I was younger, I was I was the

1266
01:07:58,880 --> 01:08:01,640
Speaker 1: dumbest hunter man. I get so mad at situations because

1267
01:08:02,080 --> 01:08:04,520
Speaker 1: those bucks met so much to me. Right well, as

1268
01:08:04,560 --> 01:08:06,800
Speaker 1: I've aged, I've learned that you've got to get over

1269
01:08:06,880 --> 01:08:09,400
Speaker 1: and move on to the next, the next opportunity, because

1270
01:08:09,440 --> 01:08:11,520
Speaker 1: if you're not thinking with a clear head, you're not

1271
01:08:11,600 --> 01:08:13,760
Speaker 1: gonna put yourself in the right position the next time.

1272
01:08:13,960 --> 01:08:16,080
Speaker 1: And that's that's kind of mental side of the game.

1273
01:08:16,320 --> 01:08:18,040
Speaker 1: We're getting off topic here a little bit, but I

1274
01:08:18,160 --> 01:08:20,639
Speaker 1: think it is a very important part of the game,

1275
01:08:21,160 --> 01:08:24,760
Speaker 1: is keeping a clear head and keeping a positive attitude.

1276
01:08:25,240 --> 01:08:28,880
Speaker 1: I can't tell you I'm like a very optimistic person

1277
01:08:28,920 --> 01:08:32,800
Speaker 1: in general. And like I've learned a long time ago

1278
01:08:33,000 --> 01:08:37,240
Speaker 1: from a legend in our county, Paul sex Are. I

1279
01:08:37,439 --> 01:08:40,920
Speaker 1: was like maybe fourteen or fifteen, and he took the

1280
01:08:41,000 --> 01:08:43,599
Speaker 1: time to sit down and talk to me about turkey

1281
01:08:43,680 --> 01:08:45,880
Speaker 1: hunting and turkey hunting tactics, and the one thing that

1282
01:08:45,960 --> 01:08:50,280
Speaker 1: he said in that moment that night I had with him,

1283
01:08:50,360 --> 01:08:53,000
Speaker 1: he said, and it was really Joe, his brother that

1284
01:08:53,080 --> 01:08:55,400
Speaker 1: pointed it out. He said, Paul hunts like he's about

1285
01:08:55,439 --> 01:08:58,840
Speaker 1: to kill a turkey every single second of every single hunt,

1286
01:08:59,280 --> 01:09:03,280
Speaker 1: and that's kill so many and that type of focus

1287
01:09:03,360 --> 01:09:06,559
Speaker 1: and so it's reality you're talking about focus that will

1288
01:09:06,640 --> 01:09:10,599
Speaker 1: help you kill more game, especially with a positive attitude.

1289
01:09:10,880 --> 01:09:12,800
Speaker 1: I'm gonna kill him. I know I'm gonna kill him.

1290
01:09:12,840 --> 01:09:15,439
Speaker 1: He's here tonight. And you know what, Mark, I didn't

1291
01:09:15,520 --> 01:09:18,080
Speaker 1: have that on October the second I mentioned before we

1292
01:09:18,160 --> 01:09:20,320
Speaker 1: got on the phone. I went in a little rusty.

1293
01:09:20,400 --> 01:09:23,160
Speaker 1: This was my only second set of the season, and

1294
01:09:23,800 --> 01:09:26,960
Speaker 1: I was a little nonchalant about things that night, and

1295
01:09:27,080 --> 01:09:29,360
Speaker 1: it cost me a giant I should have been ready,

1296
01:09:29,479 --> 01:09:32,040
Speaker 1: I should have lived by the advice that I've lived

1297
01:09:32,080 --> 01:09:34,800
Speaker 1: by for all these years. And I didn't, and it

1298
01:09:35,000 --> 01:09:37,160
Speaker 1: cost me a deer. I didn't even get my bow drawn.

1299
01:09:37,200 --> 01:09:40,120
Speaker 1: I was so little prepared, and you know, and I've

1300
01:09:40,160 --> 01:09:43,160
Speaker 1: been in that situation a lot of times, but my

1301
01:09:43,320 --> 01:09:45,720
Speaker 1: mental games sucked that night and it cost me a deer.

1302
01:09:46,120 --> 01:09:48,200
Speaker 1: So it's not meat. But you know what, by the

1303
01:09:48,280 --> 01:09:50,080
Speaker 1: time I got to the truck was over it and

1304
01:09:50,200 --> 01:09:52,360
Speaker 1: I was thinking about the weather for the next night's time.

1305
01:09:52,640 --> 01:09:55,559
Speaker 1: I have learned that, like you gotta have a closer mentality,

1306
01:09:55,840 --> 01:10:12,320
Speaker 1: get over it quickly. Yeah, that's that's great advice. So,

1307
01:10:12,800 --> 01:10:15,120
Speaker 1: speaking of your target Bucks, I did want to return

1308
01:10:15,200 --> 01:10:17,960
Speaker 1: to a question I had related to your other target bucks.

1309
01:10:18,040 --> 01:10:20,680
Speaker 1: You mentioned how most of these deer are all like,

1310
01:10:20,880 --> 01:10:23,880
Speaker 1: not homebodies. They live somewhere else and they just occasionally

1311
01:10:23,960 --> 01:10:27,040
Speaker 1: come into your neck of the woods. How does your

1312
01:10:27,080 --> 01:10:30,599
Speaker 1: approach to patterning a deer change in that scenario when

1313
01:10:30,640 --> 01:10:32,599
Speaker 1: you when you have a deer that you know it's

1314
01:10:32,640 --> 01:10:35,719
Speaker 1: just an infrequent visitor. Does does anything we've talked about

1315
01:10:36,040 --> 01:10:40,720
Speaker 1: Is it different because of that circumstance in anyway? Deeper dive, man,

1316
01:10:40,920 --> 01:10:43,960
Speaker 1: deeper dive find every That's why I keep every picture.

1317
01:10:44,800 --> 01:10:47,599
Speaker 1: They're on their seldom. So every piece of every piece

1318
01:10:47,640 --> 01:10:50,519
Speaker 1: of the puzzle you get is so much more important

1319
01:10:50,600 --> 01:10:52,680
Speaker 1: than a homeboy who you get all the time. Right,

1320
01:10:52,760 --> 01:10:56,560
Speaker 1: It's like, um, you know, it's like that friend that

1321
01:10:56,720 --> 01:10:58,400
Speaker 1: you can see every day at the bar and go

1322
01:10:58,600 --> 01:11:01,800
Speaker 1: have a beer with him. You know what he's gonna do, right,

1323
01:11:01,840 --> 01:11:03,280
Speaker 1: you know when he's gonna be there. You know what

1324
01:11:03,360 --> 01:11:04,880
Speaker 1: he's gonna say when you sit down and have the

1325
01:11:05,439 --> 01:11:07,680
Speaker 1: beer with him. You know what stories he's gonna tell

1326
01:11:07,720 --> 01:11:11,400
Speaker 1: when he's had too many beers. Okay, the guy that

1327
01:11:11,520 --> 01:11:14,840
Speaker 1: you only see once a year, you can't wait to

1328
01:11:14,880 --> 01:11:17,040
Speaker 1: have that conversation. What are you gonna learn new? And

1329
01:11:17,400 --> 01:11:19,479
Speaker 1: you you're a little bit more in tune with that

1330
01:11:19,640 --> 01:11:23,400
Speaker 1: guy because it's it's it's something that occurs seldom. So

1331
01:11:23,560 --> 01:11:26,200
Speaker 1: there far, I have files on all of these deer.

1332
01:11:26,560 --> 01:11:29,000
Speaker 1: I know exactly when I've had pictures of them in

1333
01:11:29,040 --> 01:11:31,120
Speaker 1: the past. I know what the conditions were, I know

1334
01:11:31,200 --> 01:11:35,320
Speaker 1: what the crop rotation was. And in fact, the deer

1335
01:11:35,640 --> 01:11:38,280
Speaker 1: that I'm what I would consider my number one targets,

1336
01:11:38,360 --> 01:11:41,720
Speaker 1: he's really really large, but he was he was only

1337
01:11:41,800 --> 01:11:43,840
Speaker 1: on me I think, based on what I can tell

1338
01:11:44,120 --> 01:11:47,960
Speaker 1: a few hours last season. However, when the crop rotation

1339
01:11:48,080 --> 01:11:50,920
Speaker 1: was the same in two thousand and twenty, he was

1340
01:11:51,000 --> 01:11:54,599
Speaker 1: on me several days. So therefore my confidence is much

1341
01:11:54,680 --> 01:11:58,439
Speaker 1: higher about him this year. Who he is aged, he

1342
01:11:58,600 --> 01:12:02,000
Speaker 1: is aged, he was five six, he's seven and a

1343
01:12:02,040 --> 01:12:04,920
Speaker 1: half this year. My confidence is fairly high that when

1344
01:12:04,920 --> 01:12:07,679
Speaker 1: he gets to my farm, he if he's still alive,

1345
01:12:07,840 --> 01:12:09,920
Speaker 1: is if he hasn't been killed by another hunter or

1346
01:12:09,960 --> 01:12:11,800
Speaker 1: a car or e h D or something like that.

1347
01:12:12,320 --> 01:12:15,559
Speaker 1: If I get him I think he may stay enough

1348
01:12:15,680 --> 01:12:19,080
Speaker 1: days that I'll possibly have a shot at him. So

1349
01:12:19,840 --> 01:12:22,880
Speaker 1: that goes back to that environment. Cross rotation is exactly

1350
01:12:22,960 --> 01:12:24,960
Speaker 1: what it was in two thousand and twenty, not only

1351
01:12:25,040 --> 01:12:27,479
Speaker 1: on my farm but all of the surrounding area because

1352
01:12:27,520 --> 01:12:31,120
Speaker 1: I look at everything when it comes to deer hunting. Okay,

1353
01:12:31,200 --> 01:12:33,360
Speaker 1: so I know this is going to be situation dependent.

1354
01:12:33,600 --> 01:12:36,760
Speaker 1: But if we had to generalize, if you have a

1355
01:12:36,800 --> 01:12:41,240
Speaker 1: buck like this, do you in this kind of case

1356
01:12:41,360 --> 01:12:43,280
Speaker 1: in the world of cell cameras, are you always going

1357
01:12:43,360 --> 01:12:45,960
Speaker 1: to wait until you get the camera pictures say always back?

1358
01:12:46,320 --> 01:12:48,680
Speaker 1: Or is that sometimes too late? I want to be

1359
01:12:48,800 --> 01:12:52,719
Speaker 1: the camera, so I'm gonna be sitting there waiting because

1360
01:12:52,760 --> 01:12:55,360
Speaker 1: I've never taken very many pictures of him, so I

1361
01:12:55,479 --> 01:12:57,840
Speaker 1: damn well better be there the day I do. So

1362
01:12:57,880 --> 01:13:00,519
Speaker 1: I'm gonna use historical data to be there and try

1363
01:13:00,560 --> 01:13:03,040
Speaker 1: and be the camera. If that makes sense. So is

1364
01:13:03,080 --> 01:13:06,720
Speaker 1: it different different type buck, different type personality? Man? If

1365
01:13:06,760 --> 01:13:09,680
Speaker 1: you miss your opportunity, you're out. I've got great locations,

1366
01:13:09,760 --> 01:13:12,559
Speaker 1: I've got great access in and out. I'm gonna use them.

1367
01:13:12,560 --> 01:13:14,920
Speaker 1: I'm gonna hut them, and I'm gonna hunt on much.

1368
01:13:16,000 --> 01:13:19,240
Speaker 1: I will take my shots on lesser weather than what

1369
01:13:19,360 --> 01:13:22,120
Speaker 1: I normally would on a homeboy. On a homeboy that's

1370
01:13:22,160 --> 01:13:24,880
Speaker 1: not leaving, I don't want to run him out on

1371
01:13:24,960 --> 01:13:27,439
Speaker 1: a deer that seldom there. I better be there when

1372
01:13:27,479 --> 01:13:32,400
Speaker 1: he's there. So I'm gonna hunt a little more often. Okay, Um,

1373
01:13:33,320 --> 01:13:35,519
Speaker 1: what about you know, we've we've talked a lot about

1374
01:13:35,840 --> 01:13:39,080
Speaker 1: how patterning, you know, can be a pretty important thing

1375
01:13:39,160 --> 01:13:41,640
Speaker 1: in these earlier parts of the year, but when we

1376
01:13:41,680 --> 01:13:43,960
Speaker 1: get into the rut, things are a little bit different.

1377
01:13:44,320 --> 01:13:48,160
Speaker 1: How how does your approach to patterning deer change once

1378
01:13:48,200 --> 01:13:50,040
Speaker 1: we get into those rut phases? And and do you

1379
01:13:50,120 --> 01:13:51,960
Speaker 1: even think you can pattern a deer during the rut?

1380
01:13:53,000 --> 01:13:59,360
Speaker 1: My pattern changes ahead to texas well? There it is, there,

1381
01:13:59,400 --> 01:14:02,640
Speaker 1: it is. I am one of those guys that I

1382
01:14:03,360 --> 01:14:06,720
Speaker 1: don't want to say I hate the rut, but I

1383
01:14:07,320 --> 01:14:10,880
Speaker 1: much prefer hunting October and December O October and deer

1384
01:14:10,920 --> 01:14:15,360
Speaker 1: scemmer than I do November because the way that I

1385
01:14:15,560 --> 01:14:20,120
Speaker 1: hunt me personally. I hunt based on expectation and data

1386
01:14:20,520 --> 01:14:24,360
Speaker 1: and data points rather than hope. And when it comes

1387
01:14:24,439 --> 01:14:28,439
Speaker 1: to so it's expectation rather than hope. We're real good

1388
01:14:28,560 --> 01:14:30,400
Speaker 1: in and around the food source I mean, we kill

1389
01:14:30,439 --> 01:14:33,840
Speaker 1: a lot of deer, you know, food source, tuck close

1390
01:14:33,920 --> 01:14:36,240
Speaker 1: to cover. That's a that's an equation that has worked

1391
01:14:36,280 --> 01:14:38,840
Speaker 1: well for Terry and I for for quite a while. Now.

1392
01:14:39,320 --> 01:14:42,040
Speaker 1: When you get to November and they start spreading out

1393
01:14:42,400 --> 01:14:46,759
Speaker 1: and suddenly home core ranges get just go like shotgun approach,

1394
01:14:47,160 --> 01:14:49,519
Speaker 1: it's much more difficult to run into a deer. They're

1395
01:14:49,560 --> 01:14:52,920
Speaker 1: chasing those and and uh, we still kill them during

1396
01:14:52,960 --> 01:14:56,599
Speaker 1: that period and I still hunt them, but it gets

1397
01:14:56,760 --> 01:15:00,560
Speaker 1: much tougher to kill a specific deer, which is what

1398
01:15:00,680 --> 01:15:04,280
Speaker 1: I'm typically trying to do in November than it is,

1399
01:15:04,520 --> 01:15:10,080
Speaker 1: say in October and December. Yeah, does does any does

1400
01:15:10,120 --> 01:15:12,280
Speaker 1: any of this stuff still applied during the rut? Like

1401
01:15:12,360 --> 01:15:16,240
Speaker 1: are you gonna get you know, annual pattern type data

1402
01:15:16,360 --> 01:15:18,200
Speaker 1: and say, well, I'm hunting here the second week in

1403
01:15:18,240 --> 01:15:20,160
Speaker 1: November and he did this thing last year. Do you

1404
01:15:20,400 --> 01:15:22,479
Speaker 1: ever expect that kind of stuff to repeat during that

1405
01:15:22,560 --> 01:15:24,040
Speaker 1: part of the year or do those things it's just

1406
01:15:24,120 --> 01:15:29,120
Speaker 1: two random Yeah, they still repeat, like different things repeat though,

1407
01:15:29,240 --> 01:15:32,679
Speaker 1: Like let's fast forward out of October. Let's fast forward

1408
01:15:32,800 --> 01:15:36,800
Speaker 1: thirty days and go into early November. Fifth, seven, three

1409
01:15:36,880 --> 01:15:39,360
Speaker 1: or four of the best Dad Gum days, they're still

1410
01:15:39,479 --> 01:15:42,040
Speaker 1: hitting scrapes, they're still checking food sources for the first

1411
01:15:42,080 --> 01:15:44,800
Speaker 1: available dough. They're covering a lot more ground, so you

1412
01:15:44,920 --> 01:15:46,680
Speaker 1: can go back and look at that data and kill

1413
01:15:46,760 --> 01:15:49,960
Speaker 1: that deer doing those exact same things. When I speak

1414
01:15:50,000 --> 01:15:52,320
Speaker 1: of my disdain for the rut, it's really in and

1415
01:15:52,360 --> 01:15:56,200
Speaker 1: around once they start locking down. So twelve Levet's twelve

1416
01:15:56,280 --> 01:16:02,040
Speaker 1: and November through about the tenth eighteenth, that period right

1417
01:16:02,120 --> 01:16:05,160
Speaker 1: there is a very frustrating time for me. Um. I

1418
01:16:05,200 --> 01:16:07,280
Speaker 1: would much rather be in Missouri with a rifle in

1419
01:16:07,320 --> 01:16:09,519
Speaker 1: my hand, or where my range is extended, or in

1420
01:16:09,600 --> 01:16:12,200
Speaker 1: Texas where I feel like the bucks are still doing

1421
01:16:12,320 --> 01:16:15,000
Speaker 1: things like they were doing here in late October, because

1422
01:16:15,040 --> 01:16:17,280
Speaker 1: the run is later down there, so I kind of

1423
01:16:17,600 --> 01:16:20,519
Speaker 1: I kind of go south to get on a more

1424
01:16:20,920 --> 01:16:23,720
Speaker 1: palatable period, or I go to Missouri where we can

1425
01:16:23,800 --> 01:16:25,880
Speaker 1: have a good time and it's rifle season and you

1426
01:16:25,960 --> 01:16:27,400
Speaker 1: can stretch it out a little bit if you see

1427
01:16:27,439 --> 01:16:29,799
Speaker 1: a buck tending a dough, those types of things. However,

1428
01:16:30,280 --> 01:16:33,439
Speaker 1: just prior to lockdown and just after, absolutely you can

1429
01:16:33,479 --> 01:16:35,560
Speaker 1: go back and look at pictures and figure out a

1430
01:16:35,600 --> 01:16:38,720
Speaker 1: buck's pattern. It's just that they're covering more ground. And

1431
01:16:38,920 --> 01:16:43,160
Speaker 1: and and walking more during daylight. So therefore you you

1432
01:16:43,360 --> 01:16:45,439
Speaker 1: change where you're sitting. You're no longer sitting on a

1433
01:16:45,439 --> 01:16:47,679
Speaker 1: food plot, right, You're not. One of the dumbest places

1434
01:16:47,760 --> 01:16:49,760
Speaker 1: you can be is on a greenfield. You know, I

1435
01:16:49,840 --> 01:16:52,880
Speaker 1: get into transition, I get into the bedroom. I start

1436
01:16:53,000 --> 01:16:55,960
Speaker 1: hunting mornings, I start hunting full day sits. So the

1437
01:16:56,160 --> 01:17:00,679
Speaker 1: tactics changed drastically. But yes, you can absolutely kill buck

1438
01:17:00,720 --> 01:17:03,720
Speaker 1: in his bedroom. Uh, during that period of the year,

1439
01:17:03,840 --> 01:17:06,680
Speaker 1: especially when he ages. You take a deer, say you've

1440
01:17:06,720 --> 01:17:09,880
Speaker 1: been you know, fooled by this deer when he's three,

1441
01:17:10,000 --> 01:17:13,720
Speaker 1: four or five, and suddenly six, he may not move

1442
01:17:13,760 --> 01:17:17,280
Speaker 1: as much. Uh when he's seven, when he's eight, all

1443
01:17:17,280 --> 01:17:19,320
Speaker 1: of a sudden, he's gonna daylight a little bit more.

1444
01:17:19,720 --> 01:17:22,120
Speaker 1: It gets hungry a little bit more often, and you

1445
01:17:22,240 --> 01:17:25,519
Speaker 1: can start taking advantage of his weaknesses. One of the

1446
01:17:25,600 --> 01:17:28,320
Speaker 1: toughest did dear to kill is like a price, a

1447
01:17:28,360 --> 01:17:30,160
Speaker 1: deer in his prime at age four and five, They

1448
01:17:30,240 --> 01:17:33,040
Speaker 1: just they don't daylight quite as much. So six is

1449
01:17:33,080 --> 01:17:36,680
Speaker 1: also another another challenging year. So you always keep in

1450
01:17:36,760 --> 01:17:40,120
Speaker 1: mind the age of the deer, the overall environment. But yeah,

1451
01:17:40,200 --> 01:17:42,360
Speaker 1: you can you can smoke him during the run, you know,

1452
01:17:42,479 --> 01:17:44,439
Speaker 1: before they get with the does. Once they're with the does,

1453
01:17:44,560 --> 01:17:47,559
Speaker 1: that's when it gets a little real challenging. And I think,

1454
01:17:48,000 --> 01:17:51,120
Speaker 1: if you kill a deer that's tending a dough, you

1455
01:17:51,160 --> 01:17:53,439
Speaker 1: should really go buy a lottery ticket that day because

1456
01:17:53,439 --> 01:17:57,400
Speaker 1: you probably got fairly fortunate on that day. And that's

1457
01:17:57,439 --> 01:18:00,800
Speaker 1: the truth. But that's where that's where DO factor comes in.

1458
01:18:01,040 --> 01:18:04,120
Speaker 1: That's where I'm in good country. I know he's here.

1459
01:18:04,520 --> 01:18:08,240
Speaker 1: I Am going to spend every single solid daylight hour

1460
01:18:08,400 --> 01:18:12,080
Speaker 1: in a stand every single day to increase my odds.

1461
01:18:12,280 --> 01:18:14,720
Speaker 1: That's how you kill them once they're locked down, just

1462
01:18:14,960 --> 01:18:18,400
Speaker 1: absolute seat time in the stand. Yeah, let's say we're

1463
01:18:18,439 --> 01:18:21,320
Speaker 1: after one specific buck in a scenarre like you're describing.

1464
01:18:21,479 --> 01:18:23,880
Speaker 1: There's there's just the one guy that I really want

1465
01:18:23,920 --> 01:18:28,120
Speaker 1: to get and we do all the things you describe

1466
01:18:28,200 --> 01:18:30,600
Speaker 1: that do factor get out there, spend a lot of

1467
01:18:30,680 --> 01:18:33,560
Speaker 1: time being the general area. Is it a waste of

1468
01:18:33,640 --> 01:18:38,080
Speaker 1: time to chase cell camera pictures or to chase um?

1469
01:18:38,280 --> 01:18:40,240
Speaker 1: You know, well he did this two days ago. I

1470
01:18:40,360 --> 01:18:42,559
Speaker 1: think I got to be in this little corner um

1471
01:18:42,840 --> 01:18:46,240
Speaker 1: during that particular time of year, you know, November three

1472
01:18:46,360 --> 01:18:52,519
Speaker 1: th or something like that. Um, specifically, it's not a

1473
01:18:52,600 --> 01:18:54,679
Speaker 1: waste of time because you know he's there, and that's

1474
01:18:54,800 --> 01:18:57,559
Speaker 1: part of the equation that time of the year. Um,

1475
01:18:58,640 --> 01:19:01,200
Speaker 1: you know, you get in the rut, you go, oh, uh,

1476
01:19:01,680 --> 01:19:03,640
Speaker 1: where's my target. I haven't had a picture of him

1477
01:19:03,640 --> 01:19:06,120
Speaker 1: in six seven days. Well he's standing there looking at

1478
01:19:06,160 --> 01:19:08,160
Speaker 1: a girlfriend, you know. So when you get a self

1479
01:19:08,200 --> 01:19:11,479
Speaker 1: picture and you're like, I'm still here. So that's important.

1480
01:19:11,680 --> 01:19:15,640
Speaker 1: Just just having the deer in your hunting area is

1481
01:19:15,680 --> 01:19:18,439
Speaker 1: half the battle. So therefore get in there and hunt

1482
01:19:18,479 --> 01:19:21,880
Speaker 1: his butt, you know. Uh. Not having him changes that

1483
01:19:21,960 --> 01:19:25,280
Speaker 1: a little bit. Uh So the rut brings about like

1484
01:19:25,479 --> 01:19:28,120
Speaker 1: if we were having this conversation, I think a lot

1485
01:19:28,200 --> 01:19:31,080
Speaker 1: of what I would be talking about might switch up

1486
01:19:31,080 --> 01:19:33,360
Speaker 1: a little bit because right now my mind is so

1487
01:19:33,600 --> 01:19:38,720
Speaker 1: center focused on greener pastors early October, you know, food bad,

1488
01:19:38,840 --> 01:19:41,439
Speaker 1: that type of stuff. If we're having this conversation November five,

1489
01:19:41,840 --> 01:19:44,360
Speaker 1: I might answer some of these things differently, But my

1490
01:19:44,439 --> 01:19:46,800
Speaker 1: mind's wrapped around this right now, So I'm trying to

1491
01:19:46,880 --> 01:19:49,559
Speaker 1: fast forward and think how I will be thinking that time,

1492
01:19:49,720 --> 01:19:52,760
Speaker 1: you know. So it's it's different, you know, But I

1493
01:19:53,240 --> 01:19:56,160
Speaker 1: love fifth, six, seventh, eighth, and ninth absolutely love it.

1494
01:19:56,320 --> 01:19:59,320
Speaker 1: Mornings are great, does crisp cool mornings, you get good weather,

1495
01:19:59,360 --> 01:20:01,840
Speaker 1: You've got buck walk until nine ten o'clock in the morning.

1496
01:20:02,240 --> 01:20:05,160
Speaker 1: It's pretty exciting. I mean it can be a buck

1497
01:20:05,240 --> 01:20:07,160
Speaker 1: factory in certain days. When you get the right weather

1498
01:20:07,240 --> 01:20:09,639
Speaker 1: and and uh the right hot dough in the area,

1499
01:20:09,680 --> 01:20:11,800
Speaker 1: you you find the magic circle and you're gonna kill

1500
01:20:11,800 --> 01:20:15,040
Speaker 1: a deer. So it's it's an exciting time of the year. Yeah.

1501
01:20:15,479 --> 01:20:18,519
Speaker 1: So you mentioned that you you really prefer for your

1502
01:20:18,560 --> 01:20:20,439
Speaker 1: style of hunting the early part of the year and

1503
01:20:20,479 --> 01:20:23,040
Speaker 1: the later part of the year. Uh So, let's talk

1504
01:20:23,040 --> 01:20:26,720
Speaker 1: about the later part real quick. Is anything different in

1505
01:20:26,800 --> 01:20:29,400
Speaker 1: the late season when it comes to patterning deer compared

1506
01:20:29,439 --> 01:20:32,479
Speaker 1: to what we just described for that early, earlier stuff,

1507
01:20:32,840 --> 01:20:34,439
Speaker 1: or do you go right back to the same plane

1508
01:20:35,439 --> 01:20:39,639
Speaker 1: the vastly different that similar plan, but vastly different strategy

1509
01:20:39,680 --> 01:20:42,000
Speaker 1: in terms of food source, your keying in on, and

1510
01:20:42,200 --> 01:20:45,439
Speaker 1: most importantly, the thermal cover you're king in on where

1511
01:20:45,520 --> 01:20:48,559
Speaker 1: those bucks bed right now is going to be different

1512
01:20:48,800 --> 01:20:51,800
Speaker 1: than where they're bedding in December. Right now, they're trying

1513
01:20:51,840 --> 01:20:54,439
Speaker 1: to stay cool and they've got cover everywhere because there's

1514
01:20:54,520 --> 01:20:56,719
Speaker 1: leaves on all the trees. Get rid of all the leaves,

1515
01:20:57,000 --> 01:20:59,759
Speaker 1: change the temperature by thirty or forty degrees for daytime,

1516
01:21:00,439 --> 01:21:03,360
Speaker 1: and you've got a different system in place in terms

1517
01:21:03,400 --> 01:21:05,840
Speaker 1: of what the white tails trying to do. Uh, he's

1518
01:21:05,840 --> 01:21:09,080
Speaker 1: also in recovery mode as opposed to the mode he's

1519
01:21:09,120 --> 01:21:11,800
Speaker 1: in right now, which is eating everything he can because

1520
01:21:12,400 --> 01:21:14,600
Speaker 1: he's about to go crazy during the rut. So a

1521
01:21:14,720 --> 01:21:18,040
Speaker 1: lot of dynamics change there. Does that change it? Although

1522
01:21:18,360 --> 01:21:22,280
Speaker 1: how you actually try to pattern him like is the

1523
01:21:22,439 --> 01:21:25,960
Speaker 1: same kind of data. I understand that the the environmental

1524
01:21:26,040 --> 01:21:28,559
Speaker 1: factors are different. But when you sit down at night

1525
01:21:28,600 --> 01:21:30,240
Speaker 1: and try to say, Okay, what's this buck going to

1526
01:21:30,320 --> 01:21:33,559
Speaker 1: do tomorrow? Where should I hunt tomorrow? Are you are

1527
01:21:33,640 --> 01:21:39,040
Speaker 1: you weighing things differently? Are you more confident in behaviors, repeating,

1528
01:21:39,240 --> 01:21:41,080
Speaker 1: or anything else when you're actually trying to develop that

1529
01:21:41,160 --> 01:21:45,000
Speaker 1: pattern In December, I'm a little less confident, and in

1530
01:21:45,360 --> 01:21:50,160
Speaker 1: in December, I think December requires a much more optimized

1531
01:21:51,040 --> 01:21:56,280
Speaker 1: win or not win. But whether um occurrence then does

1532
01:21:56,360 --> 01:22:00,680
Speaker 1: October October, they seem a little more patterned bowl and

1533
01:22:00,800 --> 01:22:05,639
Speaker 1: a little more likely todaylight with perhaps a little less

1534
01:22:05,680 --> 01:22:08,360
Speaker 1: weather than in December. Man, it's got to be perfect

1535
01:22:08,520 --> 01:22:11,479
Speaker 1: and again I'm speaking in terms of not deer in general,

1536
01:22:11,880 --> 01:22:14,559
Speaker 1: but a target buck like a five six seven year

1537
01:22:14,560 --> 01:22:17,880
Speaker 1: old deer. Uh, they just act different in December. They're

1538
01:22:18,040 --> 01:22:21,120
Speaker 1: very tired. They may all of a sudden, if there's

1539
01:22:21,120 --> 01:22:24,519
Speaker 1: a little secondary estros, all of a sudden, you'll go

1540
01:22:24,680 --> 01:22:27,720
Speaker 1: do that. So you know, right now, in October you

1541
01:22:27,800 --> 01:22:29,519
Speaker 1: don't have much of that. December you do get a

1542
01:22:29,560 --> 01:22:32,519
Speaker 1: lot of it, especially if you're your herds out of balance,

1543
01:22:32,600 --> 01:22:35,880
Speaker 1: so that comes into play. Uh, December can be tricky,

1544
01:22:36,760 --> 01:22:39,719
Speaker 1: But I look back at historical patterns and I honestly

1545
01:22:39,840 --> 01:22:43,519
Speaker 1: like I almost preferred to Christmas and later. Like you

1546
01:22:43,680 --> 01:22:48,519
Speaker 1: take December third, somewhere and there all the way through

1547
01:22:48,560 --> 01:22:50,840
Speaker 1: the end of the season January ten, with the right

1548
01:22:50,920 --> 01:22:53,680
Speaker 1: weather conditions on a major thermal block, with the right

1549
01:22:53,760 --> 01:22:55,840
Speaker 1: food source, you're gonna go in there and see a

1550
01:22:56,000 --> 01:22:59,559
Speaker 1: pole of deer and possibly kill your number one target. Yeah,

1551
01:23:00,200 --> 01:23:04,519
Speaker 1: that does sound pretty pretty good to me. It sounds

1552
01:23:04,560 --> 01:23:09,120
Speaker 1: good right now. On the hot side, we can dream,

1553
01:23:09,200 --> 01:23:10,800
Speaker 1: we know what's in front of us, but you know,

1554
01:23:10,880 --> 01:23:12,920
Speaker 1: you gotta take each each day as it comes. And

1555
01:23:13,280 --> 01:23:15,759
Speaker 1: it's it's exactly why we did the show thirteam because

1556
01:23:15,840 --> 01:23:19,040
Speaker 1: so many things changed throughout the season, and as they change,

1557
01:23:19,280 --> 01:23:22,679
Speaker 1: our tactics have to change. Yeah, so let's let's zoom

1558
01:23:22,680 --> 01:23:24,519
Speaker 1: out a little bit. Let's talk a little bit more

1559
01:23:24,600 --> 01:23:30,439
Speaker 1: generally here again, thinking patterning deer, what is the most

1560
01:23:30,640 --> 01:23:34,840
Speaker 1: common or the most egregious mistake that you see other

1561
01:23:34,960 --> 01:23:37,920
Speaker 1: folks making when trying to pattern deer. You talked to

1562
01:23:38,000 --> 01:23:40,760
Speaker 1: a million deer hunters, You've been exposed to the whole

1563
01:23:40,800 --> 01:23:44,000
Speaker 1: community for decades. Now, what's that thing that you see

1564
01:23:44,120 --> 01:23:47,200
Speaker 1: keep on popping up that just makes you scratch your

1565
01:23:47,200 --> 01:23:49,639
Speaker 1: head or makes you want to, you know, shake somebody

1566
01:23:49,680 --> 01:23:53,720
Speaker 1: by the shoulders and say, don't do that anymore. I

1567
01:23:53,840 --> 01:23:57,000
Speaker 1: get asked this question a lot, and I answered consistently.

1568
01:23:57,080 --> 01:23:59,479
Speaker 1: But I'll add to this answer in this question because

1569
01:23:59,520 --> 01:24:06,560
Speaker 1: of the sub matter. Today, people underestimate the quarry. I

1570
01:24:06,680 --> 01:24:11,599
Speaker 1: think white tails are so good at living that they're

1571
01:24:11,640 --> 01:24:14,880
Speaker 1: almost impossible to go kill. They are so tough, and

1572
01:24:14,960 --> 01:24:18,200
Speaker 1: again I'm speaking of mature bucks that have been around

1573
01:24:18,240 --> 01:24:20,799
Speaker 1: the block. You take a six year old buck, and Buddy,

1574
01:24:20,880 --> 01:24:23,479
Speaker 1: he's a tough, tough son of a gun to even

1575
01:24:23,920 --> 01:24:26,120
Speaker 1: see during daylight. He's tough to take a picture of.

1576
01:24:26,240 --> 01:24:28,360
Speaker 1: He's even tougher to see, and then you got to

1577
01:24:28,400 --> 01:24:31,640
Speaker 1: have the capacity and the ability to kill him and

1578
01:24:31,720 --> 01:24:33,280
Speaker 1: then make a good shot and all the things that

1579
01:24:33,280 --> 01:24:36,560
Speaker 1: it's it's so hard to kill a giant. Okay, So

1580
01:24:38,120 --> 01:24:42,000
Speaker 1: you couple that with what all they've been through and

1581
01:24:42,040 --> 01:24:45,640
Speaker 1: the overall you know, health of the deer, and I

1582
01:24:45,760 --> 01:24:50,320
Speaker 1: think people just group deer as a deer. A buck

1583
01:24:50,439 --> 01:24:53,400
Speaker 1: is a buck is a buck. A deer is as

1584
01:24:53,439 --> 01:24:56,160
Speaker 1: good as gonna be just as healthy this year as

1585
01:24:56,200 --> 01:25:00,040
Speaker 1: he is next year. And I think they just the

1586
01:25:00,200 --> 01:25:03,080
Speaker 1: side of the fact of all the things that are

1587
01:25:03,120 --> 01:25:06,520
Speaker 1: affecting a white tailed deer on a daily basis. Imagine

1588
01:25:06,600 --> 01:25:08,599
Speaker 1: what they go through on a daily basis. First of all,

1589
01:25:08,640 --> 01:25:11,519
Speaker 1: we're trying to kill them. Second of all, you know,

1590
01:25:11,640 --> 01:25:14,840
Speaker 1: they're dealing with all these different changes, all of a sudden,

1591
01:25:14,840 --> 01:25:17,880
Speaker 1: as acorns everywhere one year, next year there's none. Uh,

1592
01:25:17,960 --> 01:25:19,800
Speaker 1: we're going through a drought. This year. You've got the

1593
01:25:19,960 --> 01:25:23,280
Speaker 1: h D hitting them, Kyle populations up. Holy cow, I

1594
01:25:23,360 --> 01:25:25,679
Speaker 1: got harned in the side. I've got an infection starting.

1595
01:25:26,720 --> 01:25:30,360
Speaker 1: I'm older. Oh I broke a leg. Oh oh, Trulie

1596
01:25:30,400 --> 01:25:33,000
Speaker 1: got hit by a car. I mean, there's a lot

1597
01:25:33,160 --> 01:25:36,640
Speaker 1: of different things that affect white tail behavior. And I

1598
01:25:36,800 --> 01:25:40,320
Speaker 1: think people gloss over that, and they look at every

1599
01:25:40,400 --> 01:25:41,960
Speaker 1: deer as a deer as a deer, and I think

1600
01:25:42,000 --> 01:25:46,479
Speaker 1: there are as different as people are um and and

1601
01:25:47,080 --> 01:25:50,439
Speaker 1: I will I will extend this answer into a general

1602
01:25:51,120 --> 01:25:54,599
Speaker 1: lack of organization. If you're trying to pattern a deer.

1603
01:25:54,640 --> 01:25:57,000
Speaker 1: There's nothing wrong with not being organized, because I know

1604
01:25:57,160 --> 01:25:59,559
Speaker 1: guys that aren't, and they go out and there they

1605
01:25:59,680 --> 01:26:02,360
Speaker 1: kill dandies every year because they they're just good and

1606
01:26:02,400 --> 01:26:05,240
Speaker 1: their prowess is good, and they're they're skillful. But I

1607
01:26:05,360 --> 01:26:09,160
Speaker 1: think people can help themselves if they're having an organizational

1608
01:26:10,160 --> 01:26:13,240
Speaker 1: trade and they keep good notes and they keep all

1609
01:26:13,280 --> 01:26:16,360
Speaker 1: their pictures. We all know this guy that's got a

1610
01:26:16,439 --> 01:26:19,200
Speaker 1: handful of SD cards and he just went through all

1611
01:26:19,240 --> 01:26:21,120
Speaker 1: of them and then he goes and puts them back

1612
01:26:21,160 --> 01:26:23,519
Speaker 1: in his cameras and he never kept one picture off.

1613
01:26:23,560 --> 01:26:28,080
Speaker 1: On one car cringe, there's duck, there's dust on them,

1614
01:26:28,080 --> 01:26:31,000
Speaker 1: they're sitting in the truck, there's soda and coffee spilt

1615
01:26:31,080 --> 01:26:34,320
Speaker 1: on them. You put him in the camera, they don't work.

1616
01:26:34,439 --> 01:26:36,160
Speaker 1: You go to the camera the next time. You didn't

1617
01:26:36,200 --> 01:26:40,439
Speaker 1: get any information. We all know that guy, right, And

1618
01:26:40,520 --> 01:26:43,320
Speaker 1: I'm not knocking that guy, because he's got every right

1619
01:26:43,400 --> 01:26:46,320
Speaker 1: to do that, as I have to be anal and

1620
01:26:46,920 --> 01:26:51,920
Speaker 1: obsessive over it. But I do think a general approach

1621
01:26:52,080 --> 01:26:56,400
Speaker 1: with more organization would help put people in better positions

1622
01:26:56,560 --> 01:27:02,160
Speaker 1: more often. Yeah, he you know that, Mark, I do

1623
01:27:02,320 --> 01:27:05,280
Speaker 1: know that guy taking by the shoulders. Next time you

1624
01:27:05,360 --> 01:27:09,920
Speaker 1: see I will. Oh. I'm curious and I don't know

1625
01:27:09,960 --> 01:27:14,240
Speaker 1: if there's many opportunities for you to have this happen anymore, Mark,

1626
01:27:14,400 --> 01:27:18,640
Speaker 1: But can you think back to the last time that

1627
01:27:18,920 --> 01:27:23,639
Speaker 1: you learned something from another really good deer hunter about

1628
01:27:23,720 --> 01:27:26,960
Speaker 1: patterning deer, so specifically about this idea of patterning deer.

1629
01:27:27,479 --> 01:27:29,880
Speaker 1: Is there someone you can think of who's really really

1630
01:27:29,920 --> 01:27:32,040
Speaker 1: good at it. Do you have that buddy that is

1631
01:27:32,160 --> 01:27:33,960
Speaker 1: as good or better than you at this and that

1632
01:27:34,080 --> 01:27:36,240
Speaker 1: you said, oh, wow, you know that's a good idea,

1633
01:27:36,439 --> 01:27:38,679
Speaker 1: or wow, I never thought of that. Is there anything

1634
01:27:38,760 --> 01:27:45,040
Speaker 1: that comes to mind? Brother Terry? Um, we talk almost

1635
01:27:45,280 --> 01:27:50,439
Speaker 1: daily during the deer season, and um, we just compare notes.

1636
01:27:50,520 --> 01:27:52,640
Speaker 1: What are your deer doing? What are you seeing? I mean,

1637
01:27:52,680 --> 01:27:55,320
Speaker 1: it's almost like coaches meeting or something, you know what

1638
01:27:55,360 --> 01:27:59,000
Speaker 1: I mean. We just talk and we pick up stuff

1639
01:27:59,080 --> 01:28:02,880
Speaker 1: from each other every day and I I love collective

1640
01:28:04,360 --> 01:28:10,400
Speaker 1: UM strategizing, so myself, Wade, Perry, it is ad nauseam

1641
01:28:10,800 --> 01:28:16,080
Speaker 1: for our wives Tracy Marista style like I. I think

1642
01:28:16,160 --> 01:28:18,760
Speaker 1: if they had shock callers with controls, they would buzz

1643
01:28:18,840 --> 01:28:20,960
Speaker 1: us every single dinner we have together during the deer

1644
01:28:21,320 --> 01:28:24,160
Speaker 1: because it is all we talk about from the moment

1645
01:28:24,240 --> 01:28:27,000
Speaker 1: we see each other in the morning. We're together usually

1646
01:28:27,120 --> 01:28:29,320
Speaker 1: ten two hours a day, every day, seven days a

1647
01:28:29,360 --> 01:28:34,719
Speaker 1: week deer hunt, deer season. But that collective thought comes

1648
01:28:34,760 --> 01:28:39,360
Speaker 1: to really good UM decision making. I do it with Terry,

1649
01:28:39,400 --> 01:28:41,280
Speaker 1: I do it with Wayne and Perry. I do it

1650
01:28:41,360 --> 01:28:44,880
Speaker 1: with Josh and Carson. I do it with matt Um.

1651
01:28:45,720 --> 01:28:48,600
Speaker 1: You know, Grant Woods, He's the all time goat as

1652
01:28:48,640 --> 01:28:51,559
Speaker 1: far as I'm concerned when it comes to dear behavior

1653
01:28:51,680 --> 01:28:54,640
Speaker 1: in the science of white tail deer, like Bobby Culvertson

1654
01:28:54,800 --> 01:28:57,720
Speaker 1: Tracker John. There's certain people in my circle that I

1655
01:28:57,840 --> 01:29:00,200
Speaker 1: talked to a lot, and I talked to him Um

1656
01:29:00,320 --> 01:29:03,799
Speaker 1: as much as I can so that I can pull information.

1657
01:29:03,880 --> 01:29:07,280
Speaker 1: I'm selfish, man. If there's something that somebody's gotten his mind,

1658
01:29:07,320 --> 01:29:09,920
Speaker 1: I want it, you know, because it's it's going to

1659
01:29:10,040 --> 01:29:12,439
Speaker 1: help you, and I'm happy to share it too. Like

1660
01:29:12,680 --> 01:29:15,920
Speaker 1: I think the more we talk and the more communication

1661
01:29:16,000 --> 01:29:18,800
Speaker 1: we have, the better we all get. It's why I

1662
01:29:19,000 --> 01:29:24,880
Speaker 1: think your podcast is so popular. Uh, you're constantly trying

1663
01:29:24,920 --> 01:29:27,840
Speaker 1: to teach. I think it's why, by and large, we've

1664
01:29:27,880 --> 01:29:30,519
Speaker 1: survived thirty three years in the outdoor industry. I say

1665
01:29:30,520 --> 01:29:32,040
Speaker 1: it all the time. We're not very good looking, we're

1666
01:29:32,040 --> 01:29:35,840
Speaker 1: not very funny. We better be informational. So um, I'm

1667
01:29:35,880 --> 01:29:40,960
Speaker 1: not saying you fit in that category. You know. I

1668
01:29:41,320 --> 01:29:44,800
Speaker 1: think if you're trying to teach and your teachers learn right,

1669
01:29:44,880 --> 01:29:47,760
Speaker 1: they're they're hungry for information. So I do it all

1670
01:29:47,800 --> 01:29:50,200
Speaker 1: the time every day. I think that what just what

1671
01:29:50,400 --> 01:29:55,240
Speaker 1: makes us better. And also I'm at a very interesting

1672
01:29:55,360 --> 01:29:58,120
Speaker 1: time in my life because I'm fifty five, and I

1673
01:29:58,240 --> 01:30:01,839
Speaker 1: think I forget as much every day as as I remember.

1674
01:30:02,200 --> 01:30:04,360
Speaker 1: So therefar there are things that Wade and Perry will

1675
01:30:04,680 --> 01:30:07,320
Speaker 1: tell me, you know, last year you were saying this,

1676
01:30:07,400 --> 01:30:09,759
Speaker 1: and I'll be like, oh, yeah, that's right. I've forgotten

1677
01:30:09,840 --> 01:30:12,160
Speaker 1: some of what I knew. And if people out there

1678
01:30:12,240 --> 01:30:14,719
Speaker 1: that are in their fifties will relate to that comment.

1679
01:30:14,920 --> 01:30:18,439
Speaker 1: So it's it's a little tongue in cheek, but it's honestly,

1680
01:30:18,520 --> 01:30:21,200
Speaker 1: there's a little truth to that. So I use these guys,

1681
01:30:21,280 --> 01:30:23,240
Speaker 1: I use their eyes and ears when we're in the blind,

1682
01:30:23,560 --> 01:30:26,200
Speaker 1: and I'm starting to use their mind to remind me, hey,

1683
01:30:26,439 --> 01:30:30,439
Speaker 1: what did we do in this situation when this occurred

1684
01:30:30,560 --> 01:30:32,680
Speaker 1: last time? And they they have better memories than I do,

1685
01:30:32,920 --> 01:30:36,920
Speaker 1: so uh, it's I think collective organization and collective thought

1686
01:30:37,320 --> 01:30:39,760
Speaker 1: is a beautiful thing and it's gonna lead you down

1687
01:30:39,920 --> 01:30:42,600
Speaker 1: really good paths in life, whether that be you know,

1688
01:30:42,680 --> 01:30:44,479
Speaker 1: in terms of deer hunting, or whether that be in

1689
01:30:44,640 --> 01:30:47,679
Speaker 1: terms of your business, or whether that is in terms

1690
01:30:47,720 --> 01:30:54,960
Speaker 1: of relationship. I love communication on all facets, sports, life, religion, politics,

1691
01:30:55,240 --> 01:30:57,640
Speaker 1: deer hunting, you name it. I'll sit and talk with

1692
01:30:57,720 --> 01:31:01,160
Speaker 1: anybody for for hours, because man, just just be the

1693
01:31:01,200 --> 01:31:03,880
Speaker 1: sponge out there and learn all you can. Yeah. Yeah,

1694
01:31:03,960 --> 01:31:06,680
Speaker 1: I love that idea of collective decision making and it's

1695
01:31:06,800 --> 01:31:08,760
Speaker 1: it's a lot of fun doing it that way. But

1696
01:31:08,840 --> 01:31:11,120
Speaker 1: then also I do think, you know, like when you're

1697
01:31:11,160 --> 01:31:13,439
Speaker 1: trying to figure out what this buck's pattern is, you

1698
01:31:13,520 --> 01:31:15,960
Speaker 1: can sometimes get stuck in your own head or stuck

1699
01:31:16,000 --> 01:31:18,479
Speaker 1: in your own assumptions. But if you just get one

1700
01:31:18,520 --> 01:31:20,160
Speaker 1: other set of eyes on it all of a sudden,

1701
01:31:20,160 --> 01:31:22,120
Speaker 1: they might notice the one thing that you never saw

1702
01:31:22,200 --> 01:31:24,280
Speaker 1: there in the corner, but actually is the key to

1703
01:31:24,400 --> 01:31:27,080
Speaker 1: the whole thing. So talking these things out, you know,

1704
01:31:27,240 --> 01:31:30,320
Speaker 1: getting other perspectives on it can help you see the

1705
01:31:30,479 --> 01:31:32,960
Speaker 1: larger pattern within the data sometimes. So that's such a

1706
01:31:33,000 --> 01:31:37,400
Speaker 1: great point. Um, absolutely open mind. Right. We also know

1707
01:31:37,640 --> 01:31:39,960
Speaker 1: that guy, we know that guy knows everything. You're not

1708
01:31:40,000 --> 01:31:42,840
Speaker 1: gonna tell him anything. You've met him, you know, And

1709
01:31:43,680 --> 01:31:47,200
Speaker 1: don't be that guy, you know, don't be the guy

1710
01:31:47,400 --> 01:31:51,080
Speaker 1: that already knows it all, because that's the me I'm

1711
01:31:51,200 --> 01:31:53,800
Speaker 1: learning every day I try to figure something out new.

1712
01:31:54,400 --> 01:31:56,720
Speaker 1: I love that collective thought because you hit the nail

1713
01:31:56,760 --> 01:31:58,800
Speaker 1: on the head man. You never know when somebody's gonna

1714
01:31:58,800 --> 01:32:01,360
Speaker 1: bring something to the party that helps the collective group.

1715
01:32:01,800 --> 01:32:05,439
Speaker 1: Last night, Wade shot the deer, but we all as

1716
01:32:05,479 --> 01:32:08,040
Speaker 1: a group killed the deer. There were a lot of

1717
01:32:08,120 --> 01:32:11,960
Speaker 1: different people that were involved in that moment, and we

1718
01:32:12,080 --> 01:32:16,200
Speaker 1: were all there when we recovered him. And that's every

1719
01:32:16,360 --> 01:32:19,880
Speaker 1: hunt in this camp. It takes a village and one

1720
01:32:19,920 --> 01:32:22,800
Speaker 1: guy shoots it, but the whole village killed it. And

1721
01:32:23,160 --> 01:32:25,760
Speaker 1: and and that's why it's so important to enjoy the

1722
01:32:25,880 --> 01:32:29,040
Speaker 1: process going through it as you lead into the hunt,

1723
01:32:29,360 --> 01:32:32,080
Speaker 1: and then after the hunt enjoy it together. That's what

1724
01:32:32,200 --> 01:32:34,800
Speaker 1: makes this sport so cool. You get emotions and and

1725
01:32:34,960 --> 01:32:40,000
Speaker 1: this unbelievable range of emotions and gratitude and happiness that

1726
01:32:40,160 --> 01:32:42,400
Speaker 1: I can't find anywhere else in life. I've been looking,

1727
01:32:42,640 --> 01:32:44,600
Speaker 1: but it doesn't exist. It's right out there in the

1728
01:32:44,640 --> 01:32:48,240
Speaker 1: great outdoors. Man. It's so cool. There's some really, really

1729
01:32:48,280 --> 01:32:51,200
Speaker 1: good stuff, that's for sure. I want to tie a

1730
01:32:51,240 --> 01:32:54,599
Speaker 1: bow on this mark with one last question, and feel

1731
01:32:54,640 --> 01:32:56,599
Speaker 1: free to take a second to kind of collect your

1732
01:32:56,640 --> 01:32:58,560
Speaker 1: thoughts on this. But if, but if we had to

1733
01:32:58,680 --> 01:33:05,840
Speaker 1: create right now, Mark Druries three rules to successfully patterning bucks.

1734
01:33:05,920 --> 01:33:10,120
Speaker 1: If you had to have three statements, three things that

1735
01:33:10,240 --> 01:33:12,400
Speaker 1: everyone's got to keep in mind, or that the three

1736
01:33:12,520 --> 01:33:15,040
Speaker 1: rules they have to follow to become as good as

1737
01:33:15,120 --> 01:33:18,679
Speaker 1: you are at patterning bucks, What would those three final

1738
01:33:18,880 --> 01:33:20,719
Speaker 1: things be that we need to keep in our heads

1739
01:33:20,840 --> 01:33:25,920
Speaker 1: this season. First and foremost, keep every single solid picture

1740
01:33:26,720 --> 01:33:31,439
Speaker 1: you can um and then study them often. So pictures

1741
01:33:31,479 --> 01:33:34,920
Speaker 1: are one part of the equation. Make sure that you

1742
01:33:35,080 --> 01:33:38,280
Speaker 1: keep them all and then every single picture you look at,

1743
01:33:38,400 --> 01:33:42,200
Speaker 1: ask why and then figure out why Even that two

1744
01:33:42,280 --> 01:33:44,559
Speaker 1: year old did what he did, and that will help

1745
01:33:44,600 --> 01:33:48,080
Speaker 1: you become better in the future. That's step one. Step two,

1746
01:33:48,680 --> 01:33:51,560
Speaker 1: be a slave to the weather and everything you do

1747
01:33:51,800 --> 01:33:54,360
Speaker 1: deer hunting. And I don't care if it's July one,

1748
01:33:55,080 --> 01:33:58,719
Speaker 1: November one, or February one. Pay attention to the weather,

1749
01:33:59,080 --> 01:34:01,519
Speaker 1: and pay attention to what you're doing, how it affects

1750
01:34:01,680 --> 01:34:04,840
Speaker 1: the deer movement, how it affects your personality, your movement,

1751
01:34:05,320 --> 01:34:08,519
Speaker 1: and be a slave to the weather. Uh. Number three,

1752
01:34:09,160 --> 01:34:12,400
Speaker 1: when it comes to patterning, bucks, start taking really detailed

1753
01:34:12,439 --> 01:34:18,719
Speaker 1: notes about mass crops, about um overall crop rotation, about

1754
01:34:19,360 --> 01:34:22,760
Speaker 1: hunters habits. That's another thing you can pattern, not necessarily

1755
01:34:22,840 --> 01:34:27,080
Speaker 1: the dear, when's your neighbor hunting? Uh? When am I

1756
01:34:27,240 --> 01:34:29,760
Speaker 1: in your hunting? Am I being too patternable for this? Dear?

1757
01:34:30,120 --> 01:34:33,840
Speaker 1: So analyze yourself and your environment and everyone around you

1758
01:34:34,280 --> 01:34:36,479
Speaker 1: as much as you analyze the deer. If you do

1759
01:34:36,640 --> 01:34:40,760
Speaker 1: those three things and then collectively add them all up

1760
01:34:41,240 --> 01:34:44,559
Speaker 1: and try to create plans for the future, you're gonna

1761
01:34:44,560 --> 01:34:46,800
Speaker 1: be a much better deer hunter and and and find

1762
01:34:46,880 --> 01:34:49,880
Speaker 1: some rewards out there that you aren't finding now. Yeah, great,

1763
01:34:50,080 --> 01:34:53,080
Speaker 1: great advice. I love this stuff. This is my favorite

1764
01:34:53,120 --> 01:34:55,960
Speaker 1: thing to talk about. So so thanks for humoring me,

1765
01:34:56,120 --> 01:34:58,280
Speaker 1: Mark and getting on here to talk through these things.

1766
01:34:58,880 --> 01:35:01,080
Speaker 1: And I want to give a one last chance to

1767
01:35:01,400 --> 01:35:05,280
Speaker 1: uh tell folks where they can connect with you, where

1768
01:35:05,360 --> 01:35:06,880
Speaker 1: they can see all the great stuff you guys are

1769
01:35:06,920 --> 01:35:09,360
Speaker 1: putting out. How can they find deer Cast? What do

1770
01:35:09,400 --> 01:35:12,400
Speaker 1: we need to know about all those things? Absolutely deer

1771
01:35:12,439 --> 01:35:14,280
Speaker 1: cast dot com. Best way to get it. We've got

1772
01:35:14,320 --> 01:35:16,679
Speaker 1: a free version. We've got a version that's just prediction,

1773
01:35:16,800 --> 01:35:18,880
Speaker 1: that's either nine or ten dollars. And now if you

1774
01:35:18,960 --> 01:35:20,760
Speaker 1: want your environment a lot of things I've been talking

1775
01:35:20,800 --> 01:35:24,760
Speaker 1: about here today, we've got a version that's that will

1776
01:35:24,800 --> 01:35:27,360
Speaker 1: give you one stake's plat data or unlimited for for

1777
01:35:27,479 --> 01:35:29,800
Speaker 1: seventy nine nine. So we've got a price point for

1778
01:35:29,880 --> 01:35:32,559
Speaker 1: everybody from free up to seventy five bucks. Deer cast

1779
01:35:32,600 --> 01:35:35,280
Speaker 1: dot com that you see everything in there, every social post,

1780
01:35:35,360 --> 01:35:38,679
Speaker 1: every deer that gets killed, every every deer season twenty

1781
01:35:38,720 --> 01:35:41,080
Speaker 1: two are semi live series. You can catch it there

1782
01:35:41,520 --> 01:35:43,600
Speaker 1: or you can catch it on YouTube. Our staff is

1783
01:35:43,640 --> 01:35:46,839
Speaker 1: doing an amazing job bringing the stories out within sometimes

1784
01:35:46,880 --> 01:35:49,960
Speaker 1: within hours of when the deer goes down, or of

1785
01:35:50,080 --> 01:35:53,519
Speaker 1: course Instagram, Facebook, YouTube, where wherever you can find there

1786
01:35:53,600 --> 01:35:56,880
Speaker 1: outdoors we're there and happy to happy to talk to people.

1787
01:35:56,920 --> 01:35:59,360
Speaker 1: We've got a team of people that are that are

1788
01:35:59,400 --> 01:36:02,080
Speaker 1: just the best to the industry. In in my you know,

1789
01:36:02,320 --> 01:36:04,960
Speaker 1: biased opinion, I just think our team is just amazing.

1790
01:36:05,040 --> 01:36:08,760
Speaker 1: We you take what Matt and Taylor and Josh and

1791
01:36:08,920 --> 01:36:12,040
Speaker 1: Carson and all our guys in St. Louis are doing,

1792
01:36:12,120 --> 01:36:14,559
Speaker 1: and Wade and Perry and Forest and Ben, I mean,

1793
01:36:14,880 --> 01:36:17,960
Speaker 1: they are really putting some unbelievable content out there for

1794
01:36:18,080 --> 01:36:20,559
Speaker 1: people right now to and we stay in our lane.

1795
01:36:20,600 --> 01:36:22,639
Speaker 1: We try to. We just stayed in our deer hunting

1796
01:36:22,680 --> 01:36:24,280
Speaker 1: and turkey hunting lane and we try not to get

1797
01:36:24,320 --> 01:36:26,840
Speaker 1: out of that. And you know, we try to love

1798
01:36:26,960 --> 01:36:29,640
Speaker 1: up on people as much as they've loved on us. Yeah. Well,

1799
01:36:29,680 --> 01:36:33,120
Speaker 1: you guys, UH continue to do world class work. I

1800
01:36:33,360 --> 01:36:36,000
Speaker 1: love it. I've loved it for decades. I appreciate you, Mark,

1801
01:36:36,200 --> 01:36:39,800
Speaker 1: and Uh. I personally appreciate you, you know, always being

1802
01:36:39,920 --> 01:36:42,599
Speaker 1: willing to hop on here and chat and to answer

1803
01:36:42,640 --> 01:36:45,200
Speaker 1: my questions and to help sew so many people out.

1804
01:36:45,280 --> 01:36:49,360
Speaker 1: So thank you, thank you, Thank you absolutely. Mark. You're

1805
01:36:49,439 --> 01:36:50,800
Speaker 1: You're not the guy at the bar that I get

1806
01:36:50,840 --> 01:36:52,080
Speaker 1: to see every day. You're that guy I get to

1807
01:36:52,120 --> 01:36:55,320
Speaker 1: talk to once or twice a year, and well, I

1808
01:36:55,479 --> 01:36:58,479
Speaker 1: can't wait to hear some some more stories from me

1809
01:36:58,520 --> 01:37:01,080
Speaker 1: down the road once you close the distance again on

1810
01:37:01,160 --> 01:37:03,040
Speaker 1: that big guy who evaded you the other night, or

1811
01:37:03,160 --> 01:37:04,800
Speaker 1: one of these other guys. So it's a good luck,

1812
01:37:04,880 --> 01:37:07,559
Speaker 1: my friend. I appreciate you, Mark, good luck out there.

1813
01:37:07,600 --> 01:37:12,400
Speaker 1: Be safe and that's a rap. Thank you for listening.

1814
01:37:12,880 --> 01:37:15,280
Speaker 1: I hope you enjoyed that one. I hope that you,

1815
01:37:15,720 --> 01:37:18,040
Speaker 1: just like me, are going to be studying some trail

1816
01:37:18,120 --> 01:37:20,719
Speaker 1: camera photos tonight or maybe looking back on your journal

1817
01:37:20,760 --> 01:37:24,360
Speaker 1: of observations and thinking, m, what is this son of

1818
01:37:24,400 --> 01:37:27,600
Speaker 1: a buck gonna do? I am looking forward to it.

1819
01:37:28,040 --> 01:37:31,840
Speaker 1: I appreciate you, dear. Season is here. This is the

1820
01:37:31,920 --> 01:37:35,240
Speaker 1: good stuff, my friends. I'm having a blast. I hope

1821
01:37:35,280 --> 01:37:39,519
Speaker 1: you are as well. And until next time, stay wired

1822
01:37:40,320 --> 01:37:40,720
Speaker 1: to hunt.