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Speaker 1: The following is a production of Dallas Cowboys dot Com

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Speaker 1: and the Dallas Cowboys Football Club. This he's Talking Cowboys

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Speaker 1: training live from the Dallas Cowboys World Hours at the

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Speaker 1: Star in Chris jot Picture and welcome to Talking Cowboys

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Speaker 1: and arm HECKM. Harrison. This is another edition of our

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Speaker 1: one on one series. And guys, I have someone today

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Speaker 1: that is very heavy duty, all right. Her resume reads

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Speaker 1: like a good book. She has an undergraduate degree in biology,

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Speaker 1: master's degrees at finance and analytics. She is a former

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Speaker 1: investment banker, a come on, I gotta get this right

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Speaker 1: investment are right, financial strategist for Disney, a former ESPN analysts,

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Speaker 1: currently predictive analytics expert at NFL Network. Co host of

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Speaker 1: Fantasy Live Fantasy Now. She is always the smartest person

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Speaker 1: in the room. And let me tell you, she is

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Speaker 1: a commissur, a Fantasy League owner, tears no one other

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Speaker 1: than Miss Cynthia Freeland. Miss Cynthia, how are you you're hired?

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Speaker 1: I'll tell my age we're now hired. We're going to

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Speaker 1: switch it out because that was amazing intro. Thank you

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Speaker 1: very much. I always that's that's so kind. I really

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Speaker 1: appreciate that, Thank you. No whatever. Now I'm telling you,

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Speaker 1: I'm in doing this, getting preparing myself for this. I

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Speaker 1: do what I call extensive research. It's just going on

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Speaker 1: the interweb, right and look at at stuff and trying

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Speaker 1: to find everything that you possibly can. And oh, my god, Cynthia,

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Speaker 1: I mean, how in the heck? I mean, first of all,

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Speaker 1: how did you go from East Lansing to Boston College?

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Speaker 1: In that whole thing, I got questions for you on

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Speaker 1: Matt but then Kellogg School of Business at Northwestern that

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Speaker 1: is amazing. Talk about your academic journey I had. My

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Speaker 1: mom was a school teacher and my dad was an engineer.

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Speaker 1: So growing up in East Lansing, which is a home

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Speaker 1: of Michigan State, I was exposed to college and higher

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Speaker 1: education from a really young age. So I think that

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Speaker 1: really helped. I wanted to quote unquote live in a

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Speaker 1: big city. And I say quote unquote there because when

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Speaker 1: I go back to Boston now after having lived in

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Speaker 1: New York in Los Angeles, I'm like, in Chicago, I'm like,

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Speaker 1: this is kind of a small city. But I wanted

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Speaker 1: to be in a big city that still had some

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Speaker 1: of the things that felt like my favorite parts of

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Speaker 1: Michigan State. So sports, especially football and BC was that nice,

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Speaker 1: smaller school kind of city adjacent with sports that were

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Speaker 1: d one, big time sports, and it was just the

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Speaker 1: vibe was right. You know, it's kind of I can't

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Speaker 1: remember what seventeen year old Cynthia was thinking, but that's

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Speaker 1: you know, that's what that's what the vibe felt like

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Speaker 1: at the time. And then you know, I learned, through

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Speaker 1: experience and taking a lot of like you know, swings

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Speaker 1: and missus and all those different things you learned in

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Speaker 1: your early twenties that I needed to go back and

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Speaker 1: get some pedigree in terms of business and really refine

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Speaker 1: what I knew about, you know, how to think through things,

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Speaker 1: and in doing so that that's where I was lucky

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Speaker 1: enough to get my Kellog education. And then realize also

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Speaker 1: that adding the analytics to it could make me a

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Speaker 1: little bit more multiple and a little bit more able

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Speaker 1: to add value in ways beyond what I thought possible

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Speaker 1: when I was that girl who was seventeen and East Lansing.

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Speaker 1: Right now, let me tell you I have an East

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Speaker 1: Lansing story, right So, I was recruited by Michigan State

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Speaker 1: out of personal no listen you got before you. Let's

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Speaker 1: go my story living finish. So I get off of

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Speaker 1: the plane in East Leston. I want to go to

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Speaker 1: Michigan State because of Matcheck Johnson, big time matcheck Johnson fan. Right.

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Speaker 1: So I'm from Dallas, Texas, so I've never experienced any

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Speaker 1: kind of winter like in Michigan winters. Right. So I

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Speaker 1: get off the plane and East Lansing, and I kid

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Speaker 1: you not, there is a power of snow next to

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Speaker 1: the baggage claim, an area that is the size of

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Speaker 1: the building, taller than the building. I decided right there

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Speaker 1: on the tarmact that I was not going to Michigan State.

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Speaker 1: That was it. I was like, it ain't happening. I

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Speaker 1: don't know anything about a winner like that. Wasn't prepared.

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Speaker 1: I had a like long Jones and the starter jacket.

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Speaker 1: It just didn't work out. Those Michigan winters are crazy. Yeah,

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Speaker 1: that's why I no longer lived there. I prefer the

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Speaker 1: sunny or climate of California because the Michigan winter didn't

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Speaker 1: agree with me very well either. I mean, I did

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Speaker 1: live in other cold climates, but I prefer the heat.

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Speaker 1: I totally under stand. I will say Michigan State is

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Speaker 1: a special place, but it is especially special in the fall,

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Speaker 1: and about February, you're like, we out of here yet,

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Speaker 1: Let's let's get this school year over with. So for

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Speaker 1: sure the fall though, in the fall in Michigan, you

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Speaker 1: know you did miss out. Oh look, I did it.

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Speaker 1: I did I'm sure. And let me let me say

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Speaker 1: this to you before we go and go any further.

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Speaker 1: How are you doing during all of this pandemic? You know?

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Speaker 1: How you holding out? You know the funny part. I

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Speaker 1: read a really good Wall Street Journal article that was

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Speaker 1: about like how our minds work and the wiring of

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Speaker 1: our brain to experience negative and positive emotions, and I

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Speaker 1: feel more connected to other people after having read It's

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Speaker 1: a really good article and I recommend everyone reading it.

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Speaker 1: But ultimately, what I'm realizing is that these are all

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Speaker 1: even if you don't love the the experience of being home,

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Speaker 1: or you're feeling a little less connected than normal, these

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Speaker 1: are really good things. We're going to look back in

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Speaker 1: hopefully not that long of a time, when we're back

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Speaker 1: working with each other, and we're going to really not

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Speaker 1: take for granted any of the things. You know. I

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Speaker 1: live in Los Angeles. My commute stinks, but now I

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Speaker 1: feel like maybe I could make better use of my commute,

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Speaker 1: Maybe I could listen to a different book or meditator,

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Speaker 1: do you know, find something else to make the time feel,

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Speaker 1: you know, not feel wasted or disconnected because it's been

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Speaker 1: hard to be so, you know, I miss my family,

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Speaker 1: and I miss my friends, and I miss I missed

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Speaker 1: working all of those things. But but I'm really I'm

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Speaker 1: really starting to see how we have an opportunity to

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Speaker 1: make this experience very positive, even though there's a lot

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Speaker 1: of negative that's been baked in. Absolutely well, Synthia, let's

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Speaker 1: get right into it. And and I'm I'm one of

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Speaker 1: those people that for a number of years had my

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Speaker 1: doubts about analytics, and and I've I've seen, I see

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Speaker 1: the way that analytics is changing financial markets with quant

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Speaker 1: guys and everyone with analytics, you know, not only with

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Speaker 1: algorithms and artificial intelligence and all of that. And so

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Speaker 1: when it came down to football, the game that I

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Speaker 1: love changing and that conventional wisdom of football of run

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Speaker 1: on first downs, run on second downs, those things have changed.

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Speaker 1: You know. More teams are passing on first down, more

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Speaker 1: teams are passing on second downs, more teams are making

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Speaker 1: more risk, where most of that conventional wisdom would tell

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Speaker 1: you not to make those decisions because most coaches are

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Speaker 1: risk averse. Talk about how analytics has changed the game

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Speaker 1: of football totally. It's only as good as good inputs

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Speaker 1: mean good outputs. You have better inputs, you get better outputs. Right.

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Speaker 1: So the more information we've been gathering, so with the

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Speaker 1: advent of next gen stats and people's appreciation for if

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Speaker 1: I track things like what does this defense, what has

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Speaker 1: this defense seen on first down or on second and

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Speaker 1: seven or ever plus to go, and they see, oh,

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Speaker 1: well they've been anticipating run and we've seen that they've

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Speaker 1: seen seventy percent run, Maybe maybe we should pass. So

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Speaker 1: it gives you a framework to make decisions based on

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Speaker 1: a lot of information, but very quickly. Right, so you've

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Speaker 1: been tracking this thing, you can then use it and

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Speaker 1: you can interpret it. And then a coach who has

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Speaker 1: a lot of institutional knowledge about what their players can do,

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Speaker 1: what the playbook is like, they can then use that

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Speaker 1: kind of framework to help remind the decision. So it's

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Speaker 1: really not about being prescriptive. It's about narrowing down the

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Speaker 1: choices from a lot of good options or a lot

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Speaker 1: of options to maybe three good ones. The coach or

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Speaker 1: a play caller or whomever can make a decision based

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Speaker 1: on like, let's go with the three best ones. And

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Speaker 1: maybe we're wrong, but here are three the three we

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Speaker 1: think are the best. And let's let's create those three

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Speaker 1: choices when we're it's a neutral not the game feeling,

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Speaker 1: and you don't you know, your heart isn't beating and

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Speaker 1: there isn't a mannever they're trying to to attack you, right, like,

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Speaker 1: making it in a neutral situation, and here are three

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Speaker 1: best options. Let's leverage that information during the game and

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Speaker 1: be calm, cool, collected and be able to execute better. Now,

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Speaker 1: probability does not equal certainty at all. Right, So, and

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Speaker 1: so there's so many things that has to be factored

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Speaker 1: into it. And I'll take you back to last year,

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Speaker 1: Week eleven, coach Matt Patricia and I know you're a

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Speaker 1: Lions fan, but coach coach Matt Patricia makes the decision

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Speaker 1: five minutes left in the game to go for a

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Speaker 1: two point conversion down by fourteen, right, and so he goes,

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Speaker 1: I mean, obviously the Cowboys one. But in the postgame interview,

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Speaker 1: come on, So in the postgame interview, everyone's asking him

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Speaker 1: like what is the model? Why did you do that?

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Speaker 1: And he talked about how analytics form his decision making,

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Speaker 1: like how is it that coaches are, like you said,

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Speaker 1: making these decisions on the fly based off of you know,

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Speaker 1: all of those things that you thought with your schemes

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Speaker 1: and studying tendencies and things like that. But guys like

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Speaker 1: you are in analytics are measuring the distance between you know,

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Speaker 1: offensive guards but to their ankle and stuff like that

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Speaker 1: to see if a play has got to be successful.

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Speaker 1: What does all of that mean and how does that

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Speaker 1: equate into football success. It's just like you know, like

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Speaker 1: I said, I'm gonna go back to better better input,

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Speaker 1: better output. If a coach is looking for an edge

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Speaker 1: the game, they can look at things like like you

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Speaker 1: can go for the point, like how many how many

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Speaker 1: more downs do you probably have a left given the score,

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Speaker 1: the time on the clock, and the team you're facing, right,

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Speaker 1: if it's a run heavy team versus a past have

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Speaker 1: you but at the end of the games up by fourteen,

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Speaker 1: so down distance situation right, And you can say what

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Speaker 1: Matt Patricia was saying was that they created a model

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Speaker 1: prior to the game, so not in the middle of

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Speaker 1: the game. But prior to the game that they said, well,

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Speaker 1: the Cowboys, they run the ball, especially if they're up

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Speaker 1: by fourteen, right, and if they're going to keep running

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Speaker 1: the ball, we have to take every opportunity that we

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Speaker 1: have to earn some points because we're not going to

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Speaker 1: get this many more possessions. Plus, if you go for it,

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Speaker 1: if you go for two on the first drive. So

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Speaker 1: Matt Patricia thought they had two drives left, right, so

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Speaker 1: this first drive they score a touchdown, might as well

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Speaker 1: might as well go for two on there, because if

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Speaker 1: you don't get it, then you can go for two

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Speaker 1: on the second one. You're not really losing anything. Whereas

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Speaker 1: if you go for two on the first one and

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Speaker 1: then you have the second one, then you could win

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Speaker 1: the game ultimately. You know, that was the I'm not

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Speaker 1: in his head and I didn't ask him specifically about,

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Speaker 1: but I guess that that's what he was that that's

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Speaker 1: where that's where his model was favoring. You know, the

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Speaker 1: Eagles have a different model the rates the Cowboys do.

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Speaker 1: Everyone has a different thing they are looking at. So

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Speaker 1: the smarter teams the thing that they're looking at. The

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Speaker 1: teams that works out either they're lucky and they pick

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Speaker 1: the right things to look at or whatever, or maybe

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Speaker 1: that probability goes on their side more often, right, Or

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Speaker 1: what I would think is the way that they study

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Speaker 1: and the trends that they study are the ones they're hitting,

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Speaker 1: the higher probability ones as opposed to being more lucky.

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Speaker 1: That would be no guess, okay, now, and knowing that

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Speaker 1: you do a lot of well I say a lot,

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Speaker 1: but you do consulting work for NFL teams that are

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Speaker 1: looking to have more extensive analytics. And thinking about coach

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Speaker 1: Mike McCarthy, coach Mike McCarthy was one of those like

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Speaker 1: conservative coaches that at first denied the effect of analytics. Right,

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Speaker 1: And so that you know, club never talk about Bike Club.

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Speaker 1: They never talk about bike Club, one of my favorite movies. Also, anyway,

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Speaker 1: I want to tell you that, you know, Mike McCarthy,

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Speaker 1: he is out of football for here he has an

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Speaker 1: opportunity to study all of the nuances of analytics and

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Speaker 1: now he swears by it. Right, he's like a new

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Speaker 1: man and he's you know, all with the technology that

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Speaker 1: comes with analytics. When looking at a guy that's coming

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Speaker 1: into a new system, here a new new franchise here

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Speaker 1: with the Dallas Cowboys. How do you believe, in just

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Speaker 1: your experience of doing that consulting work that an analytics

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Speaker 1: is going to help Mike McCarthy here in Dallas. I

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Speaker 1: haven't spoken to Mike McCarthy specifically, but I do know

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Speaker 1: one of my very favorite, maybe the smartest individual analytics

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Speaker 1: mind in the NFL, is a Cowboy. So I will

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Speaker 1: say that y'all have a really good group out there

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Speaker 1: because and I can vouch for that. But the one

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Speaker 1: thing that I think the way to think about it

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Speaker 1: as a fan is probably that think about the different

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Speaker 1: just type of quarterback that Aaron Rodgers is versus Dak Prescott.

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Speaker 1: Think about the type of running back that is Zekiel

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Speaker 1: Elliott versus who which running back? You want to talk

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Speaker 1: about the Packers because like, yeah, right, like when McCarthy

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Speaker 1: was there, not Aaron Jones, I will Aaron Jones Jamal

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Speaker 1: Willins are great, But I'm saying, you know, with Aaron

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Speaker 1: Rodgers with Mike McCarthy, that they weren't known for like

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Speaker 1: the best run game. Right. You have to look at

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Speaker 1: the assets that you have and then you have to

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Speaker 1: you have to deploy those assets to get the biggest

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Speaker 1: return on investment. Right, So these are different assets. So

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Speaker 1: in order to make the best use of this old

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Speaker 1: line which is great, this quarterback which is great, this

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Speaker 1: running back, and then how many wide receivers you have

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Speaker 1: that are awesome I count, right, So ultimately making use

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Speaker 1: of those assets and making sure that as you're facing

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Speaker 1: you know, this is like the first year that the Giants,

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Speaker 1: that the Giants and Cowboys aren't playing each other week

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Speaker 1: one what but like n it was right, like so

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Speaker 1: you have to look to see, Okay, the corners corners

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Speaker 1: are a little young for the Cowboys, probably not a

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Speaker 1: problem against the Giants, so it would golden tape. You know,

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Speaker 1: you've got you got a little bit to worry about it.

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Speaker 1: That might have been a good first game for those corners. Likewise,

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Speaker 1: but the offense versus their versus the Giants evens, you

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Speaker 1: got to look for those mismatches. And it's not just

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Speaker 1: look for them from you know, the regular like Mike

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Speaker 1: McCarthy has watched a front of film. I mean I

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Speaker 1: don't I haven't watched with him, but I can imagine

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Speaker 1: it's thousands of hours, right, And in doing so, he

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Speaker 1: has a good feel for it. If you can model

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Speaker 1: out his brain so that the other people Kellen Moore,

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Speaker 1: like all of the all the offensive pieces of people

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Speaker 1: who people who are helping to call plays or coordinating

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Speaker 1: the passing game or all the different things, they can

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Speaker 1: all be on the same page more quickly. You're just

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Speaker 1: creating a better game plan. And that's how analytics can

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Speaker 1: be most useful is you get everyone on the same page,

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Speaker 1: so we're all rowan in the same direction, right, and

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Speaker 1: then you have the best opportunity to take your opponent

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Speaker 1: and find their weaknesses and exploit them so that your

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Speaker 1: assets return the biggest for you, meaning win as many

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Speaker 1: games as possible. Absolutely. Now you see those I guess

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Speaker 1: one off and I said this, you know, based off

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Speaker 1: of you know, looking at a team like the Ravens

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Speaker 1: and the forty nine ers, who have really really good

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Speaker 1: analytics departments. The Ravens were a shoeing on fourth downs

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Speaker 1: during the season eight and eight, so obviously we know

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Speaker 1: what the percentage is on that. Then they go into

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Speaker 1: a game versus the Titans and they go forward twice

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Speaker 1: and conventional wisdom and analytics tells them, because of this

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Speaker 1: previous success, that this may work versus a team like

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Speaker 1: the Titans. The Titans, on the other hand, first down,

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Speaker 1: run the ball, second down, run the ball, Third down,

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Speaker 1: run the ball. This is the conventional side of old

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Speaker 1: school football, the three yards in a cloud of dust

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Speaker 1: style that we had before. How does that? How do

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Speaker 1: you take that? And you say, look, analytics helps you

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Speaker 1: in this situation, but may not help you in a

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Speaker 1: winner takes all elimination game. I argue that that's where

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Speaker 1: you have to do. Like, think of the world as

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Speaker 1: a decision tree. Right, it shouldn't be binary, right, Like

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Speaker 1: binary means either yes or no. There's only two options, right,

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Speaker 1: The world isn't binary. So sure, maybe maybe your fifty

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Speaker 1: percent going forward on fourth down during the season, But

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Speaker 1: let's add some context. Were those zone or man defenses

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Speaker 1: you faced? Where were you on the field? What was

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Speaker 1: the time left on the clock? What was the score?

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Speaker 1: What are all of the different important inputs? Was their

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Speaker 1: number one defensive end hurt or not playing? You know who?

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Speaker 1: Who were these people you were playing against? Right? And

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Speaker 1: what play did you call to achieve that? So you

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Speaker 1: have to also be able to adapt to what you see.

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Speaker 1: So it's this decision tree. Maybe they obviously they thought

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Speaker 1: it was going to work if they kept doing it,

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Speaker 1: but not for the sake of the pure volume. Right.

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Speaker 1: They probably had seven plays, eight plays that they had

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Speaker 1: ready for those specific situations, but honestly, the Titans defense

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Speaker 1: had them scout it, right, So that's what happens. But

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Speaker 1: that's the chess match we all want to watch, right,

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Speaker 1: our best versus my best. Let's lock horns at the post.

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Speaker 1: You know you don't, it's not It's not always fun

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Speaker 1: when it's like, you know, a super lop sided score.

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Speaker 1: I was at a Rams Ravens game that got real

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Speaker 1: boring after about you know, three drives, right, So I'll

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Speaker 1: tell you what I'm gonna have to use that life

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Speaker 1: is a decision tree for my thirteen year old. Okay,

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Speaker 1: I got steal that with So this, I've you know,

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Speaker 1: done my research, like I said, And you had some

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Speaker 1: really outstanding things to say about our number one draft

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Speaker 1: pick and Cede Lamb. And it's just based off of

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Speaker 1: your numbers that you saw for him. And now now

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Speaker 1: obviously as a Cowboys fan, we are all sighted about

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Speaker 1: Cede Lamb, but your number is kind of took him

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Speaker 1: to a whole another level. Just talk about what you

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Speaker 1: see from Cede Lamb from a numbers perspective, usually you

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Speaker 1: don't see so much talent that fits so well, do

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Speaker 1: you know what I'm saying, Like, like, you've got the

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Speaker 1: space that Amri Cooper occupies, the space meaning the routes,

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Speaker 1: the routes that he runs, and the and the presence

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Speaker 1: from a defense that he commands. Same and by the way,

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Speaker 1: he's like twelve, he's super young. Still like he's a

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Speaker 1: college very young too, so that's a that's a positive.

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Speaker 1: And then he got Michael Gallup also very young, and

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Speaker 1: the space that he occupies and the defense command that

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Speaker 1: he requires, right, and then you've got ce Lamb is like, hey, um,

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Speaker 1: Slot High, run away with you. So ultimately, the any

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Speaker 1: any rookie, it's hard to project their use because just

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Speaker 1: like any college graduate, you have kids in college, they

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Speaker 1: gotta go get a job. Their resume. It's just maybe

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Speaker 1: maybe they've had a few summer jobs, internship. Maybe they

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Speaker 1: we're a biology major, so they have a little more.

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Speaker 1: You have only the resume you have, and if you've

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Speaker 1: run those routes that compliment what the other guys are doing,

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Speaker 1: right as well as Ceedee Lamb compliments what Michael Gallup

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Speaker 1: and Amari Cooper have been able to do. I mean,

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Speaker 1: that's a nicer fit because you don't have to then

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Speaker 1: your learning curve. It's really based on your resume and

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Speaker 1: less based on a whole new route tree, because you're

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Speaker 1: gonna have to learn the playbook. You're gonna have to

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Speaker 1: learn the speed. You're gonna have to get the touch

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Speaker 1: with Dak Prescott. By the way, I don't know how

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Speaker 1: much they've been working together because COVID's very tricky, right,

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Speaker 1: So you might as well put yourself in a situation

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Speaker 1: where at least your muscles know how to run that route,

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Speaker 1: you know. And by the way, Amari Cooper, Michael gall

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Speaker 1: go let me open, right guys. So so that's the

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Speaker 1: kind of that's the kind of thing where the more

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Speaker 1: you have fit and reps that are meaningful that already

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Speaker 1: match easier transition. Well that that I love when you

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Speaker 1: talk data to me, Cynthia, and I hope that it

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Speaker 1: works out exactly the way that your numbers have estivated

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Speaker 1: for our for our rookie receiver. Now, look, wanting to

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Speaker 1: pull this back a little bit and talk about something

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Speaker 1: that I think is very unique to your situation. And

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Speaker 1: that is the fact that you are the only female

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Speaker 1: analysts on a Sunday morning talk show only and Synthia

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Speaker 1: being a girl dad like I am, and warning the

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Speaker 1: best for my girls and every environment. Talk about what

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Speaker 1: it means to be so groundbreaking the way that you

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Speaker 1: are and breaking into these industries the way that you have.

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Speaker 1: Feel very fortunate to have been given an opportunity to

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Speaker 1: talk to have an analyst role talking about numbers. These

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Speaker 1: are sometimes boring things. People don't always love math. And

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Speaker 1: being able to be supported by men and women in

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Speaker 1: front of and behind the camera that allow me to

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Speaker 1: to do that, that is that means everything to me,

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Speaker 1: and I'm very grateful for that. I'm super grateful to

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Speaker 1: see things like ESPN just announced that Mina Kimes is

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Speaker 1: now an analyst full time for NFL Live, which is

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Speaker 1: amazing and I love that. So I love seeing these

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Speaker 1: people whose voices I respect and I learned from being

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Speaker 1: able to be like you know, you're not just like

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Speaker 1: a you know, you're not just like a weather girl

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Speaker 1: right like you know you want to be. You get

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Speaker 1: a chance to have an opinion, and you have to

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Speaker 1: earn your You earn your stripes every week you know,

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Speaker 1: every every time. So I feel very fortunate that I've

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Speaker 1: had the support of the men and the women in

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Speaker 1: front of and behind the camera in order to be

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Speaker 1: able to even be considered for it. So I it means,

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Speaker 1: it means everything to me that that is is completely awesome.

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Speaker 1: Now we're at the part of the show that I

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Speaker 1: really enjoy and these are the rapid fire questions that

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Speaker 1: I had it all right, So yeah yourself, just know

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Speaker 1: that this may you know, send your smoke detectives off

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Speaker 1: because I'm gonna serve these like anti cornicoke, all right?

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Speaker 1: Get ready? All right, so Mexican food or Italian food.

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Speaker 1: I'm Italian Italian food. I eat more Mexican food. But

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Speaker 1: if I'm gonna say, like my grandma known as lasagna

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Speaker 1: every day, yes I would be three hundred pounds, but yes,

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Speaker 1: Italian food, all right. A beach or skis Okay, I'm

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Speaker 1: from Michigan, so I didn't know which one you bay,

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Speaker 1: I'm with you, all right, not for me. Now, I

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Speaker 1: know that you are a fitness nut, right, so I've

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Speaker 1: heard this. I'm right well different and I mean, is

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Speaker 1: it true that you've ran a marathon in every state? State?

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Speaker 1: So I'm trying to go to every state. I'm at

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Speaker 1: twenty three, I'm at my Jordan. I just did my Jordan.

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Speaker 1: But they're all this year, so I'm not gonna be

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Speaker 1: able to get They're not running any marathons this year,

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Speaker 1: so or the ones that I would be able to do,

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Speaker 1: So maybe next year I'll have to do a few. Well,

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Speaker 1: So choose between these two, the New York Marathon of

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Speaker 1: the Boston Marathon. I haven't done Boston yet, but I

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Speaker 1: went to BC so I had a lot of fun

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Speaker 1: watching it. New York Marathon holds a very special place

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Speaker 1: in my heart, though, so I'm going to go with

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Speaker 1: New York for now, but I'll probably like Boston once

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Speaker 1: I run it. Now, tell me, what are your thoughts

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Speaker 1: when I say this name Anthony? No though, Oh my

430
00:24:45,840 --> 00:24:49,560
Speaker 1: most important mentor super grateful, super grateful for everything he's

431
00:24:49,560 --> 00:24:53,520
Speaker 1: taught me. That is awesome. That's it. In the fire,

432
00:24:54,160 --> 00:24:56,160
Speaker 1: the alarms didn't go off, but you made it through

433
00:24:56,200 --> 00:24:58,679
Speaker 1: with Cynthia, I made it. I made it. Thank you,

434
00:24:58,840 --> 00:25:03,199
Speaker 1: good look, thank you so much for joining me on

435
00:25:03,400 --> 00:25:07,680
Speaker 1: Talking Cowboys. I really appreciated Cynthia. This was this was awesome.

436
00:25:08,240 --> 00:25:11,800
Speaker 1: Did she Cynthia Freeman. She has a ninety four percent

437
00:25:11,960 --> 00:25:15,280
Speaker 1: win streak and draft king stuff you wanna win. Yeah,

438
00:25:15,400 --> 00:25:19,920
Speaker 1: battle follow Cynthia Freeland. I put it out there, I'll

439
00:25:19,960 --> 00:25:21,879
Speaker 1: put it out there, but thank you so much. I

440
00:25:21,920 --> 00:25:24,840
Speaker 1: really appreciate it, and thank all of you guys for

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00:25:24,920 --> 00:25:27,720
Speaker 1: joining us here on Talking Cowboys. We'll see you