WEBVTT - Episode 60: Fitting Science (Feat. Chris Broadie) 0:00:00.360 --> 0:00:02.360 The guys from Ping. They've kind of showed me how 0:00:02.440 --> 0:00:03.840 much the equipment matters. 0:00:04.120 --> 0:00:05.960 I just love that I can hit any shot I 0:00:06.040 --> 0:00:06.560 kind of want. 0:00:06.680 --> 0:00:08.479 We're gonna be able to tell some fun stories about 0:00:08.480 --> 0:00:10.639 what goes on here to help golfers play better golf. 0:00:11.000 --> 0:00:13.560 Hey, everybody, welcome back to the Pink Proven Grounds Podcast. 0:00:13.560 --> 0:00:16.480 I'm Shane Bacon, joined us always by Marty Jerts and Marty. 0:00:16.520 --> 0:00:19.000 We are diving deep with a man that I know 0:00:19.440 --> 0:00:20.840 you work closely with this week. 0:00:21.400 --> 0:00:26.200 Yeah, we got Chris Brody here. Brody, as he goes 0:00:26.239 --> 0:00:29.200 by amongst our engineering group and our R and D group, 0:00:30.360 --> 0:00:34.479 has a background in mathematics and is the sun of 0:00:35.080 --> 0:00:38.479 one very famous statistician in the golf industry. So Brody, 0:00:38.560 --> 0:00:39.600 welcome to the pod man. 0:00:40.320 --> 0:00:41.559 Thanks for having me, Marian. 0:00:41.400 --> 0:00:45.720 Shane, Chris, what's like dinner talk like with Pops when 0:00:45.720 --> 0:00:48.000 you guys are just discussing golf? Can you have normal 0:00:48.040 --> 0:00:51.440 golf conversations or does it always lend down some avenue 0:00:51.479 --> 0:00:53.960 of analytics and like what's going on? 0:00:54.800 --> 0:00:57.240 Yeah? I feel like it gets pretty deep. There's been 0:00:57.240 --> 0:01:00.840 a lot of recent work he's done on world golf rankings, 0:01:00.880 --> 0:01:04.720 college golf rankings. So he's he's trying to figure it 0:01:04.760 --> 0:01:08.080 out and hopefully not get too much abuse from from 0:01:08.080 --> 0:01:12.119 PJ Tour pros. So it's it's it's fun to hear 0:01:12.240 --> 0:01:15.880 what's going on in his in his world of golf rankings. 0:01:15.640 --> 0:01:17.840 Brody before your dad got into the what he's kind 0:01:17.840 --> 0:01:20.280 of working on now, which is the world world golf rankings, 0:01:20.280 --> 0:01:23.520 the college side of things. Obviously, he he, you know, 0:01:23.600 --> 0:01:26.880 wrote the book Every Shot Counts, a kind of you know, 0:01:27.400 --> 0:01:30.119 golf's version of Moneyball is is I think the best 0:01:30.160 --> 0:01:34.119 analogy therefore, tell us about your kind of childhood and 0:01:34.160 --> 0:01:37.039 in some early days of you know, some of the 0:01:37.080 --> 0:01:39.480 work and background he was doing in the golf space. 0:01:39.520 --> 0:01:42.279 How did how did he get interested or involved in golf? 0:01:42.319 --> 0:01:45.840 And how did you you know, you and your brother, 0:01:45.959 --> 0:01:48.160 your family members there contribute to that. 0:01:48.560 --> 0:01:50.880 Yeah, I know, it's been it's been very fun to 0:01:50.920 --> 0:01:55.120 see the progression of early days of interest to writing 0:01:55.120 --> 0:01:58.920 a book getting adopted by PJ Tour. I think interestingly, 0:01:59.000 --> 0:02:02.760 for me, there's always been like golf and math floating 0:02:02.800 --> 0:02:05.760 around in the background. But for me, it start a 0:02:05.760 --> 0:02:08.679 lot with baseball. I remember playing Little League as like 0:02:08.720 --> 0:02:12.639 a seven eight year old and probably classically. My dad 0:02:12.639 --> 0:02:16.600 would start to record, not just like your typical like 0:02:16.880 --> 0:02:18.959 walk singles, but you record like where the ball was 0:02:19.040 --> 0:02:22.240 hit to what each player on the team was doing. 0:02:22.320 --> 0:02:24.560 So he started asking me, okay, like if you were 0:02:24.560 --> 0:02:26.600 to manage this team, like what would you do? How 0:02:26.600 --> 0:02:31.360 would you set the lineup for our little league baseball team? 0:02:31.840 --> 0:02:34.600 And he's like, one of the first questions like, okay, 0:02:34.639 --> 0:02:36.959 how many how many different combinations of lineups are there? 0:02:37.480 --> 0:02:39.320 And it's okay, So the first batter you can put 0:02:39.360 --> 0:02:41.799 there's nine different people who can choose from second bat 0:02:41.919 --> 0:02:43.840 is eight different people, and so you'd be okay. So 0:02:43.840 --> 0:02:46.079 the number of combinations you can think through is nine 0:02:46.120 --> 0:02:48.840 times eight times seven times six. And I was like this, 0:02:49.000 --> 0:02:50.679 this is kind of this kind of getting into like 0:02:50.720 --> 0:02:52.640 what the dinner dinner time my seven year old dinner 0:02:52.639 --> 0:02:53.360 time conversation. 0:02:54.160 --> 0:02:56.080 You're like, I just want to play baseball, man, you're 0:02:56.120 --> 0:02:56.960 talking about. 0:02:56.800 --> 0:02:58.200 I loved it. It was like, okay, I think you might 0:02:58.240 --> 0:03:00.200 have set up like a custom simulation for me of 0:03:00.240 --> 0:03:02.280 like all right, we can put this player here, see 0:03:02.280 --> 0:03:04.840 a expected runs there are? And he was like, quickly, 0:03:04.880 --> 0:03:06.960 very quickly, you learn that, like you want to have 0:03:07.080 --> 0:03:09.440 your best player up first. It's like at the most 0:03:09.480 --> 0:03:12.880 possible at bats. And that was like very early like Moneyball, 0:03:12.960 --> 0:03:15.720 like same same conclusion. You want to have your highest 0:03:15.760 --> 0:03:20.280 on base sentage hitter going off first. Similarly, like we 0:03:20.280 --> 0:03:21.720 looked at like where the hits were in the field, 0:03:21.760 --> 0:03:25.280 and like, no little leaguer can keep up with a fastball, 0:03:25.320 --> 0:03:26.639 so they all hit it to the right side. So 0:03:26.680 --> 0:03:30.320 you put your best defensive guy at second base. Interesting, 0:03:30.880 --> 0:03:35.880 so the Nuggets were rolling in pretty quick. Another one 0:03:36.000 --> 0:03:38.040 we're going we're going probably too deep into baseball. But 0:03:38.080 --> 0:03:40.480 another one was he asked me, like, what what percent 0:03:40.520 --> 0:03:43.600 of time do you need to successfully steal second in 0:03:43.720 --> 0:03:46.600 order to make it worth it? So guy on first, 0:03:46.680 --> 0:03:49.040 no Out's like, when should you give the guy green 0:03:49.080 --> 0:03:52.360 light to steal? And I guess my first like initial 0:03:52.400 --> 0:03:54.800 thought is, okay, well what's the average success rate? Like 0:03:54.800 --> 0:03:58.360 if you can get over seven percent, then go ahead, 0:03:58.560 --> 0:04:00.280 And he's like no, no, there's like there's a better 0:04:00.320 --> 0:04:03.520 way of think through it, and so we end up 0:04:03.520 --> 0:04:05.480 breaking it down. It's okay, with a man on first, 0:04:05.920 --> 0:04:10.640 no outs, your expected runs is maybe point eight, but 0:04:10.720 --> 0:04:12.480 if you get that guy a second, it jumps up 0:04:12.480 --> 0:04:14.880 to one point zero. Now a single might score him, 0:04:15.200 --> 0:04:17.040 but then if he gets out, now you have nobody 0:04:17.080 --> 0:04:19.159 on and one out and you're down to like point 0:04:19.200 --> 0:04:21.440 two runs. And so say, okay, you just gotta look 0:04:21.440 --> 0:04:23.720 at the trade off of going point eight to one 0:04:23.760 --> 0:04:26.120 point zero or point eight down to point two, and 0:04:26.600 --> 0:04:29.240 to make it worthwhile steal you've got to have an 0:04:29.240 --> 0:04:32.120 over seventy five percent success rate. And it's like, oh, 0:04:32.120 --> 0:04:33.920 that's that's that's the pretty unid insight. And you can 0:04:33.960 --> 0:04:36.080 do that for what happens if this guy in first 0:04:36.200 --> 0:04:38.000 two outs and they can do the math again, it's like, okay, 0:04:38.000 --> 0:04:41.160 if it's zero point two with two outs and guy 0:04:41.160 --> 0:04:43.160 on first, make it cessful and a guy guy in 0:04:43.400 --> 0:04:46.000 scorem position, you have too point four. But then if 0:04:46.040 --> 0:04:49.680 you if you're unsuccessful, the aning's over and down to zero. 0:04:50.160 --> 0:04:52.000 But interesting thing there is, if it's point two verse 0:04:52.080 --> 0:04:54.320 point four, all you need is a figure sent success 0:04:54.400 --> 0:04:56.719 rate to make it worthwhile. And so it's like, okay, 0:04:56.720 --> 0:04:58.920 the incentive then is to send a lot of guys 0:04:58.920 --> 0:05:02.160 to try to steal second with two outs, think on first. 0:05:03.920 --> 0:05:05.560 So a lot of things end up like correlating well 0:05:05.560 --> 0:05:07.119 with golf, Like you don't want to just look at 0:05:07.520 --> 0:05:11.039 raw stolen base percentage, Like the metric that matters for 0:05:11.120 --> 0:05:12.239 baseball is run scored. 0:05:12.480 --> 0:05:12.760 Yeah. 0:05:12.920 --> 0:05:15.120 I think that translated over pretty quickly towards golf, Like 0:05:15.560 --> 0:05:17.359 you don't really want to care about what your farely 0:05:17.440 --> 0:05:20.200 hit percentage is, what your green hit percentage is. What 0:05:20.360 --> 0:05:22.640 really matters at the end of the day is how 0:05:22.640 --> 0:05:24.080 many shots that take you to get into the hole. 0:05:24.480 --> 0:05:25.800 And so you can hit a good drive that doesn't 0:05:25.839 --> 0:05:27.560 hit the fair way, but if it's three hundred and 0:05:27.560 --> 0:05:29.200 thirty yards down there, you might be in a pretty 0:05:29.200 --> 0:05:29.680 good spot. 0:05:29.880 --> 0:05:32.159 Marty. It's interesting, you know, as Chris talks about this, 0:05:32.400 --> 0:05:34.880 I think about in my life and we're similar raised 0:05:34.880 --> 0:05:37.720 to Marty, but in my life, like the real switch 0:05:37.960 --> 0:05:41.320 for analytics and golf to me personally, was the switch 0:05:41.400 --> 0:05:44.119 from how we play par fives. Yes, and I feel 0:05:44.120 --> 0:05:46.400 like it was probably fifteen twenty years ago, Matt. Maybe 0:05:46.400 --> 0:05:48.839 now was twenty five years ago, where the idea was 0:05:48.880 --> 0:05:51.159 layup to enough you can't get there into lay up 0:05:51.200 --> 0:05:52.760 to a number you're comfortable with. And you know, for 0:05:52.800 --> 0:05:54.719 me it was always ninety five to one hundred yards. 0:05:54.720 --> 0:05:56.760 I've lay up to that number or tried to and 0:05:56.800 --> 0:05:58.800 that gave you the best chance of making birdie. And 0:05:58.839 --> 0:06:00.600 then there was a flip I feel like in the 0:06:00.640 --> 0:06:03.800 early two thousands where numbers and data started to tell 0:06:03.880 --> 0:06:05.720 us no, no, no, no, no, send it as far up as 0:06:05.720 --> 0:06:07.920 you can ye with both both golf shots, because it's 0:06:07.920 --> 0:06:09.719 obviously the easiest place to get up and down make birdie. 0:06:09.960 --> 0:06:12.680 Yeah, when when Brody was talking about the baseball in 0:06:13.000 --> 0:06:15.400 his work his dad was doing on the baseball side, 0:06:15.120 --> 0:06:18.320 my brain was on, okay, instead of should I steal second? 0:06:18.360 --> 0:06:20.599 Should I go for the par five and two? Yeah? 0:06:20.600 --> 0:06:23.000 That was exactly Yeah, that was exactly where my head 0:06:23.040 --> 0:06:27.280 was at. So yeah, that's it's super cool Brody to 0:06:27.320 --> 0:06:30.280 hear those those early days of like your dad thinking 0:06:30.279 --> 0:06:32.960 about the probabilities. I mean, one of the other questions 0:06:33.000 --> 0:06:36.919 I always thought of Shane when I was in school 0:06:37.000 --> 0:06:40.960 for the listeners out there is is Brodie's background is 0:06:41.080 --> 0:06:43.680 in mathematics. His degrees in math, and I'm always like, 0:06:43.720 --> 0:06:47.279 what does a math major even do? So I think 0:06:47.320 --> 0:06:50.560 Brodie's a real life example here, Chris, tell us a 0:06:50.600 --> 0:06:53.279 little bit why you went that direction and some of 0:06:53.279 --> 0:06:55.760 the work you do, you know, like day to day, 0:06:55.839 --> 0:06:58.919 like what does a math major do in the working world. 0:06:59.680 --> 0:07:03.080 Yeah, definitely didn't have much of a clue what I 0:07:03.120 --> 0:07:04.680 was gonna do. When I was in college. I was like, 0:07:04.880 --> 0:07:07.839 I know, I've always liked math. I've always enjoyed having 0:07:07.920 --> 0:07:13.120 these how can I apply data to different problems? And 0:07:14.120 --> 0:07:15.440 it was more it was more just like, Okay, I 0:07:15.440 --> 0:07:17.120 think if I do a math major, I'm gonna have 0:07:18.400 --> 0:07:21.440 some open something's gonna work out, like it might be consulting, 0:07:21.480 --> 0:07:24.960 it might be econ, but I'll keep my options open. 0:07:26.080 --> 0:07:30.680 And I definitely gravitated towards like applied math problems, probably 0:07:30.680 --> 0:07:33.880 stunning from when I was seven years old, and so 0:07:35.200 --> 0:07:37.480 it worked out pretty well with I think at the 0:07:37.560 --> 0:07:39.120 end of my college career, we're doing a lot of 0:07:39.160 --> 0:07:41.560 theoreical math. I was like, this is not quite clicking 0:07:41.600 --> 0:07:43.920 for me. I was very lucky to get to paying 0:07:43.960 --> 0:07:45.400 and they're like, oh, we got a whole lot of 0:07:45.480 --> 0:07:47.360 data and a whole lot of problems we want you 0:07:47.360 --> 0:07:50.360 to look at. And it was really fun, just like 0:07:50.480 --> 0:07:54.320 dive into a world of golf and math and continue 0:07:54.320 --> 0:07:57.200 with a lot of my growing up interests. 0:07:57.440 --> 0:07:59.680 Chris, can you give us an example of something once 0:07:59.720 --> 0:08:02.040 you came to Paying because your job at Paying fitting 0:08:02.080 --> 0:08:05.360 science manager, what like giving us an example of something 0:08:05.680 --> 0:08:08.680 somebody might come to you with a problem to find 0:08:08.720 --> 0:08:11.920 a solution, like anything that's popped up throughout your career pain. 0:08:12.480 --> 0:08:16.000 Yeah, I mean there's been a lot of really fun 0:08:16.160 --> 0:08:22.760 different ones. One of the more fun ones was Travis Milman, 0:08:22.840 --> 0:08:26.080 one of our design engineers, was working on our G 0:08:26.120 --> 0:08:29.200 four to thirty Farawood line and he's like, hey, we 0:08:29.280 --> 0:08:31.720 have ten grams of discretionary mass. It's just kind of 0:08:31.760 --> 0:08:36.360 the gold currency for designers. And he was like, should 0:08:36.440 --> 0:08:39.800 we just keep on pushing MI we can probably get 0:08:39.840 --> 0:08:43.280 like a five to ten percent boost this Ferrywood or 0:08:43.360 --> 0:08:45.439 I can move around the mass, I can try to 0:08:45.480 --> 0:08:47.480 drop the CG location. And we kind of had a 0:08:47.520 --> 0:08:49.480 hunch that maybe, like if we canet a little bit 0:08:49.520 --> 0:08:52.319 higher launched, lower spin out of our out of our farrewoods, 0:08:52.360 --> 0:08:56.320 like it could be a pretty nice gain in terms 0:08:56.360 --> 0:09:00.360 of strokes gain in terms of performance. But it's a 0:09:00.360 --> 0:09:03.080 hard one from a design side, like he's not really 0:09:03.120 --> 0:09:05.600 sure how to tell that story, like what exactly do 0:09:05.640 --> 0:09:09.360 you gain from higher launch and lower spin? And so 0:09:10.320 --> 0:09:13.200 I was able to use some of my simulation background, 0:09:13.880 --> 0:09:17.320 use our vocal data where we know help people deliver 0:09:17.400 --> 0:09:20.240 fairy woods, and basically run a virtual test that Okay, 0:09:20.280 --> 0:09:23.160 if we use your default G four twenty five head 0:09:23.200 --> 0:09:26.360 shape with these mass properties versus a four point thirty 0:09:26.400 --> 0:09:29.680 with maybe your higher MLI pathway versus four thirty with 0:09:29.679 --> 0:09:32.280 your lower CG pathway, or the trade offs that you 0:09:32.280 --> 0:09:35.480 can see in terms of performance and kind of all 0:09:35.520 --> 0:09:38.280 the things that matter not just can your longest shot 0:09:38.320 --> 0:09:40.760 go further, but what happens on your full range of 0:09:40.800 --> 0:09:44.800 impacts and mishits. And that's where looking at through a 0:09:44.840 --> 0:09:47.480 stroke scand lens kind of helps you blend those things together. 0:09:47.520 --> 0:09:49.720 It's not just seeing the ball as far as possible 0:09:49.720 --> 0:09:53.120 every time, but it's getting that right blend of distance 0:09:53.160 --> 0:09:55.559 and accuracy. And so that was a fun one where 0:09:55.559 --> 0:09:58.200 I could tell him like, hey, this is unconventional, but 0:09:58.280 --> 0:10:00.640 you can drop the MI by a decent amount. But 0:10:01.320 --> 0:10:03.840 on that Elsie Farrowood, if you can lower your CG 0:10:03.960 --> 0:10:06.720 location by point one point two inches, you'll see a 0:10:06.720 --> 0:10:08.800 pretty big boost and performance. 0:10:09.240 --> 0:10:12.160 Yeah. Shane Brody's been a big part of the ability, 0:10:12.360 --> 0:10:15.640 as he talked about of connecting the dots on our 0:10:15.760 --> 0:10:19.360 modeling capabilities. So, like you know, ping, we've gone through 0:10:19.360 --> 0:10:22.080 this revolution where we used to always do like tons 0:10:22.120 --> 0:10:26.520 of robot tests, but those have their limitations because while 0:10:26.559 --> 0:10:29.080 sometimes you want to deliver the club perfectly the same 0:10:29.160 --> 0:10:31.800 every time, it's not what humans do. So then we 0:10:31.840 --> 0:10:33.920 have FOCAL. We spend some time in FOCAL. We talked 0:10:33.960 --> 0:10:37.080 to doctor Eric hendrickson on how that works. Chris is 0:10:37.120 --> 0:10:41.280 on the end of marrying those things together, running all 0:10:41.320 --> 0:10:45.920 these what if scenarios, these virtual simulations, so it saves 0:10:46.000 --> 0:10:48.640 us a lot of time and it helps us answer 0:10:48.760 --> 0:10:52.960 questions with a lot more clarity more quickly because we 0:10:53.000 --> 0:10:55.880 can run these things virtually, and then we can kind 0:10:55.880 --> 0:10:59.120 of validate a hypothesis. Then we make the physical prototypes, 0:10:59.360 --> 0:11:03.120 test them through our full suite of robot and human testing. 0:11:03.160 --> 0:11:05.600 So been able to fast track. So a lot of 0:11:05.640 --> 0:11:08.400 fun Chris working on that. Marty. 0:11:08.400 --> 0:11:10.320 I got a question for you, Marty in this, In 0:11:10.360 --> 0:11:12.920 this because I'm interested in this because Chris's point about 0:11:12.920 --> 0:11:15.400 bringing an idea to him and having to figure it out. Marty, 0:11:15.440 --> 0:11:17.360 I know you've been big in terms of you know, 0:11:17.440 --> 0:11:19.880 conceptualizing golf clubs and building golf clubs over the last 0:11:19.880 --> 0:11:23.480 couple decades at Ping, how many departments are you running 0:11:23.480 --> 0:11:25.679 things by when you're coming up with a new driver? 0:11:25.840 --> 0:11:28.880 I mean, are there ten departments you're going to and 0:11:28.920 --> 0:11:31.200 you're saying, you help us with this, you help us 0:11:31.240 --> 0:11:33.280 with this, because I don't think people at home think 0:11:33.280 --> 0:11:36.120 about building a golf club and they're thinking Ping's trying 0:11:36.120 --> 0:11:38.120 to make a golf club that goes as long as possible, right, 0:11:38.240 --> 0:11:40.520 or it goes as straight as possible. But obviously there's 0:11:40.600 --> 0:11:43.720 fifty one hundred and two hundred two thousand factors that 0:11:43.840 --> 0:11:46.640 go into a driver. So like, how many departments are 0:11:46.640 --> 0:11:48.840 you leaning on, Marty as you're coming up with the 0:11:48.880 --> 0:11:50.240 new age, the new Ping driver. 0:11:50.800 --> 0:11:53.480 Yeah, yeah, that's a great question, Shane. Like to get 0:11:54.040 --> 0:11:57.400 a driver to the market, it's very super cross functional, 0:11:57.520 --> 0:12:00.839 all right. So it's it's the designing it three D CAD, 0:12:00.960 --> 0:12:05.800 the joints, the mechanical design optimization. Then you're working with 0:12:05.920 --> 0:12:09.480 an innovation group and they're working on maybe materials like 0:12:09.520 --> 0:12:12.280 our carbon fly wrap and things of that nature and 0:12:12.480 --> 0:12:15.439 optimizing those kind of those are they're kind of baking 0:12:15.440 --> 0:12:17.480 them in the R and D world, right and getting 0:12:17.520 --> 0:12:20.040 them ready to be integrated to the design. Then you're 0:12:20.040 --> 0:12:25.040 working with kind of supply chain, manufacturing, sourcing, materials, components, 0:12:25.360 --> 0:12:29.120 project engineering, which is kind of all the detailed nitty 0:12:29.120 --> 0:12:31.080 gritty to kind of ramp it up and scale the 0:12:31.120 --> 0:12:34.559 manufacturing quality control to make sure we're bringing it for 0:12:34.679 --> 0:12:38.320 designing a new manufacturing process, we can make it consistently 0:12:38.679 --> 0:12:42.839 to meet our brand standards. Our testing group which make 0:12:42.880 --> 0:12:46.000 sure it's not going to break, it's durable. We validated 0:12:46.040 --> 0:12:49.440 the performance that we want. You know, we got you know, 0:12:49.800 --> 0:12:52.920 a USGA liaison in here. We got my team now, 0:12:52.960 --> 0:12:55.800 which is the fitting and performance group, which make sure 0:12:55.960 --> 0:12:58.079 we're getting the right launch conditions. You know. Then you 0:12:58.160 --> 0:13:00.240 got sales and marketing to kind of tell the worry 0:13:00.320 --> 0:13:02.320 of it on the on the back end. So yeah, 0:13:02.360 --> 0:13:06.040 cross functionally, I mean it's you know, over ten plus departments, 0:13:06.120 --> 0:13:09.160 and you know we have eighty plus engineers putting their 0:13:09.160 --> 0:13:09.960 fingerprints on it. 0:13:10.600 --> 0:13:12.280 And Chris is a part of your team, so I 0:13:12.320 --> 0:13:15.160 mean he's involved in so much of that kind of 0:13:15.480 --> 0:13:17.880 from start to finish process of how that golf club's 0:13:17.920 --> 0:13:19.760 going to look and perform and how it's going to 0:13:19.800 --> 0:13:21.840 perform the best, and how it's going to function the best. 0:13:22.080 --> 0:13:24.480 As he was mentioning kind of with that three wood example. 0:13:24.679 --> 0:13:27.880 Yeah, he's left his fingerprint on especially the modeling side 0:13:27.880 --> 0:13:30.000 of things here when we're looking at you know, being 0:13:30.000 --> 0:13:33.200 able to do virtual player test, tying it not only 0:13:33.280 --> 0:13:37.840 to our focal data, but also are like baldnamic. You know, 0:13:37.960 --> 0:13:39.800 Chris and I have worked together and teamed up on 0:13:39.960 --> 0:13:42.280 being able to simulate what's going to happen. How does 0:13:42.280 --> 0:13:45.760 wind affect it in things of that nature as well 0:13:45.800 --> 0:13:48.000 as Shane. Wh's really fun and Chris I want to 0:13:48.000 --> 0:13:52.599 get into is learning from en course data. So I 0:13:52.600 --> 0:13:54.880 think one of the things we have access to now is, 0:13:55.320 --> 0:13:58.000 you know, hundreds of millions of shots from from from 0:13:58.120 --> 0:14:01.319 Arcos and our partnership there where we got on course 0:14:01.440 --> 0:14:05.640 really precise GPS tracking data. Chris, tell us a little 0:14:05.640 --> 0:14:09.040 story of your first experience with that kind of again 0:14:09.080 --> 0:14:12.720 stepping back into your childhoodhood here of helping collect some 0:14:12.880 --> 0:14:17.800 data from en course play patterns, working with your dad 0:14:17.840 --> 0:14:19.040 when he was first getting into that. 0:14:19.640 --> 0:14:24.480 Yeah, we definitely have jumped around a good amount, but yeah, 0:14:24.560 --> 0:14:26.920 definitely started. I think maybe now when I was ten, 0:14:27.360 --> 0:14:30.480 my dad's focus shifted into the golf arena and how 0:14:30.520 --> 0:14:34.240 can we do a better job understanding golf performance. There 0:14:34.240 --> 0:14:36.000 are a bunch of different avenues. I think shot link 0:14:36.080 --> 0:14:37.600 was starting to come into the fold, so he knew 0:14:37.600 --> 0:14:40.040 there's some really good PGA Tour data, but there was 0:14:40.080 --> 0:14:43.080 nothing on amateur data outside of some kind of fairly 0:14:43.200 --> 0:14:43.880 hit green hit. 0:14:44.120 --> 0:14:45.760 You were talking about you and your dad kind of 0:14:45.800 --> 0:14:49.840 transitioning from baseball to golf. What was the why did 0:14:49.880 --> 0:14:51.760 he want to get into the golf analytics side? Did 0:14:51.760 --> 0:14:53.480 he get into golf at that point in his life? 0:14:53.600 --> 0:14:55.080 Did he just see opportunity there? 0:14:55.480 --> 0:14:57.600 Yeah? I think I think he saw opportunity. I think 0:14:57.800 --> 0:15:01.760 there's probably some frustration of trying to record golf stats 0:15:01.800 --> 0:15:07.320 and seeing like just some really obvious potential flaws in 0:15:07.360 --> 0:15:09.920 the stats. It was like there was, as I said, 0:15:09.920 --> 0:15:12.720 like faraoe hit percentage, green hit percentage, Like I think 0:15:12.720 --> 0:15:16.240 one of them was like putts per round, and it's like, Okay, 0:15:16.280 --> 0:15:20.480 the leader of that stat is not necessarily the best putter. 0:15:20.520 --> 0:15:22.320 It's the person who like misses the most screens and 0:15:22.440 --> 0:15:22.840 chips it. 0:15:22.800 --> 0:15:24.760 Up that's three feet totally totally. 0:15:24.920 --> 0:15:26.920 So he's just like that doesn't seem right. And then 0:15:27.640 --> 0:15:31.080 like every single stat you could just like poke some 0:15:31.120 --> 0:15:34.800 holes in it's like, I don't know, Tiger's hitting it 0:15:34.920 --> 0:15:37.760 miss He's missing like five percent more faraways than average, 0:15:37.800 --> 0:15:40.120 So it's like always he's a bad driver of the ball. 0:15:40.160 --> 0:15:41.640 I think that was a pretty like I've heard that 0:15:41.760 --> 0:15:44.400 narrative still like two thousand and six, he's spraying everywhere. 0:15:44.400 --> 0:15:46.760 Steven Aames probably bought into that too and lost nine 0:15:46.760 --> 0:15:51.920 to eight. But it's like you see on the surface, like, Okay, yeah, 0:15:51.920 --> 0:15:54.640 he's one eightieth and faaraow hit percentage, he has to 0:15:54.640 --> 0:15:57.280 be a bad golf driver of the golf ball, but 0:15:57.400 --> 0:16:00.280 just doesn't quite add up because you know, he's really 0:16:00.320 --> 0:16:01.600 doing very well in terments and. 0:16:02.360 --> 0:16:03.240 It was a weapon of him. 0:16:03.320 --> 0:16:04.000 Yeah he hit it. 0:16:04.000 --> 0:16:05.600 He might maybe sprayed a bit, but he had this 0:16:05.720 --> 0:16:08.240 distance that people couldn't keep up with at a time 0:16:08.280 --> 0:16:09.880 when that was transitioning into the game. 0:16:10.000 --> 0:16:10.160 Right. 0:16:10.240 --> 0:16:13.640 So I think the focus we in the quote unquote 0:16:13.640 --> 0:16:16.520 olden days in terms of statistics in golf, we were 0:16:16.600 --> 0:16:19.880 looking at these things is absolutes. Right, you hit fairways, 0:16:20.440 --> 0:16:23.760 that's great, You hit greens, that's great, But not every 0:16:23.800 --> 0:16:26.160 green regulation is the same, and not every fairway hit 0:16:26.240 --> 0:16:27.600 is the same, right, And I think that's something you 0:16:27.680 --> 0:16:29.960 guys have done an unbelievable job at breaking down. 0:16:30.280 --> 0:16:30.480 Yeah. 0:16:30.520 --> 0:16:31.920 I think it was just like, how do we get 0:16:31.920 --> 0:16:34.280 this into a context that makes sense? I think even 0:16:34.280 --> 0:16:37.160 the laying up on par fives, it's like there's some 0:16:37.160 --> 0:16:40.040 psychological safety of Oh, I can really easily hit a 0:16:40.080 --> 0:16:42.480 seven iron two hundred yards and I'm gonna hit the green, 0:16:42.720 --> 0:16:44.760 so it's gonna look good from a status respective like 0:16:45.520 --> 0:16:48.320 hitting more greens regulation that it feels safe. And it's 0:16:48.320 --> 0:16:50.880 like if you do take out a threewood and plasted 0:16:50.960 --> 0:16:54.040 around the green, somewhere you might be underneath the tree 0:16:54.040 --> 0:16:55.080 and that it might be hard to get on the 0:16:55.120 --> 0:16:58.200 green and you might be throwing off just like you're 0:16:58.200 --> 0:17:01.840 clean round. But it was nicer. He could kind of 0:17:01.840 --> 0:17:04.160 start to say, Okay, well, how do we get beyond 0:17:04.440 --> 0:17:07.800 just these counting stats? And I think, I don't know. 0:17:07.880 --> 0:17:10.200 My dad did a phenomenal job of like getting into 0:17:10.240 --> 0:17:13.080 that simplest metric, which I think makes sense. Like a 0:17:13.119 --> 0:17:15.600 lot of other stats have moved in that direction as well. 0:17:15.960 --> 0:17:20.359 Expected goals now is in hockey and soccer, the runs 0:17:20.359 --> 0:17:23.080 is in baseball. So it's like it was a trend 0:17:23.119 --> 0:17:26.000 that was happening. I would say someone probably would have 0:17:26.000 --> 0:17:28.199 come up with it if my dad did not, but 0:17:28.320 --> 0:17:30.720 helped answer some of those questions where it's like, Okay, 0:17:30.760 --> 0:17:34.000 what is the most meaningful metric for golf? It's shots 0:17:34.040 --> 0:17:36.200 and if you start looking in that perspective, then everything 0:17:36.240 --> 0:17:38.640 makes sense. Tires a really good driver with the golf ball. 0:17:38.720 --> 0:17:42.239 He follows the same blueprint as Rory and Bryson and 0:17:42.560 --> 0:17:44.360 guys who a long way but just miss a couple 0:17:44.440 --> 0:17:47.520 more fairways, missing one fairway per round, and here you 0:17:47.560 --> 0:17:50.040 get twenty five yards past the field. Is actually a 0:17:50.040 --> 0:17:53.080 really really good formula for playing good high level golf. 0:17:54.440 --> 0:17:56.440 So yeah, definitely cool to see, and it was also 0:17:56.480 --> 0:17:59.639 really cool growing up to like see coaches and players 0:17:59.640 --> 0:18:03.879 start to adopt it. So I think Luke, Donald Duarte, Mollinari, 0:18:04.320 --> 0:18:07.239 Chris Como, Sean Foley, where a lot of a lot 0:18:07.320 --> 0:18:09.520 of guys to start to reach out and like see 0:18:09.560 --> 0:18:12.720 the insights of of what what looking at things from 0:18:12.720 --> 0:18:16.960 a strokes gain perspective could do. So yeah, really really 0:18:17.000 --> 0:18:19.960 fun to be involved with the Tangentially as a sixteen 0:18:20.000 --> 0:18:21.000 year old didn't know anything. 0:18:21.400 --> 0:18:25.480 Brody, Let's let's fast forward to now and how have 0:18:25.960 --> 0:18:28.879 you in our team here? Where we've answered some of 0:18:28.880 --> 0:18:32.880 these questions, like brought that to the club fitting world. Right, 0:18:33.119 --> 0:18:35.960 So you're going in for a club fitting and you 0:18:36.040 --> 0:18:40.160 might have these kind of legacy ideas maybe in your head, 0:18:40.359 --> 0:18:42.720 you know, like like I got to hit it straighter, 0:18:42.760 --> 0:18:45.040 I gotta I gotta find the middle of the face more. 0:18:45.560 --> 0:18:47.280 You know, I need to play a shorter driver because 0:18:47.280 --> 0:18:50.439 that's what the tour players are doing. So, uh, you know, 0:18:50.640 --> 0:18:52.639 just let's double click on that a little bit of 0:18:52.640 --> 0:18:55.640