1 00:00:00,280 --> 00:00:02,400 Hi, and welcome to the Neil Ashton Podcast. 2 00:00:03,080 --> 00:00:05,920 In each episode, we explained some of the fascinating ways 3 00:00:05,920 --> 00:00:09,080 that science and engineering are changing the world around us. 4 00:00:09,800 --> 00:00:12,760 We talked to leading engineers from elite level sports like 5 00:00:12,840 --> 00:00:16,880 cycling and Formula One to some of the world's top academics to 6 00:00:16,880 --> 00:00:20,450 understand how fluid dynamics, machine learning and 7 00:00:20,450 --> 00:00:23,000 supercomputing are bringing in a new era of discovery. 8 00:00:23,960 --> 00:00:27,080 We also hear some of their life stories, their career advice, 9 00:00:27,640 --> 00:00:30,080 the lessons they've learned on the way that I hope will be 10 00:00:30,080 --> 00:00:33,800 helpful to you too. So sit back and enjoy this 11 00:00:33,800 --> 00:00:41,080 episode. Hi and welcome back to the Neil 12 00:00:41,080 --> 00:00:45,520 Ashton podcast today. Super excited about this, this 13 00:00:45,520 --> 00:00:49,240 episode. I'm a big fan of cycling. 14 00:00:49,680 --> 00:00:54,560 I'm a big fan of the use of engineering within sports, hence 15 00:00:54,560 --> 00:00:59,160 my love of Formula One. And I couldn't think of a better 16 00:00:59,400 --> 00:01:06,160 person and team to speak to, to help people to understand what 17 00:01:06,160 --> 00:01:09,520 cycling is all about and why engineering and technology is 18 00:01:09,520 --> 00:01:11,240 such an important thing for the sport. 19 00:01:11,240 --> 00:01:16,480 And in some ways, cycling is becoming, in my opinion, and 20 00:01:16,480 --> 00:01:19,720 growing to become more like Formula One in being not only a 21 00:01:19,720 --> 00:01:23,440 human sport, but one where technology is really making a 22 00:01:23,440 --> 00:01:28,440 difference with really exciting innovations that that then make 23 00:01:28,440 --> 00:01:32,080 their way to to you and I, you know, the, the, the public. 24 00:01:32,960 --> 00:01:38,120 And so today I'm speaking to to Kurt, Kurt Bergin-Taylor, who's 25 00:01:38,120 --> 00:01:40,960 the head of innovation at Tudor Pro Cycling. 26 00:01:41,560 --> 00:01:47,400 And I kind of say in a way that if you're in the know, you're a 27 00:01:47,400 --> 00:01:50,280 bit obsessed with with cycling like I am. 28 00:01:50,880 --> 00:01:54,444 I think it's pretty universally accepted that Tudor are 29 00:01:54,444 --> 00:01:59,556 actually one of the up and coming teams who I think have 30 00:01:59,556 --> 00:02:04,936 a very good chance in the next sort of two to five years of 31 00:02:04,936 --> 00:02:07,840 winning Grand Tours and some of the biggest races. 32 00:02:09,038 --> 00:02:12,280 As you'll find from the conversation today, you'll see 33 00:02:12,280 --> 00:02:18,360 they are taking really an amazing long term view of how to 34 00:02:18,360 --> 00:02:23,840 take technology and, and really, yeah, build up a team and a 35 00:02:23,840 --> 00:02:27,836 process and science to to really extract the maximum 36 00:02:27,836 --> 00:02:29,636 performance out of their riders. 37 00:02:29,644 --> 00:02:34,515 And of course the equipment based in based in Switzerland 38 00:02:34,523 --> 00:02:38,215 with a very famous owner in Fabian Cancellara, who of course 39 00:02:38,215 --> 00:02:42,752 is one of the world's most famous cyclist with amazing 40 00:02:42,760 --> 00:02:48,480 palmares and and Tudor obviously is one of the world's sort of 41 00:02:48,488 --> 00:02:52,420 top, top watch brands. It's a, it's a very interesting 42 00:02:52,420 --> 00:02:56,852 company, but really what we're talking about today is about 43 00:02:56,860 --> 00:03:01,625 what what is cycling, I suppose a little bit just to start off 44 00:03:01,633 --> 00:03:03,114 with. That's how we started the 45 00:03:03,122 --> 00:03:05,800 conversation. But really diving into the areas 46 00:03:05,800 --> 00:03:08,860 where technology makes a difference, where science makes 47 00:03:08,860 --> 00:03:11,735 a difference, and ultimately where there is innovation 48 00:03:11,743 --> 00:03:15,165 potential, which is the whole point of of Kurt's job. 49 00:03:15,173 --> 00:03:19,348 So we go through, you know, things like nutrition, thermal, 50 00:03:19,348 --> 00:03:23,894 so how the human body reacts to heat and cold. 51 00:03:23,902 --> 00:03:27,828 We talk about some of the influence of aerodynamics around 52 00:03:27,828 --> 00:03:30,440 the development. You hear some of the stuff 53 00:03:30,448 --> 00:03:35,216 they're doing, their use of CFD in terms of, you know, mannequin 54 00:03:35,216 --> 00:03:38,230 pedalling mannequins, how the strategy happens. 55 00:03:38,238 --> 00:03:44,016 You hear some about the number of race days that they have, the 56 00:03:44,016 --> 00:03:47,008 logistical challenges, hopefully all just to give you a 57 00:03:47,008 --> 00:03:50,308 better sense of why I again, I perceive now cycling as being, 58 00:03:50,308 --> 00:03:53,866 if you're into Formula One, I always say get into cycling 59 00:03:53,866 --> 00:03:57,320 because I really do think it's great human and technological 60 00:03:57,320 --> 00:04:00,200 sport. But at the end we talk about 61 00:04:00,200 --> 00:04:03,400 something that again, you, you know, it's a common theme of 62 00:04:03,400 --> 00:04:07,680 these podcasts is advice for people wanting to get into to 63 00:04:07,680 --> 00:04:10,680 the sport of cycling. But I'd say just in general 64 00:04:10,680 --> 00:04:13,840 advice for people wanting to do well in engineering and science 65 00:04:13,920 --> 00:04:16,920 and in any of the sort of sports engineering side. 66 00:04:16,920 --> 00:04:22,000 So, yeah, I, I, I really enjoyed this conversation. 67 00:04:22,000 --> 00:04:24,680 I, I actually learned some things from it and I was even 68 00:04:24,680 --> 00:04:29,120 more motivated with all the latest technological advances. 69 00:04:29,520 --> 00:04:34,040 So I, I hope you are too. I'm going to put some links in 70 00:04:34,040 --> 00:04:36,640 the chat about Tudor and so you can learn a little bit more 71 00:04:36,640 --> 00:04:39,880 about the team because again, I do think it's interesting and 72 00:04:39,960 --> 00:04:42,400 hopefully from there you'll make your way to learning a little 73 00:04:42,400 --> 00:04:46,280 bit also about the sport if you're not so familiar with Pro 74 00:04:46,280 --> 00:04:49,920 Cycling. So yeah, today sit back and 75 00:04:49,920 --> 00:04:54,600 enjoy this episode with Kurt Bergin-Taylor of Tudor Pro 76 00:04:54,600 --> 00:04:56,720 Cycling. Maybe you could tell a little 77 00:04:56,720 --> 00:05:00,280 bit more about yourself and Tudor Pro Cycling. 78 00:05:01,120 --> 00:05:04,200 Some people listening are probably really into cycling and 79 00:05:04,320 --> 00:05:06,640 proper geeks and know about the different teams. 80 00:05:06,640 --> 00:05:09,240 But maybe just to level set everybody, maybe you could just 81 00:05:09,240 --> 00:05:13,040 say a little bit about you, what you do at Tudor and who are 82 00:05:13,040 --> 00:05:16,080 Tudor Pro Cycling. Yeah, absolutely, Neil. 83 00:05:17,040 --> 00:05:19,680 So really my background comes from from academic. 84 00:05:20,360 --> 00:05:23,920 So rather than some people in cycling who've come from kind of 85 00:05:23,920 --> 00:05:26,280 being a professional athlete themselves, mine's more from 86 00:05:26,280 --> 00:05:30,720 from an academic background. Did a master's and then a PhD at 87 00:05:30,720 --> 00:05:33,480 Loughborough University in the UK and that was really around 88 00:05:33,480 --> 00:05:36,960 kind of physiology and nutrition around cycling really. 89 00:05:36,960 --> 00:05:40,720 So understanding kind of from a human component and that really 90 00:05:40,720 --> 00:05:43,880 kind of enticed me into wanting to work within, within cycling. 91 00:05:44,280 --> 00:05:47,280 I was really fortunate at that point in time to be able to work 92 00:05:47,280 --> 00:05:52,520 with people on the track. So people like Dan Bigham, who's 93 00:05:52,520 --> 00:05:54,920 kind of a performance engineer now working within cycling and 94 00:05:54,920 --> 00:05:57,640 also and, and doing some really interesting things about that 95 00:05:57,640 --> 00:06:01,480 human equipment interaction and, and looking at how to move 96 00:06:01,480 --> 00:06:04,600 forward, performance forward. And, and it attracts a really 97 00:06:04,600 --> 00:06:07,320 nice environment for that because it's, it's measured, you 98 00:06:07,320 --> 00:06:09,800 know, it's controlled. It's like a science experiment 99 00:06:09,800 --> 00:06:11,524 every time you go on the boards. 100 00:06:11,532 --> 00:06:14,920 So it's really has this culture for for innovation and that was 101 00:06:14,920 --> 00:06:16,783 something that I enjoyed so much. 102 00:06:16,791 --> 00:06:20,144 I really then decided I wanted to work within within cycling. 103 00:06:20,152 --> 00:06:23,336 And then I had the opportunity to go to Canada. 104 00:06:23,344 --> 00:06:26,876 So I worked for the Canadian federation on the track towards 105 00:06:26,876 --> 00:06:30,066 the Tokyo Olympic Games. And that was a really amazing 106 00:06:30,074 --> 00:06:32,361 experience in this kind of performance scientist role. 107 00:06:32,369 --> 00:06:36,440 So sitting in between the human, the equipment, the whole system 108 00:06:36,440 --> 00:06:41,088 innovation really and looking at that as a as a system and 109 00:06:41,088 --> 00:06:44,708 that was such a great experience towards that games. 110 00:06:44,716 --> 00:06:49,552 And yeah, really had a positive impact on on where I saw myself 111 00:06:49,552 --> 00:06:52,438 moving forward. Then COVID hit and yeah, the 112 00:06:52,446 --> 00:06:56,021 whole world kind of changed. So that was really a point where 113 00:06:56,021 --> 00:07:00,039 we decided that we had to come back to Europe and then had an 114 00:07:00,047 --> 00:07:02,848 opportunity to work within a professional cycling team more 115 00:07:02,856 --> 00:07:06,228 as a coach, which was Team DSM at the time. 116 00:07:06,236 --> 00:07:08,780 I worked there for two years, mainly in that physiological 117 00:07:08,788 --> 00:07:11,305 kind of coaching role. And then the opportunity with 118 00:07:11,313 --> 00:07:15,064 Tudor Pro Cycling came up to kind of sit back in that more 119 00:07:15,072 --> 00:07:18,584 holistic kind of space. So working with the physical and 120 00:07:18,584 --> 00:07:22,120 technical components of cycling, which is where I kind 121 00:07:22,120 --> 00:07:26,742 of see myself really as as a scientist, like not as a as an 122 00:07:26,742 --> 00:07:28,816 engineer, not as a physiologist, but really as a 123 00:07:28,816 --> 00:07:30,560 scientist. You can kind of, you know, make 124 00:07:30,560 --> 00:07:33,720 experiments, understand A versus B, and then find the right 125 00:07:33,720 --> 00:07:36,480 people with the expertise and knowledge to kind of drive 126 00:07:36,480 --> 00:07:40,240 things forward. In terms of the team, it's a 127 00:07:40,240 --> 00:07:42,040 really, it's a really interesting story. 128 00:07:42,480 --> 00:07:46,440 It was really born out of a team called Swiss Racing 129 00:07:46,440 --> 00:07:49,240 Academy. So there was a team in the past, 130 00:07:49,240 --> 00:07:52,040 a continental level team, which is like the third tier 131 00:07:52,040 --> 00:07:55,608 basically of cycling that was there to encourage Swiss 132 00:07:55,608 --> 00:07:58,480 riders to be able to make it professional basically. 133 00:07:58,480 --> 00:08:02,120 So it was a team that was made, so they had basic conditions to 134 00:08:02,120 --> 00:08:06,400 race, to have a salary, to have bikes, and that has been there 135 00:08:06,400 --> 00:08:09,720 for many years and was really kind of a successful pathway for 136 00:08:09,720 --> 00:08:11,920 Swiss riders to get into professional cycling. 137 00:08:12,440 --> 00:08:17,120 And in 2022, essentially that was going to close. 138 00:08:17,120 --> 00:08:21,320 So they struggled to gain their funding and it happened at a 139 00:08:21,320 --> 00:08:23,400 really difficult point in terms of timing. 140 00:08:23,800 --> 00:08:27,345 And basically, the guys who were left on that team were not 141 00:08:27,345 --> 00:08:29,620 going to be able to find another team because all the teams 142 00:08:29,620 --> 00:08:32,240 were full. And then the owner of our team, 143 00:08:32,240 --> 00:08:36,120 Fabian, Fabian Cancellara, who's a very famous and successful 144 00:08:36,120 --> 00:08:40,400 cyclist from, from Switzerland, really saw this opportunity as 145 00:08:40,840 --> 00:08:43,640 really saving, you know, the opportunity and careers of 146 00:08:43,640 --> 00:08:44,805 these, these young Swiss riders. 147 00:08:44,813 --> 00:08:47,740 And he put himself in their shoes and said, well, if I don't 148 00:08:47,740 --> 00:08:50,630 step in and, and give them this chance to, to ride, like 149 00:08:50,630 --> 00:08:52,520 what's going to happen to their career? 150 00:08:52,880 --> 00:08:55,360 And that's really the, the start of that process. 151 00:08:56,760 --> 00:09:00,280 Then he found out pretty quickly, you need sponsorship, 152 00:09:00,280 --> 00:09:01,922 you need help, you need support. 153 00:09:01,930 --> 00:09:05,478 And that's where Tudor came in. Tudor being the, the watch 154 00:09:05,486 --> 00:09:09,310 brand, part of the Hans Wilsdorf foundation with Rolex as the 155 00:09:09,318 --> 00:09:13,660 main sponsor of, of the team. And that started in 2022. 156 00:09:13,668 --> 00:09:17,649 And now we're we're going into our third year of being a Tudor 157 00:09:17,649 --> 00:09:21,347 Pro Cycling really, which is it's gone from strength to 158 00:09:21,355 --> 00:09:24,059 strength. We're a pro team, so second tier 159 00:09:24,059 --> 00:09:26,770 technically, but with like a world tour mindset. 160 00:09:26,778 --> 00:09:29,935 So we really see ourselves growing towards being one of the 161 00:09:29,935 --> 00:09:33,742 biggest teams in the world. And we're investing now in the 162 00:09:33,750 --> 00:09:37,178 kind of future of the team. We have a really long term 163 00:09:37,186 --> 00:09:39,300 vision. We invest in the staff, we 164 00:09:39,308 --> 00:09:42,220 invest in the people, we invest in the science really because we 165 00:09:42,220 --> 00:09:46,470 know long term that's what's going to make us at the highest 166 00:09:46,470 --> 00:09:52,300 level in the sport great. Yeah, and I suppose at least 167 00:09:52,308 --> 00:09:57,355 from, from myself watching it, Tudor's definitely seen as one 168 00:09:57,363 --> 00:10:01,232 of the top teams that potentially will get, you know, 169 00:10:01,232 --> 00:10:04,165 promoted, I guess, you know, in the in the coming years and 170 00:10:04,165 --> 00:10:07,588 gets the invitations to the to the sort of Grand Tours. 171 00:10:07,596 --> 00:10:11,529 So I guess to many people who are not deep into sport, you may 172 00:10:11,529 --> 00:10:13,456 people may not know the difference between the second 173 00:10:13,464 --> 00:10:16,502 tier and the top tier because Tudor tends to be in actually 174 00:10:16,510 --> 00:10:18,452 quite a few of the big races anyway. 175 00:10:18,460 --> 00:10:23,932 But you know, before maybe we get into some of the more 176 00:10:23,940 --> 00:10:28,075 detailed topics, what you know, what's it like working for a 177 00:10:28,083 --> 00:10:29,704 team? I imagine it's a bit like 178 00:10:29,712 --> 00:10:32,128 Formula One where there's a difference between, you know, 179 00:10:32,136 --> 00:10:35,860 the races, you know, the Lewis Hamiltons and the Julian 180 00:10:35,868 --> 00:10:38,165 Alaphilippes now and the team behind. 181 00:10:38,173 --> 00:10:41,906 So what what does it look like to to work for a pro team? 182 00:10:41,914 --> 00:10:45,455 You know, like a typical week, you know, how much are you at 183 00:10:45,463 --> 00:10:49,115 the races versus back at testing places in factories, just to 184 00:10:49,123 --> 00:10:51,628 give a sense. Yeah, yeah. 185 00:10:51,636 --> 00:10:55,120 No, I'd say the first thing is it's not very typical. 186 00:10:55,128 --> 00:10:58,328 So it's, it's one of them industries where especially my 187 00:10:58,336 --> 00:11:01,335 role kind of as as head of innovation, it really sits 188 00:11:01,343 --> 00:11:04,930 across, you know, many different disciplines and, and yeah, with 189 00:11:04,930 --> 00:11:08,852 with the first thing really with cyclists, the season is so, 190 00:11:08,852 --> 00:11:11,680 so big. So we race from the middle of 191 00:11:11,688 --> 00:11:13,665 January until the end of October. 192 00:11:13,673 --> 00:11:18,895 So we can be racing at three races on the same day all across 193 00:11:18,895 --> 00:11:20,887 Europe and even across the world. 194 00:11:20,895 --> 00:11:23,970 So it's a big logistical challenge first of all, where 195 00:11:23,978 --> 00:11:28,212 where everything occurs. We race roughly around 250 days 196 00:11:28,212 --> 00:11:32,760 a year in that period. So it's quite a lot of time on 197 00:11:32,768 --> 00:11:35,752 the ground that's obviously without the preparation before, 198 00:11:35,752 --> 00:11:38,214 after logistics and things like that. 199 00:11:38,222 --> 00:11:41,740 So that during that period really most of the time is 200 00:11:41,748 --> 00:11:44,200 focused on delivery of race delivery of performance 201 00:11:44,208 --> 00:11:47,040 delivery. So a lot of my support then is 202 00:11:47,048 --> 00:11:50,440 about optimization of setups, making sure that all the work 203 00:11:50,448 --> 00:11:53,665 we've done is executed. We, we have a really big push 204 00:11:53,673 --> 00:11:55,120 on, on the application of innovation. 205 00:11:55,128 --> 00:11:57,685 which I think is really important because we can do a 206 00:11:57,685 --> 00:12:00,388 lot of, you know, really cool things, but actually to get them 207 00:12:00,388 --> 00:12:03,388 to be applied at the right time with the right people in 208 00:12:03,388 --> 00:12:06,980 the right races is massive when you can have 3 or 4 races 209 00:12:06,980 --> 00:12:10,635 going on on the same day. So that's a big push during the 210 00:12:10,635 --> 00:12:12,820 season. We still have our innovation 211 00:12:12,828 --> 00:12:16,205 team that runs basically 24/7 throughout the season as well. 212 00:12:16,213 --> 00:12:18,772 So we have a setup based in Silverstone. 213 00:12:18,780 --> 00:12:24,812 We have 4 full time engineers, we have a PhD student, we have 214 00:12:24,820 --> 00:12:27,890 an industrial designer, all working on technological 215 00:12:27,898 --> 00:12:30,594 development. So we look at all the strands 216 00:12:30,602 --> 00:12:33,680 which we can approach really and we move them forward. 217 00:12:33,688 --> 00:12:36,864 And we have 3 strategic themes with all our innovation. 218 00:12:36,872 --> 00:12:39,740 So we look from aerodynamics because we know that's the 219 00:12:39,748 --> 00:12:42,068 biggest force that we overcome as a cyclist. 220 00:12:42,076 --> 00:12:45,298 We look from thermal because we know thermal challenges are 221 00:12:45,306 --> 00:12:48,302 really, really important. And then we look from safety. 222 00:12:48,310 --> 00:12:51,330 So everything that we do, we always try and say, can we make 223 00:12:51,330 --> 00:12:53,388 it faster or economically, can we understand the thermal 224 00:12:53,396 --> 00:12:56,965 properties and can we ultimately make it safer for the riders 225 00:12:56,973 --> 00:13:01,232 going into race and competition. And that can be if we're in the 226 00:13:01,232 --> 00:13:04,320 wind tunnel testing, it can be if we're doing fabric testing in 227 00:13:04,320 --> 00:13:06,194 the wind tunnel, whole system testing. 228 00:13:06,202 --> 00:13:07,894 How are we doing bike development? 229 00:13:07,902 --> 00:13:09,960 How are we doing CFD simulations? 230 00:13:09,968 --> 00:13:13,856 Are we doing velodrome testing? Are we in the field, doing 231 00:13:13,856 --> 00:13:16,524 in-field measurements of rolling resistance or tire 232 00:13:16,524 --> 00:13:19,800 development? Are we working with academic or 233 00:13:19,800 --> 00:13:21,520 industry partners on different projects? 234 00:13:21,520 --> 00:13:24,917 So it's really varied depending on what we have going on at 235 00:13:24,917 --> 00:13:27,560 that point in time. Yeah, I always find this 236 00:13:27,560 --> 00:13:32,720 fascinating, and I guess This is why so many people I know have 237 00:13:32,720 --> 00:13:37,080 this love of cycling who also tend to be into things like 238 00:13:37,080 --> 00:13:39,400 Formula One, because the technology is such an 239 00:13:39,400 --> 00:13:43,680 interesting part of it. But you mentioned something 240 00:13:43,680 --> 00:13:46,640 about the thermal side and that's something that I 241 00:13:47,080 --> 00:13:52,240 personally wasn't as familiar with until I personally did the 242 00:13:52,240 --> 00:13:54,440 Étape du Tour in like very hot temperatures. 243 00:13:54,480 --> 00:13:57,320 I was like, OK, thermal does actually make a lot of 244 00:13:57,320 --> 00:13:59,040 difference. So maybe could you explain a 245 00:13:59,040 --> 00:14:02,120 little bit more because I think this may actually be useful for 246 00:14:02,120 --> 00:14:04,560 day-to-day cyclists who are doing things. 247 00:14:04,800 --> 00:14:10,240 What sort of technology or learnings do you get about 248 00:14:10,360 --> 00:14:13,600 cycling in sort of more extreme conditions over, you know, very 249 00:14:13,600 --> 00:14:16,920 hot or very, very cold? But how does that influence the 250 00:14:16,920 --> 00:14:20,200 performance of a cyclist? Yeah, it's a really good 251 00:14:20,200 --> 00:14:23,840 question and it's something we see more and more is integral to 252 00:14:23,840 --> 00:14:27,960 the performance. I think that too are very 253 00:14:27,960 --> 00:14:30,080 different, you know, scenarios and situations. 254 00:14:30,320 --> 00:14:34,320 If we look at hot weather, we know that in Europe, from 255 00:14:34,600 --> 00:14:39,807 probably May until the end of August, it can be 35–40°C in 256 00:14:39,807 --> 00:14:43,800 some races, which we know is a really extreme environment. 257 00:14:44,120 --> 00:14:46,724 And we also know that the riders are getting fitter and 258 00:14:46,724 --> 00:14:48,703 stronger, which means they're putting out more power 259 00:14:48,703 --> 00:14:50,632 outputs, which ultimately means they're putting out more heat 260 00:14:50,632 --> 00:14:52,612 as well. Because yeah, what you see on 261 00:14:52,620 --> 00:14:55,990 the pedals is actually probably only 1/4 of the energy that's 262 00:14:55,998 --> 00:14:58,360 actually produced. The other 3/4 of that is thermal 263 00:14:58,360 --> 00:15:00,879 energy as well. So we know that you have these 264 00:15:00,887 --> 00:15:04,228 guys sitting in really hot environments making a lot of 265 00:15:04,236 --> 00:15:06,778 thermal energy, and something has to give. 266 00:15:06,786 --> 00:15:08,275 And ultimately that is performance. 267 00:15:08,283 --> 00:15:12,720 You know, we see more and more that it can be so critical to 268 00:15:12,728 --> 00:15:15,224 performance. If you overheat, things start to 269 00:15:15,224 --> 00:15:18,400 shut down, your body protects you from that and ultimately 270 00:15:18,408 --> 00:15:20,751 performance is part of a consequence of that. 271 00:15:20,759 --> 00:15:24,534 So we try and do a lot of research around heat. 272 00:15:24,542 --> 00:15:28,590 We do probably a few different strands. 273 00:15:28,598 --> 00:15:30,792 So we do kind of prevention and preparation. 274 00:15:30,800 --> 00:15:34,480 I would say so. We train the riders to tolerate 275 00:15:34,480 --> 00:15:37,437 heat demands. We know that that is a trainable 276 00:15:37,437 --> 00:15:40,234 stimulus like getting fitter. You can also tolerate heat 277 00:15:40,242 --> 00:15:42,010 better. You get changes with your sweat 278 00:15:42,010 --> 00:15:45,480 response, you get changes with plasma volume, you get these 279 00:15:45,488 --> 00:15:48,288 physiological changes which allow you to to basically deal 280 00:15:48,296 --> 00:15:52,359 better with the heat. So we do a lot of that 281 00:15:52,367 --> 00:15:54,365 preparation and we've seen more and more in cycling. 282 00:15:54,373 --> 00:15:57,158 That is probably the thing that's really increased a lot in 283 00:15:57,158 --> 00:15:59,630 the last year's research around that area, understanding 284 00:15:59,630 --> 00:16:02,852 of that area, understanding the transient responses that can 285 00:16:02,852 --> 00:16:06,850 be done there. And then we also see we do a lot 286 00:16:06,850 --> 00:16:09,440 of prevention stuff. So we look at precooling. 287 00:16:09,448 --> 00:16:13,140 Can we bring down the temperature prior or even during 288 00:16:13,140 --> 00:16:14,862 exercise? Can we create a bigger thermal 289 00:16:14,870 --> 00:16:18,732 sink so that we know there's just more room to drive heat 290 00:16:18,740 --> 00:16:21,384 into? And there's lots of great 291 00:16:21,392 --> 00:16:23,736 researchers in that area. We work with partners quite a 292 00:16:23,744 --> 00:16:27,395 lot on on that. We do a lot of work around 293 00:16:27,403 --> 00:16:30,760 fabrics and helmet design and things like that to understand 294 00:16:30,768 --> 00:16:33,750 convective cooling and, and material components and 295 00:16:33,758 --> 00:16:35,858 properties to really help with with that. 296 00:16:35,866 --> 00:16:38,866 And we're doing a lot of work around UV radiation because we 297 00:16:38,874 --> 00:16:42,376 know also this, you know, the radiative effect of sun as well 298 00:16:42,376 --> 00:16:44,902 and things like that. So there's definitely a lot of 299 00:16:44,910 --> 00:16:47,788 work to be done from a heat perspective to really allow 300 00:16:47,796 --> 00:16:49,665 athletes to perform in hot conditions. 301 00:16:49,673 --> 00:16:53,490 But like you said, also in the cold, it's something we see more 302 00:16:53,490 --> 00:16:54,962 and more. You know, some of the biggest 303 00:16:54,970 --> 00:16:57,832 one day races in the world, they're in Belgium in the middle 304 00:16:57,832 --> 00:17:00,990 of March and April. And I can tell you now from 305 00:17:00,998 --> 00:17:04,175 being there first hand, you want every layer of clothing you have 306 00:17:04,175 --> 00:17:07,300 on possible because the conditions can be really quite 307 00:17:07,308 --> 00:17:08,940 harsh. And that's something we also 308 00:17:08,948 --> 00:17:12,924 know if riders get cold, if they get wet, it also has a massive 309 00:17:12,932 --> 00:17:16,380 detriment on their performance. So it's something we work on 310 00:17:16,387 --> 00:17:20,972 quite a lot to also understand what can we do from a material 311 00:17:20,980 --> 00:17:23,592 perspective, from an intervention perspective, How do 312 00:17:23,592 --> 00:17:26,280 we do the logistics around that? 313 00:17:26,280 --> 00:17:28,840 You know, there's so many things that ultimately come back to 314 00:17:28,840 --> 00:17:30,200 logistics. How do you make sure you 315 00:17:30,200 --> 00:17:33,320 potentially have hot bottles that are available on the course 316 00:17:33,320 --> 00:17:37,360 when the whole peloton is strung out over over a few kilometres 317 00:17:37,360 --> 00:17:40,960 or doing clothing development to understand how to, you know, 318 00:17:40,960 --> 00:17:45,894 improve breathability or insulation in a harsh 319 00:17:45,894 --> 00:17:48,240 environment. So yeah, we really try and do 320 00:17:48,240 --> 00:17:52,120 quite a lot of work around that to understand what's going on. 321 00:17:52,720 --> 00:17:55,280 And I think on top of that, just something we've generally been 322 00:17:55,280 --> 00:17:58,360 doing with the team is we do a lot of work to understand real 323 00:17:58,360 --> 00:18:00,720 world conditions. So it's something that's been a 324 00:18:00,840 --> 00:18:04,040 big project that we do around everything is we have all these 325 00:18:04,040 --> 00:18:06,960 tools and techniques to, you know, to simulate in science. 326 00:18:06,960 --> 00:18:10,800 We try and take out the variables to to get answers, but 327 00:18:10,800 --> 00:18:14,160 we're trying to also understand how we tune them variables to 328 00:18:14,160 --> 00:18:15,440 understand things moving forward. 329 00:18:15,440 --> 00:18:19,600 So thermal being a massive piece, but yeah, wind, 330 00:18:20,160 --> 00:18:22,400 turbulence intensities, all these different things we're 331 00:18:22,400 --> 00:18:25,440 trying to understand so we can really make more informed 332 00:18:25,440 --> 00:18:28,560 decisions with the tools we use and the data that we drive out 333 00:18:28,560 --> 00:18:29,960 through our through our techniques. 334 00:18:31,120 --> 00:18:37,360 And maybe linked to that then, So what about, you know, we've 335 00:18:37,480 --> 00:18:40,360 seen a lot of people now tracking and I think there's 336 00:18:40,360 --> 00:18:46,960 some brand names that are shown on certain TV show commentary, 337 00:18:46,960 --> 00:18:49,120 you know, where they talk about their recovery, their sleep 338 00:18:49,120 --> 00:18:51,640 recovery and nutrition, things like that. 339 00:18:51,640 --> 00:18:57,000 How much of that do you think has contributed or maybe here's 340 00:18:57,000 --> 00:18:58,160 the big, here's the big question. 341 00:18:58,800 --> 00:19:02,760 You look at the current riders and look at them breaking 342 00:19:02,760 --> 00:19:06,200 records and and seeming to go faster and faster. 343 00:19:07,200 --> 00:19:12,600 How much of that do you think is down to bike technology? 344 00:19:13,280 --> 00:19:21,625 So aerodynamics, how much of it is down to training and how 345 00:19:21,625 --> 00:19:26,880 much of it is down to things like nutrition and sleep? 346 00:19:27,000 --> 00:19:30,720 Like what? Do you see them all equal or do 347 00:19:30,720 --> 00:19:34,400 you think some are more important than others? 348 00:19:35,200 --> 00:19:39,746 Yeah, I think they've all played their part in improving 349 00:19:39,746 --> 00:19:42,000 cycling over the last kind of 10 years, I would say. 350 00:19:42,000 --> 00:19:46,680 I mean, taking them individually, nutrition has been 351 00:19:46,680 --> 00:19:51,040 a massive driver for sure. If you look at where cycling was 352 00:19:51,040 --> 00:19:53,920 10 years ago and where it is now in terms of definitely all the 353 00:19:53,920 --> 00:19:57,720 research around carbohydrate intake, how to increase uptake, 354 00:19:57,720 --> 00:20:01,760 how to understand fueling, that's dramatically changed. 355 00:20:01,760 --> 00:20:04,240 And that we really know has helped drive performance 356 00:20:04,240 --> 00:20:05,720 forward. Because if you can have more 357 00:20:05,720 --> 00:20:08,320 carbohydrate availability and you can oxidize more 358 00:20:08,320 --> 00:20:10,320 carbohydrate, you can generate more energy. 359 00:20:10,320 --> 00:20:15,040 And I think that has been a, a big push with performance. 360 00:20:15,960 --> 00:20:18,960 And I think you see now that the training volumes that are able 361 00:20:18,960 --> 00:20:22,627 to be sustained the the physical level within racing and and 362 00:20:22,627 --> 00:20:24,880 just what you see mainly under fatigue. 363 00:20:24,920 --> 00:20:27,240 I think that's the biggest thing that we've really seen a shift 364 00:20:27,240 --> 00:20:30,560 is. Not only the fresh capacity of 365 00:20:30,560 --> 00:20:32,960 riders, but what they can do after four or five, six hours, 366 00:20:32,960 --> 00:20:35,760 what they can do after days, weeks of stage racing. 367 00:20:36,120 --> 00:20:38,880 I think that a lot of that is down to really optimizing 368 00:20:38,880 --> 00:20:41,320 nutrition. And you can see even since I've 369 00:20:41,320 --> 00:20:44,520 been working in professional cycling, the investment from 370 00:20:44,520 --> 00:20:47,000 teams around the area. You know, we have two 371 00:20:47,000 --> 00:20:52,920 nutritionists, we have 4 chefs, we have a food truck, we have 372 00:20:53,520 --> 00:20:56,400 nutrition sponsors, we have nutrition partners, we have 373 00:20:56,400 --> 00:20:59,880 academic nutrition partners. We have data scientists that 374 00:20:59,880 --> 00:21:03,000 look at all the data that we generate around nutrition. 375 00:21:03,000 --> 00:21:05,440 Actually, you know, we measure hydration status. 376 00:21:05,440 --> 00:21:10,083 We look at energy expenditure to make sure that we match on a 377 00:21:10,083 --> 00:21:13,560 day on day, on a meal, on meal basis across, you know, a 378 00:21:13,560 --> 00:21:16,040 Grand Tour for instance. And a lot of that has really 379 00:21:16,040 --> 00:21:17,560 helped drive performance forward. 380 00:21:17,560 --> 00:21:22,720 We see riders can train more, get sick less and perform much 381 00:21:22,720 --> 00:21:24,160 better, especially under fatigue. 382 00:21:24,160 --> 00:21:26,680 And a lot of that I think is down to nutrition over the last 383 00:21:26,680 --> 00:21:32,920 10 years, definitely aerodynamics and equipment 384 00:21:32,920 --> 00:21:34,400 development has moved forward a lot. 385 00:21:34,600 --> 00:21:37,960 You know, I think there was some teams early on that kind of 386 00:21:37,960 --> 00:21:40,600 clicked this. And I think, yeah, you know, it 387 00:21:40,600 --> 00:21:43,600 started really on the track. I think if you look at equipment 388 00:21:43,600 --> 00:21:45,960 development and where you see performance, I think British 389 00:21:45,960 --> 00:21:48,520 Cycling were kind of the the real front runners of that from 390 00:21:48,880 --> 00:21:51,560 probably 2004–2008 onwards on the track. 391 00:21:51,560 --> 00:21:54,800 And then they're starting to understand the physics involved. 392 00:21:55,240 --> 00:21:58,160 And as you know, there's such massive potential there. 393 00:21:58,160 --> 00:22:02,240 The rider is, you know, 80% of probably the drag in the system. 394 00:22:02,240 --> 00:22:05,320 And then what you wrap the rider in is a big part of that as 395 00:22:05,320 --> 00:22:06,840 well. So it's there's a lot of 396 00:22:06,840 --> 00:22:10,720 opportunities there that are now starting to be more and more 397 00:22:10,720 --> 00:22:12,880 understood. And we just see that the peloton 398 00:22:12,880 --> 00:22:17,560 just goes faster and faster. And for me, knowing the 399 00:22:17,560 --> 00:22:20,720 relationship between power and speed is, is cubic. 400 00:22:21,160 --> 00:22:24,200 It can't all come from power. You know, it's not that riders 401 00:22:24,200 --> 00:22:27,920 are all of a sudden getting to the, you know, to the cube more 402 00:22:27,920 --> 00:22:30,400 powerful, but actually the, you know, the, the demands are 403 00:22:30,400 --> 00:22:33,160 coming down as well because we're getting more aerodynamic. 404 00:22:33,160 --> 00:22:35,160 We're understanding that speed relationship. 405 00:22:35,920 --> 00:22:38,160 So that's been a big driver moving forward. 406 00:22:38,600 --> 00:22:41,240 And I'd say because of that, that's why as a team we're 407 00:22:41,240 --> 00:22:43,600 really, really focused on the safety part as well, because we 408 00:22:43,600 --> 00:22:47,240 just do so much, so many innovations to make our riders 409 00:22:47,240 --> 00:22:50,240 faster, fit and stronger, but we're also then putting them at 410 00:22:50,240 --> 00:22:52,240 more risk. You know, if you can go down, if 411 00:22:52,240 --> 00:22:54,320 you can go down climbs 10 kilometres per hour faster 412 00:22:54,320 --> 00:22:57,474 now, if you can take corners faster, if you can do this 413 00:22:57,474 --> 00:23:00,018 faster, that faster, we should also look after the riders 414 00:23:00,018 --> 00:23:01,640 more. So that's really why every 415 00:23:01,648 --> 00:23:04,239 innovation we do, we also take on that responsibility to make 416 00:23:04,247 --> 00:23:06,548 sure that we try and keep them safe as well. 417 00:23:06,556 --> 00:23:09,275 And I think, yeah, every team should do that. 418 00:23:09,283 --> 00:23:12,460 But we take that really seriously at Tudor Pro Cycling. 419 00:23:12,460 --> 00:23:14,720 Yeah, that's a very, yeah. 420 00:23:14,720 --> 00:23:16,800 There's definitely a sort of hot topic, isn't it, on the 421 00:23:18,040 --> 00:23:20,520 equipment versus the rider versus everything. 422 00:23:20,520 --> 00:23:23,760 It's, yeah, one I guess you could dedicate an entire 423 00:23:24,200 --> 00:23:27,600 conversation to. But one thing I did on that 424 00:23:27,600 --> 00:23:33,284 point of maybe training, I was listening to Geraint Thomas on, 425 00:23:33,284 --> 00:23:37,137 you know, on his podcast and I think he was talking with 426 00:23:37,137 --> 00:23:40,640 Pavel Sivakov about like the different training and they were 427 00:23:40,640 --> 00:23:43,360 talking about the sort of Team Sky where they basically just 428 00:23:43,360 --> 00:23:50,440 starved themselves and and went out comparing to now Pavel was 429 00:23:50,440 --> 00:23:52,960 talking about the sort of zone 2. 430 00:23:53,920 --> 00:23:56,680 But I always thought it was surprising because I assume 431 00:23:56,680 --> 00:23:58,320 that, OK, all the team do that anyway. 432 00:23:58,320 --> 00:24:02,920 But it it sort of made clear that he was describing that 433 00:24:02,920 --> 00:24:06,080 there was they spent a lot of junk miles that people would 434 00:24:06,080 --> 00:24:07,440 just go out. And because they're chatting 435 00:24:07,440 --> 00:24:10,240 with mates and they're drafting and they're so strong, the 436 00:24:10,240 --> 00:24:13,600 riders that they were probably only in zone 1 where now they're 437 00:24:13,600 --> 00:24:15,840 trying. And he says he was, he almost 438 00:24:15,840 --> 00:24:18,720 starts just training on his own because it's it's impossible to 439 00:24:18,720 --> 00:24:20,480 do. Is that something that you've 440 00:24:20,480 --> 00:24:25,400 seen as well as a very recent shift towards this more rigorous 441 00:24:26,120 --> 00:24:30,667 focus on extracting the maximum amount of all the time you're 442 00:24:30,667 --> 00:24:35,840 on the bike? Yeah, it's really interesting 443 00:24:35,840 --> 00:24:38,800 with training methodologies, there's, there's many ways to do 444 00:24:38,800 --> 00:24:40,760 it. And I think the longer I've 445 00:24:40,760 --> 00:24:43,676 worked in professional cycling, the more I've realized that 446 00:24:43,676 --> 00:24:46,560 it's really tailoring it to each individual rider. 447 00:24:46,560 --> 00:24:47,810 That's the most important thing. 448 00:24:47,818 --> 00:24:52,080 And the reason I say that is it's, you know, they have the 449 00:24:52,088 --> 00:24:53,540 same demands, you know, relative. 450 00:24:53,548 --> 00:24:56,136 I mean, a sprinter's obviously different to a climber or a 451 00:24:56,144 --> 00:24:58,275 classics rider, but they're endurance cyclists first of all. 452 00:24:58,275 --> 00:24:59,800 So there's this key kind of 453 00:25:00,280 --> 00:25:02,840 physiological underpinning of what you're trying to achieve to 454 00:25:02,840 --> 00:25:04,960 and then you've got these specific components on top. 455 00:25:05,480 --> 00:25:08,560 But I think we're a lot of or where maybe even when I was 456 00:25:08,560 --> 00:25:13,520 younger, people see training as is, is as you're training the 457 00:25:13,520 --> 00:25:15,840 machine, you know, you have these inputs and you have an 458 00:25:15,840 --> 00:25:19,000 output. And what we know now more and 459 00:25:19,000 --> 00:25:21,840 more and what I know working with with humans is that the 460 00:25:21,840 --> 00:25:24,120 input you put in doesn't always necessarily end up being the 461 00:25:24,120 --> 00:25:26,160 output. And the reason being is that, 462 00:25:26,560 --> 00:25:29,640 you know, training is the one lever we can adjust as a coach 463 00:25:29,640 --> 00:25:31,440 or as someone working within cycling. 464 00:25:31,840 --> 00:25:34,560 But what we can't adjust is the stress on their on their 465 00:25:34,560 --> 00:25:38,360 everyday life, their family, did they sleep well? 466 00:25:38,360 --> 00:25:42,160 What's their nutrition like? Are they happy? 467 00:25:42,160 --> 00:25:43,720 Are they depressed? There's all these different 468 00:25:43,720 --> 00:25:45,520 factors that go into a human being. 469 00:25:45,520 --> 00:25:48,960 And that what we understand more is that humans are very 470 00:25:48,960 --> 00:25:52,000 complicated systems. They're not just, they're not 471 00:25:52,000 --> 00:25:55,120 just individual inputs, but they have all this, these inputs 472 00:25:55,120 --> 00:25:56,920 actually interact with each other as well. 473 00:25:57,880 --> 00:26:02,440 And I think it's more about, I find tailoring the training 474 00:26:02,640 --> 00:26:04,720 relative to that. So you have your idea, you have 475 00:26:04,720 --> 00:26:07,800 your plan, you have your overall vision and goals and 476 00:26:07,800 --> 00:26:09,197 periodization, things like that. 477 00:26:09,205 --> 00:26:13,100 But it's been able to to tweak and tailor that relative to 478 00:26:13,108 --> 00:26:15,212 what's going on within that rider's life. 479 00:26:15,220 --> 00:26:18,055 Because, you know, you might have the best plan in the world, 480 00:26:18,055 --> 00:26:20,620 but if they're not eating properly or they're stressed at 481 00:26:20,620 --> 00:26:23,400 home, or, you know, they're running a second business on the 482 00:26:23,400 --> 00:26:25,401 side that you don't know about, then actually your 483 00:26:25,401 --> 00:26:27,240 optimal training might not be correct. 484 00:26:27,320 --> 00:26:30,320 Because, yeah, it's good on paper and it moves forward. 485 00:26:30,840 --> 00:26:33,680 And I would say every training methodology can have its 486 00:26:33,680 --> 00:26:36,320 benefits. It's something that I really 487 00:26:36,360 --> 00:26:39,320 reflected on quite a lot. Now, working in different 488 00:26:39,320 --> 00:26:41,960 environments and different teams, you see lots of different 489 00:26:41,960 --> 00:26:46,080 ways of achieving success. And ultimately I've seen things 490 00:26:46,080 --> 00:26:49,440 that, you know, maybe I wouldn't actually have done, but I've 491 00:26:49,440 --> 00:26:51,080 also seen them be very successful. 492 00:26:51,360 --> 00:26:55,577 And I've also started to, to, to learn and understand from, 493 00:26:55,577 --> 00:26:58,120 from them experiences that you can do things in many 494 00:26:58,120 --> 00:27:01,672 different ways. And yeah, some teams have 495 00:27:01,680 --> 00:27:04,180 certain philosophies and, and some riders go really, really 496 00:27:04,188 --> 00:27:06,388 well for them philosophies and other riders don't. 497 00:27:06,396 --> 00:27:10,006 And my philosophy is always to try and make the individual 498 00:27:10,014 --> 00:27:13,975 rider better. So I and I think when I look at 499 00:27:13,975 --> 00:27:17,300 kind of successful coaches or, or people that I really respect, 500 00:27:17,300 --> 00:27:20,334 it's the ones that make all their riders better, not just 501 00:27:20,342 --> 00:27:23,230 one. And I think that's where that 502 00:27:23,238 --> 00:27:25,952 individualisation, that communication with a rider, that 503 00:27:25,952 --> 00:27:29,264 understanding of where they're at and tailoring their training 504 00:27:29,264 --> 00:27:33,020 to them is stronger rather than just saying, OK, this is my 505 00:27:33,028 --> 00:27:35,675 training philosophy, we do it or or you don't. 506 00:27:35,683 --> 00:27:39,129 Yeah, that's a good point. And I guess this is what's, I 507 00:27:39,137 --> 00:27:41,830 guess maybe to people listening or to watching this who are into 508 00:27:41,830 --> 00:27:44,640 cycling. It's always the tricky thing 509 00:27:44,648 --> 00:27:49,740 because we there's always a temptation to follow a specific 510 00:27:49,740 --> 00:27:55,840 guide because you hear that somebody else does it, but you 511 00:27:55,848 --> 00:28:00,142 don't know whether should you just follow it and you just need 512 00:28:00,142 --> 00:28:02,950 to suck it up and just, you know, deal with the suffering, 513 00:28:02,958 --> 00:28:08,240 or is it just not well suited to you and you would be better 514 00:28:08,248 --> 00:28:11,312 doing something else? It's, you know, there's so much 515 00:28:11,312 --> 00:28:13,600 not misinformation, but there's so many different theories out 516 00:28:13,608 --> 00:28:17,770 there, isn't there, that it's hard for an amateur cyclist to 517 00:28:17,778 --> 00:28:22,060 really know what to follow. It's it's. 518 00:28:22,068 --> 00:28:24,054 Yeah, definitely. Sensationalized as well. 519 00:28:24,062 --> 00:28:28,270 I think so, especially when you, you know, you have a full time 520 00:28:28,278 --> 00:28:30,536 job and a family and and everything else and you're 521 00:28:30,544 --> 00:28:33,409 trying to do this as on the side, it is really difficult. 522 00:28:33,417 --> 00:28:36,783 You want to try and extract as much as you can out of it. 523 00:28:36,791 --> 00:28:39,600 And that's where I think it can be difficult because 524 00:28:39,608 --> 00:28:42,412 professional riders, they ride the bike, that's their full time 525 00:28:42,412 --> 00:28:44,050 job. And actually the other thing 526 00:28:44,058 --> 00:28:45,840 they can do is they can recover professionally. 527 00:28:45,848 --> 00:28:48,326 And a lot of amateurs can't do that. 528 00:28:48,334 --> 00:28:51,524 And I think that's the the challenge is you want to do what 529 00:28:51,524 --> 00:28:54,092 the pros are doing, but actually you can't do the 530 00:28:54,092 --> 00:28:56,000 recovery part. And we know that adaptations, 531 00:28:56,000 --> 00:28:57,480 they don't actually occur when you're on the bike. 532 00:28:57,480 --> 00:29:00,640 The stress happens then, but the adaptations happen afterwards. 533 00:29:00,640 --> 00:29:04,040 And if you can't have the adaptive processes, then maybe 534 00:29:04,040 --> 00:29:06,440 the training doesn't fulfill what you want it to achieve 535 00:29:06,440 --> 00:29:08,680 because you can't do the other proportion of that. 536 00:29:10,560 --> 00:29:12,640 Yeah, no, that, that makes complete sense. 537 00:29:13,720 --> 00:29:18,440 So what maybe going a little bit more into the, you know, the 538 00:29:18,440 --> 00:29:21,400 bike side of things. Where do you see the the sort of 539 00:29:21,400 --> 00:29:23,117 big performance areas nowadays? 540 00:29:23,125 --> 00:29:28,220 You know, is it, you know, in the bike, the fabric, you know, 541 00:29:28,220 --> 00:29:31,920 the tyre choice, you know, where some of the maybe 542 00:29:31,920 --> 00:29:35,640 interesting areas that that you think have led to some gains 543 00:29:35,640 --> 00:29:38,350 and maybe where are sort of future areas that people are 544 00:29:38,350 --> 00:29:42,622 starting to to explore now? I think the biggest thing you 545 00:29:42,630 --> 00:29:45,641 can look at really is, is the whole system approach. 546 00:29:45,649 --> 00:29:50,595 Like for me this is really critical looking at the rider 547 00:29:50,603 --> 00:29:53,400 and all their equipment as a whole system. 548 00:29:53,408 --> 00:29:58,062 The more kind of information or, or testing I've done, what you 549 00:29:58,070 --> 00:30:01,032 see is if you change one component of it, it's a cascade 550 00:30:01,032 --> 00:30:03,184 and everything else is interacting with that. 551 00:30:03,192 --> 00:30:07,030 And if you can't just say this helmet is fast, this skinsuit is 552 00:30:07,030 --> 00:30:10,264 fast, this bike is fast. It's in what context with what 553 00:30:10,272 --> 00:30:13,038 rider, with what demands. I think that that's the really 554 00:30:13,046 --> 00:30:16,940 kind of where I really see the innovation happening now on that 555 00:30:16,940 --> 00:30:20,700 individualized level, you know, because there is just such 556 00:30:20,700 --> 00:30:23,425 different demands on on them individual user cases. 557 00:30:23,433 --> 00:30:27,040 So, for instance, a sprinter, you know, we know sprinters go 558 00:30:27,048 --> 00:30:31,220 70–80 kilometres an hour in the final and we know they have to 559 00:30:31,228 --> 00:30:34,526 have very aggressive positions to try and put their heads in 560 00:30:34,534 --> 00:30:36,989 certain places. And we know because of all that, 561 00:30:36,989 --> 00:30:41,280 that we need to understand certain flow structures, certain 562 00:30:41,280 --> 00:30:45,664 stiffness, aerodynamics, we need to understand vision, we 563 00:30:45,664 --> 00:30:48,956 need to understand how all that interacts with each other. 564 00:30:48,956 --> 00:30:50,400 And we need to understand 565 00:30:50,520 --> 00:30:53,320 fabrics relative to that rider at them speeds. 566 00:30:54,040 --> 00:30:55,360 Whereas that is completely different. 567 00:30:55,360 --> 00:30:57,360 If you look at a climber, for instance, you know, the demands 568 00:30:57,360 --> 00:30:59,600 of a climber are going up, the climber probably coming down, 569 00:30:59,600 --> 00:31:02,720 the climber on the other side. And if we look at the whole 570 00:31:02,720 --> 00:31:05,600 system, the position, the orientation they're in, it's a 571 00:31:05,600 --> 00:31:08,960 completely different system. So one helmet is not going to be 572 00:31:09,640 --> 00:31:12,030 perfect for both. One skinsuit's not going to be 573 00:31:12,030 --> 00:31:13,652 perfect for both. One bike's not going to be 574 00:31:13,660 --> 00:31:16,064 perfect for both. So I think what we'll see in the 575 00:31:16,064 --> 00:31:19,610 industry of cycling is long term is this individualization 576 00:31:19,618 --> 00:31:22,828 development. So can we build stuff on an 577 00:31:22,836 --> 00:31:26,280 individualized basis? Can manufacture methods cope 578 00:31:26,288 --> 00:31:29,088 with that? You know, can we find ways to 579 00:31:29,096 --> 00:31:32,222 really individualize it? And I think that's where we see 580 00:31:32,222 --> 00:31:35,350 real benefit in terms of the performance moving forward. 581 00:31:35,358 --> 00:31:39,659 Yeah, that is so interesting. I, I must admit that that sort 582 00:31:39,667 --> 00:31:42,910 of aligns to some of the findings that I found, you know, 583 00:31:42,910 --> 00:31:46,680 when I was working on some of the British Cycling stuff. 584 00:31:46,688 --> 00:31:50,107 It's almost an unbelievably complicated optimization problem 585 00:31:50,107 --> 00:31:54,742 because you know that the, the bike, the rider, the wheel, the 586 00:31:54,742 --> 00:31:58,096 helmet and you, what you really want to do is test every 587 00:31:58,104 --> 00:31:59,720 combination with every other combination. 588 00:31:59,728 --> 00:32:05,510 And then whereas I guess a lot of the time because of 589 00:32:05,518 --> 00:32:08,880 commercial reasons, partnership reasons, you're like, hey, 590 00:32:08,888 --> 00:32:12,920 helmet manufacturer independently just give me a 591 00:32:12,928 --> 00:32:16,688 good helmet, but you haven't been involved in that. 592 00:32:16,696 --> 00:32:20,705 So with that, what you're trying to say that you're trying to be 593 00:32:20,705 --> 00:32:23,909 more involved with the partners so they can, so you're not just 594 00:32:23,909 --> 00:32:26,192 buying off the shelf something they've made, but potentially 595 00:32:26,200 --> 00:32:30,292 it's a little bit more aligned to your needs and how that 596 00:32:30,300 --> 00:32:33,160 interacts with the other bits you have. 597 00:32:33,168 --> 00:32:35,280 Yeah, 100%. It's something we've really 598 00:32:35,288 --> 00:32:37,920 driven forward in the last years and it's still a continual 599 00:32:37,928 --> 00:32:40,960 process. But we have what we call like 600 00:32:40,968 --> 00:32:42,658 reciprocal relationships with our partners. 601 00:32:42,666 --> 00:32:45,450 So we really make sure that when we select our partners, their 602 00:32:45,458 --> 00:32:48,360 partners that want to go on this innovation process with us 603 00:32:48,368 --> 00:32:54,075 because it's not easy, you know, it costs money, time, effort and 604 00:32:54,075 --> 00:32:57,732 we're really, you know demanding of what we want. 605 00:32:57,740 --> 00:33:00,955 But we're also, which I think is quite unique, we also have the 606 00:33:00,963 --> 00:33:04,406 capacities in house to actually put time and resource towards 607 00:33:04,414 --> 00:33:06,440 them problems. So it's not that we just knock 608 00:33:06,448 --> 00:33:09,459 on the door of our partner and say, OK, we want a new bike or a 609 00:33:09,459 --> 00:33:11,400 new helmet. We say no, we want to go on this 610 00:33:11,400 --> 00:33:13,480 project with you. We understand the demands that 611 00:33:13,488 --> 00:33:16,542 we're aiming towards. Let's do it in a collaboration. 612 00:33:16,542 --> 00:33:18,360 So, you know, a perfect example 613 00:33:18,360 --> 00:33:22,400 could be when we were developing a new helmet and we were 614 00:33:22,400 --> 00:33:26,440 developing a new helmet with a, with a new partner and we had 615 00:33:26,520 --> 00:33:29,400 wind tunnel trips happening in, in, in their location. 616 00:33:29,400 --> 00:33:31,920 Wind tunnel trips with our, with ourselves in the UK. 617 00:33:31,920 --> 00:33:34,960 We had riders there, we had 3D pedalling mannequins. 618 00:33:34,960 --> 00:33:38,880 We did simulation, we did all these collaboration approaches, 619 00:33:38,920 --> 00:33:43,760 thermal fit development over over over a long period of time 620 00:33:43,760 --> 00:33:46,520 to really make sure that the initial product we had was as 621 00:33:46,720 --> 00:33:48,480 evolved as possible in the time we had. 622 00:33:49,560 --> 00:33:52,400 And yeah, and we continue to try and do that across all the 623 00:33:52,400 --> 00:33:56,680 things you said, the bike, the tires, the wheels, the clothing. 624 00:33:56,680 --> 00:33:59,880 It's something that we're taking ownership of internally as a 625 00:33:59,880 --> 00:34:01,960 cycling team. And I think that's quite 626 00:34:01,960 --> 00:34:05,400 different to maybe many other cycling teams is we invest 627 00:34:05,400 --> 00:34:08,760 resource in that. You know, we have engineers, we 628 00:34:08,760 --> 00:34:13,800 have an industrial designer, we have fabric experts in house 629 00:34:13,800 --> 00:34:17,619 that complement the expertise of our partners to really make 630 00:34:17,619 --> 00:34:20,800 sure that there's investment from our side to to tailor the 631 00:34:20,800 --> 00:34:22,371 products to exactly what we need. 632 00:34:22,380 --> 00:34:26,362 So we really start to understand that and move it forward and we 633 00:34:26,362 --> 00:34:31,148 see that that will really be our way of moving forward and, 634 00:34:31,148 --> 00:34:34,121 and being at the forefront and it takes time, but I think it's 635 00:34:34,121 --> 00:34:37,360 the right way to do it. Investing in that innovation 636 00:34:37,368 --> 00:34:41,400 process is where we see really critical to to our performances 637 00:34:41,400 --> 00:34:47,621 in the future. And how easy or difficult is it 638 00:34:47,621 --> 00:34:53,449 or a barrier to get the riders involved because you've said at 639 00:34:53,449 --> 00:34:57,528 the same time they're off doing 60–70 race days or however long 640 00:34:57,528 --> 00:35:01,518 some of them do, How easy is it to get them to come, you know, 641 00:35:01,526 --> 00:35:05,420 to a test or to go? Is that a limiting factor 642 00:35:05,428 --> 00:35:08,720 sometimes? Yeah, there's a few things to 643 00:35:08,728 --> 00:35:11,098 that. I think the first thing we do is 644 00:35:11,098 --> 00:35:13,920 whenever we speak to new riders, we always tell them 645 00:35:13,920 --> 00:35:17,222 about our process, that we're, you know, we're an innovative 646 00:35:17,222 --> 00:35:21,090 team, that we take risks, that we push the boundaries on these 647 00:35:21,090 --> 00:35:22,240 things. And that ultimately that 648 00:35:22,240 --> 00:35:24,560 requires investment of time as well. 649 00:35:24,920 --> 00:35:27,800 And you know, for some riders, maybe that's not what they want 650 00:35:27,840 --> 00:35:30,840 from their cycling team. And therefore it's a 651 00:35:30,840 --> 00:35:33,720 conversation to have early on to set expectations. 652 00:35:34,440 --> 00:35:39,240 But we've also realized as we move forward that still it's, 653 00:35:39,280 --> 00:35:42,360 you know, it's impractical to expect riders to be available 654 00:35:42,400 --> 00:35:44,480 24/7 for the, for these learnings. 655 00:35:44,800 --> 00:35:46,680 So what we really try and do is we try and leverage 656 00:35:46,680 --> 00:35:48,920 methodologies that allow us to do a lot of the stuff 657 00:35:48,920 --> 00:35:51,480 beforehand. So we do a lot of simulation. 658 00:35:51,480 --> 00:35:54,600 We have 3D scans of the majority of our riders. 659 00:35:55,960 --> 00:35:57,960 So we can do a lot of digitalization. 660 00:35:57,960 --> 00:35:59,920 So we can do a lot of CFD computation. 661 00:35:59,920 --> 00:36:04,280 We can do a lot of clothing optimization fit, we can do a 662 00:36:04,280 --> 00:36:07,960 lot of understanding external to them even being needed. 663 00:36:08,760 --> 00:36:11,680 We also create mannequins and we have mannequins of, you know, 664 00:36:12,080 --> 00:36:14,440 our higher priority riders pedalling mannequins that allow 665 00:36:14,440 --> 00:36:17,080 us to go to the wind tunnel and test things without them being 666 00:36:17,080 --> 00:36:19,320 there. So we have really high 667 00:36:19,320 --> 00:36:22,600 repeatability methods. You know, it's also what we find 668 00:36:22,600 --> 00:36:26,680 is with riders, I'm sure anyone working with humans and doing 669 00:36:26,680 --> 00:36:29,360 testing, as you see that it's really difficult to get reliable 670 00:36:29,360 --> 00:36:33,000 data because naturally you're a human, you get tired, you get 671 00:36:33,000 --> 00:36:35,560 hungry. Whereas if you have a mannequin, 672 00:36:35,560 --> 00:36:38,240 you can run them for 10 hours a day and get ready for 673 00:36:38,240 --> 00:36:39,840 repeatability and not have to feed them. 674 00:36:39,840 --> 00:36:43,000 So it gives you a lot more scope and capacity to do that work. 675 00:36:43,440 --> 00:36:45,600 But there always needs to be a validation step and that's 676 00:36:45,600 --> 00:36:47,600 really important. We always make sure that all the 677 00:36:47,600 --> 00:36:51,640 work we're doing loops back to either field testing or some 678 00:36:51,640 --> 00:36:56,080 kind of simulation tool, be it wind tunnel track testing in the 679 00:36:56,080 --> 00:36:59,560 field to validate the findings that we find from doing all this 680 00:36:59,560 --> 00:37:02,800 kind of in-depth research. And for sure that costs time 681 00:37:02,800 --> 00:37:06,000 from the riders. But we try and educate our 682 00:37:06,000 --> 00:37:07,800 riders on why we're doing that. 683 00:37:07,808 --> 00:37:10,188 We, we empower them, we show them their data. 684 00:37:10,196 --> 00:37:12,695 You know, I think we're really open from that perspective. 685 00:37:12,703 --> 00:37:15,568 We, we give them that information so they understand, 686 00:37:15,568 --> 00:37:19,288 OK, we're asking you to do this and we've provided you this and 687 00:37:19,288 --> 00:37:22,060 this is the consequence. And for the majority of riders 688 00:37:22,068 --> 00:37:25,196 we work with, they're really involved in that process and 689 00:37:25,204 --> 00:37:28,696 they really understand it. I think it's one of the nice 690 00:37:28,704 --> 00:37:32,354 things with cycling. It's such a data rich sport that 691 00:37:32,354 --> 00:37:36,280 actually a lot of the cyclists understand watts; they 692 00:37:36,280 --> 00:37:39,400 understand watt savings, they understand speed gain. 693 00:37:39,400 --> 00:37:41,680 You know, they're even some of them, you know, they understand 694 00:37:41,680 --> 00:37:45,080 aerodynamics and they can quote you the equation for XYZ. 695 00:37:45,760 --> 00:37:48,920 And yeah, it's definitely something that's really powerful 696 00:37:48,920 --> 00:37:52,760 in cycling that that you can have that conversation and they 697 00:37:52,760 --> 00:37:55,080 know how hard they train to try and gain 10 watts. 698 00:37:55,080 --> 00:37:57,344 So when you can tell them you can find it from something 699 00:37:57,344 --> 00:37:59,608 else that they're usually quite grateful and willing to invest 700 00:37:59,608 --> 00:38:03,160 that time in. It and do you see a shift 701 00:38:03,160 --> 00:38:06,160 between the younger riders who were just coming through from 702 00:38:06,160 --> 00:38:08,080 the development squads and the older riders? 703 00:38:08,080 --> 00:38:11,800 Is there a has has has all of this changed? 704 00:38:11,800 --> 00:38:15,160 The past 5–10 years meant that the younger riders are far more 705 00:38:15,240 --> 00:38:19,040 educated than maybe the the older generation are. 706 00:38:20,120 --> 00:38:22,720 Yeah, it's, that's a really, really good question. 707 00:38:22,720 --> 00:38:26,320 It's something that we we see quite a lot in many different 708 00:38:26,320 --> 00:38:29,600 ways. So I think generally the younger 709 00:38:29,600 --> 00:38:32,880 generation are a lot more, like you said, maybe educated on it 710 00:38:32,880 --> 00:38:35,800 and, and, and thoughtful of it, but I'd say sometimes also 711 00:38:35,800 --> 00:38:37,880 obsessed with it, which can be quite interesting. 712 00:38:37,920 --> 00:38:42,400 You know, it's sometimes they think it's a, it's a PlayStation 713 00:38:42,400 --> 00:38:45,680 game and, and you know, it's a laboratory and, and, and it's, 714 00:38:45,680 --> 00:38:48,800 you know, it's only this equation of numbers and, and, 715 00:38:48,800 --> 00:38:50,400 and clothing and equipment and things like that. 716 00:38:50,400 --> 00:38:52,480 And what you actually see is, you know, you've also got to 717 00:38:52,480 --> 00:38:56,000 make decisions within a race. You've also got to be able to 718 00:38:56,000 --> 00:38:59,240 tactically and technically be able to execute on a bike. 719 00:38:59,240 --> 00:39:03,200 And there are things that sometimes are often overlooked, 720 00:39:03,200 --> 00:39:05,280 you know, with the younger generation that that that's what 721 00:39:05,280 --> 00:39:08,560 also wins your bike races. It's not just all this physics, 722 00:39:08,560 --> 00:39:11,400 but actually there's a it's a sport and there's decisions and 723 00:39:12,120 --> 00:39:14,720 it just we had some really interesting talks with with 724 00:39:14,720 --> 00:39:17,886 Julian. Julian has joined the team 725 00:39:17,886 --> 00:39:21,144 recently and historically, you know, he's not a man who's 726 00:39:21,144 --> 00:39:23,294 obsessed with data or insights, something like that. 727 00:39:23,302 --> 00:39:25,895 He's a guy who wants to race his bike, but he also understands 728 00:39:25,903 --> 00:39:29,256 the value of it and he trusts that if we say, OK, we're going 729 00:39:29,256 --> 00:39:31,860 to do XYZ, we're going to try to prove it, that we're working 730 00:39:31,860 --> 00:39:34,418 on that in the background, you know, and he's really open to 731 00:39:34,426 --> 00:39:36,229 that. But that was one of the things 732 00:39:36,237 --> 00:39:39,072 that was really important when he joined the team that we do 733 00:39:39,080 --> 00:39:41,860 this stuff. But he also has that passion 734 00:39:41,868 --> 00:39:45,610 about racing your bike and, you know, and educating the younger 735 00:39:45,610 --> 00:39:47,846 riders on tactics, technical positioning. 736 00:39:47,854 --> 00:39:50,594 There are things that we also know are super important as 737 00:39:50,602 --> 00:39:51,992 well. So it's definitely an 738 00:39:52,000 --> 00:39:54,680 interesting time in cycling from that regard. 739 00:39:54,688 --> 00:39:56,540 Yeah. And I think that's a really good 740 00:39:56,540 --> 00:40:00,740 point actually, because I feel in some ways that, you know, 741 00:40:00,748 --> 00:40:05,970 Team Sky arguably were the one that really heralded this shift 742 00:40:05,970 --> 00:40:10,255 to a more like marginal gains obviously data-driven, but I 743 00:40:10,263 --> 00:40:13,280 would argue that potentially it turned. 744 00:40:13,288 --> 00:40:17,632 Maybe it was the personalities who were in the team, but he was 745 00:40:17,632 --> 00:40:20,069 a little bit mechanical, a little bit the emotion maybe 746 00:40:20,077 --> 00:40:25,605 went out of it a little bit, which led to a bit of a backlash 747 00:40:25,605 --> 00:40:29,878 almost on some of that. And but now you've got people 748 00:40:29,886 --> 00:40:34,323 like Tadej who clearly do a lot of the data stuff where you, you 749 00:40:34,323 --> 00:40:36,867 know, he does a lot of training and the team. 750 00:40:36,875 --> 00:40:41,720 But it it it's perceivably seems more impulsive and more 751 00:40:41,728 --> 00:40:44,876 emotional, a bit like Julian Alaphilippe. 752 00:40:44,884 --> 00:40:48,640 So I guess the sport has to balance both, doesn't it? 753 00:40:48,648 --> 00:40:52,455 If it becomes too obsessed with all the data and sort of 754 00:40:52,463 --> 00:40:56,523 mechanical stuff, then the human side and what we love of seeing 755 00:40:56,523 --> 00:40:59,180 riders may sort of lose that as well. 756 00:40:59,188 --> 00:41:02,584 So I guess maybe that's the the balance isn't? 757 00:41:02,592 --> 00:41:05,816 It definitely, it's storytelling, you know, it's 758 00:41:05,824 --> 00:41:09,650 people, it's, it's, and I think the same thing happened with F1, 759 00:41:09,650 --> 00:41:13,828 you know, it's, it's, it's finding a way for people to to 760 00:41:13,836 --> 00:41:16,618 build them emotional relationships, to tell these 761 00:41:16,626 --> 00:41:19,680 stories, these experiences. That's just as important as all 762 00:41:19,680 --> 00:41:22,320 the tech that allows for them things to happen, you know. 763 00:41:22,328 --> 00:41:24,214 So it's definitely this, this balance for sure. 764 00:41:24,222 --> 00:41:28,040 Yeah, One thing that I would love to see, and I, I assume 765 00:41:28,048 --> 00:41:31,060 it's been discussed and maybe it's just not happened for 766 00:41:31,068 --> 00:41:36,540 various reasons, is I find the riders are so good at masking 767 00:41:36,548 --> 00:41:40,748 their pain that it's, you don't always know. 768 00:41:40,756 --> 00:41:44,697 And as a sort of more geeky person, I would love, and I know 769 00:41:44,697 --> 00:41:48,092 they've started to do this a little bit, but I would love to 770 00:41:48,092 --> 00:41:50,536 have their like body temperature, their heart rate, 771 00:41:50,544 --> 00:41:55,136 their power, like in real time. So I could sort of see how much 772 00:41:55,136 --> 00:41:58,680 they're suffering almost, you know, because sometimes you see 773 00:41:58,680 --> 00:42:02,078 somebody and you think they're doing great and then they 774 00:42:02,086 --> 00:42:04,962 suddenly just go and you think, surely, you know, he's felt that 775 00:42:04,962 --> 00:42:07,272 for a while, but he's just hidden it, you know? 776 00:42:07,280 --> 00:42:08,450 Do you know what I'm talking about? 777 00:42:08,458 --> 00:42:10,616 I don't know. The data could be. 778 00:42:10,624 --> 00:42:14,008 Used to make the sport more interactive in a way. 779 00:42:14,016 --> 00:42:18,004 It's a really good point and it's something, you know, as a, 780 00:42:18,004 --> 00:42:21,200 as Tudor and, and people I speak to have thought about a 781 00:42:21,200 --> 00:42:22,600 lot. It's, it's how do you improve 782 00:42:22,600 --> 00:42:26,080 that viewer engagement? You know, can you give more 783 00:42:26,080 --> 00:42:30,240 insights to allow, to allow for a better experience? 784 00:42:30,240 --> 00:42:33,240 And I think it's something that F1 did over the last, you know, 785 00:42:33,240 --> 00:42:37,680 5 or 10 years with cameras and, and having more of the, the 786 00:42:37,680 --> 00:42:40,360 radio on on on the TV and things like that. 787 00:42:40,360 --> 00:42:42,920 I think them things are that they're the really nice insights 788 00:42:42,920 --> 00:42:45,160 that you gather and you think, oh, OK, yeah, that, you know, I 789 00:42:45,160 --> 00:42:47,600 have this unique insight on what's happening in the F1 car. 790 00:42:47,600 --> 00:42:50,680 And I think cycling can, can definitely move forward. 791 00:42:50,680 --> 00:42:52,560 There are there are some initiatives, there's initiative 792 00:42:52,560 --> 00:42:55,920 called Velon, which is kind of a set a separate company that 793 00:42:55,920 --> 00:42:59,134 kind of is attached to certain races and they have like more 794 00:42:59,134 --> 00:43:02,052 data insights and they share certain insights they have in, 795 00:43:02,052 --> 00:43:04,742 you know, in video footage of the races. 796 00:43:04,750 --> 00:43:07,392 But apart from that, it's quite controlled from the UCI. 797 00:43:07,400 --> 00:43:09,576 So it's not something a team could do individually. 798 00:43:09,584 --> 00:43:12,700 You know, it's not like we could put cameras on every bike and 799 00:43:12,708 --> 00:43:16,180 release it to the world. It's very restrictive from that 800 00:43:16,180 --> 00:43:19,024 perspective. So it would take a from a UCI 801 00:43:19,032 --> 00:43:21,820 level from an organization to, to kind of take it forward. 802 00:43:21,828 --> 00:43:23,994 But for me, it's something that should definitely be done. 803 00:43:24,002 --> 00:43:26,840 And if it's done on a level playing field, there's no 804 00:43:26,848 --> 00:43:29,642 negative consequence of that. If everyone has to have a 805 00:43:29,650 --> 00:43:32,345 camera, then it's the same, you know, and then you get all these 806 00:43:32,345 --> 00:43:34,200 insights. So no, I will be definitely for 807 00:43:34,200 --> 00:43:37,590 that. So maybe one you, you mentioned 808 00:43:37,590 --> 00:43:42,478 a little bit and maybe this is tying a little bit to some of 809 00:43:42,486 --> 00:43:46,707 the AI or machine learning side of things, but maybe first on 810 00:43:46,715 --> 00:43:50,150 the strategy side. So you've talked a lot about 811 00:43:50,158 --> 00:43:56,086 nutrition, bike design, how much data can be used to optimize 812 00:43:56,094 --> 00:43:58,035 strategy? You know, when someone should 813 00:43:58,043 --> 00:44:03,377 try, because sometimes I watch a race and I see somebody try to 814 00:44:03,385 --> 00:44:08,409 break away and I think surely there's an optimum power for 815 00:44:08,417 --> 00:44:12,223 them to just get that break, you know, to get the elastic to go. 816 00:44:12,223 --> 00:44:13,280 And you think, oh, if they could 817 00:44:13,280 --> 00:44:16,400 have just gone for another 10 seconds, maybe they would have 818 00:44:16,400 --> 00:44:20,560 actually made it. Is there any way that you can 819 00:44:20,560 --> 00:44:25,000 look at that sort of more strategy side of things with the 820 00:44:25,000 --> 00:44:27,602 data-driven sport as it is now? 821 00:44:27,610 --> 00:44:32,136 Yeah, it's something I think a lot of teams are are trying to 822 00:44:32,144 --> 00:44:36,130 do and excited about. Like I said, cycling's a very 823 00:44:36,138 --> 00:44:37,758 data-rich sport. So we have a lot of data. 824 00:44:37,766 --> 00:44:41,002 You know, we have second by second data on all our riders 825 00:44:41,010 --> 00:44:44,864 for maybe 1000 hours of training a year for many, many years. 826 00:44:44,872 --> 00:44:48,272 So we have a lot of data there and I think people are now 827 00:44:48,280 --> 00:44:51,622 starting to harness it. We definitely have quite a few 828 00:44:51,630 --> 00:44:56,110 projects that we look at, you know, we try and look at certain 829 00:44:56,110 --> 00:44:58,595 riders. Can they make it in certain 830 00:44:58,603 --> 00:45:01,235 races, you know, maybe sprinters for instance, can they pass 831 00:45:01,243 --> 00:45:02,924 certain climbs? What's the probability of 832 00:45:02,932 --> 00:45:06,480 chances of success to get to a certain point? 833 00:45:06,488 --> 00:45:09,240 Yeah. Do we expect a breakaway or not? 834 00:45:09,240 --> 00:45:10,640 I think it's quite an 835 00:45:10,640 --> 00:45:14,800 interesting one. Do we expect it to to succeed? 836 00:45:14,800 --> 00:45:17,440 Should we should we participate in that on certain stages? 837 00:45:18,720 --> 00:45:20,560 I think there's, there's lots of things that can be done. 838 00:45:20,560 --> 00:45:26,000 There's a lot of stuff around race choice and, and picking 839 00:45:26,000 --> 00:45:28,440 certain races for certain riders, understanding where 840 00:45:28,440 --> 00:45:31,480 their kind of potential is, you know, for, for results. 841 00:45:32,920 --> 00:45:36,280 So yeah, there's definitely a lot of optimization for, for 842 00:45:36,280 --> 00:45:38,800 those kind of data insights from data that's driven there. 843 00:45:39,160 --> 00:45:42,680 And then I think also with AI and, and the other kind of 844 00:45:42,680 --> 00:45:44,880 emerging techniques, there's, there's lots of stuff to be done 845 00:45:44,880 --> 00:45:48,560 around, around all the CFD computation stuff that we do. 846 00:45:48,920 --> 00:45:52,440 We've found that really in the early processes of that, but 847 00:45:53,000 --> 00:45:55,360 every time we run a simulation, every time we generate some 848 00:45:55,360 --> 00:45:58,760 data, we know that there could be long term potential insights 849 00:45:58,760 --> 00:46:00,040 in that data. So it's really about 850 00:46:00,040 --> 00:46:05,644 understanding how to sequence, to store, to evolve to know that 851 00:46:05,644 --> 00:46:08,695 maybe, you know, maybe not now, but in one year, 2 year, 852 00:46:08,695 --> 00:46:11,438 five years, there's, there's insights that can be gathered 853 00:46:11,438 --> 00:46:13,560 from that. And I think it's, yeah, making 854 00:46:13,560 --> 00:46:16,360 sure you're in the the right place now to set them things up 855 00:46:16,480 --> 00:46:19,317 so that in the future it is definitely a possibility, that's 856 00:46:19,317 --> 00:46:21,280 for sure. So would it be fair to say that 857 00:46:21,280 --> 00:46:28,800 probably cycling has for the past, you know, 2-3, four years 858 00:46:28,800 --> 00:46:32,800 been moving far more to a data-driven approach, But we're, 859 00:46:32,840 --> 00:46:37,600 we're only just entering now the age of really AI for it. 860 00:46:37,600 --> 00:46:42,360 That would it be fair to say that most of cycling is probably 861 00:46:42,360 --> 00:46:44,760 always just now really getting into potential. 862 00:46:44,760 --> 00:46:48,400 So that could be something in the coming years that that could 863 00:46:48,400 --> 00:46:50,400 be used because as we talked about that sort of design 864 00:46:50,400 --> 00:46:52,840 optimization, you know, you've got so many different choices 865 00:46:52,840 --> 00:46:57,880 that seems or even logistics, I guess AI is a classic tool for 866 00:46:57,880 --> 00:47:01,680 optimizing things. Yeah, yeah, it definitely is 867 00:47:01,680 --> 00:47:03,480 something that I think we'll see more and more of. 868 00:47:03,480 --> 00:47:07,040 I think the sport itself is getting more professional, more 869 00:47:07,040 --> 00:47:09,560 funding. It's having, you know, more 870 00:47:10,440 --> 00:47:13,680 people like myself working in sport, you know, kind of sitting 871 00:47:13,680 --> 00:47:16,720 in between the lines of of scientists that are kind of 872 00:47:16,720 --> 00:47:19,680 integrated. And yeah, I'd say most of the 873 00:47:19,720 --> 00:47:22,160 highest level teams now are starting to understand that and 874 00:47:22,160 --> 00:47:25,440 invest some of their resource in that and not just in better 875 00:47:25,440 --> 00:47:28,480 riders or, you know, or things like that. 876 00:47:29,520 --> 00:47:34,040 So what how about for for Tudor in particular, what does the, 877 00:47:34,160 --> 00:47:38,240 the sort of future hold? What, what's the big target, I 878 00:47:38,240 --> 00:47:42,440 guess this year and the coming years that that is driving all 879 00:47:42,440 --> 00:47:45,000 this towards? Do you have some very specific 880 00:47:45,320 --> 00:47:48,600 things that the team is trying to, you know, focus on and and 881 00:47:48,640 --> 00:47:53,320 and succeed? Yeah, I think as a team, I mean 882 00:47:53,320 --> 00:47:55,360 we have, we have quite a lot of strategy. 883 00:47:55,360 --> 00:47:57,160 I think in terms of where we want to go. 884 00:47:57,160 --> 00:47:59,880 We're we're really fortunate that we're a long term team. 885 00:47:59,960 --> 00:48:03,440 We have a long term vision and and a sustainable long term 886 00:48:03,440 --> 00:48:06,400 vision, which I think is quite unique in cycling. 887 00:48:07,880 --> 00:48:12,240 I think the first priority of the team is really to be in a 888 00:48:12,240 --> 00:48:14,680 position to allow us to have the full race calendar. 889 00:48:15,400 --> 00:48:17,080 So for people who don't understand cycling, if you're 890 00:48:17,080 --> 00:48:20,040 not a World Tour team, if you aren't one of the top 18 teams, 891 00:48:20,360 --> 00:48:24,000 then essentially you're kind of at the will of the race 892 00:48:24,000 --> 00:48:26,440 organizers to invite you to the biggest races. 893 00:48:27,720 --> 00:48:32,080 So we know if we achieve a certain rating every year, being 894 00:48:32,080 --> 00:48:35,240 one of what's called the top 2 pro teams, then that will allow 895 00:48:35,240 --> 00:48:36,402 us to have a full race calendar. 896 00:48:36,410 --> 00:48:40,115 And then once we have a full race calendar, it then opens up 897 00:48:40,115 --> 00:48:43,181 all the opportunities in terms of where we want to go and how 898 00:48:43,189 --> 00:48:44,235 we want to do stuff at the moment. 899 00:48:44,243 --> 00:48:48,040 Because we're a brand new team, we have to rely on them 900 00:48:48,048 --> 00:48:50,840 invitations, which can make planning and strategy quite 901 00:48:50,848 --> 00:48:54,300 challenging sometimes. So that's our first real goal. 902 00:48:54,308 --> 00:48:57,496 And really the long term goal, especially from my perspective 903 00:48:57,504 --> 00:49:01,312 is around the innovation team is really to just be a world 904 00:49:01,320 --> 00:49:04,860 leading innovation team with regards to performance. 905 00:49:04,868 --> 00:49:08,700 So safety, aerodynamics, thermal from all the opportunities, 906 00:49:08,700 --> 00:49:11,460 having this whole system, individualized approach around 907 00:49:11,460 --> 00:49:15,784 key riders, looking at them as a whole system is really where 908 00:49:15,784 --> 00:49:18,214 the next, you know, 5–10 years look like. 909 00:49:18,222 --> 00:49:21,756 And we can really do that ultimately, because we have a 910 00:49:21,764 --> 00:49:23,503 sustainable platform to launch from. 911 00:49:23,511 --> 00:49:27,079 You know, it's, I can imagine it's quite hard if you're in a 912 00:49:27,087 --> 00:49:29,344 team that's unstable to think, you know, I'm going to do this 913 00:49:29,352 --> 00:49:32,380 now and it might not pay off in five years, but we, we're in a 914 00:49:32,388 --> 00:49:34,406 real good place that we can do that. 915 00:49:34,414 --> 00:49:37,744 And I think that really allows us to be a front runner in the 916 00:49:37,752 --> 00:49:41,214 future and really invest in this kind of data-driven science 917 00:49:41,222 --> 00:49:45,609 driven approach. So maybe turning maybe towards 918 00:49:45,617 --> 00:49:49,845 the end of the of this chat, towards the topic that, I think 919 00:49:49,845 --> 00:49:52,920 is I personally am always interested in which is the 920 00:49:52,928 --> 00:49:56,860 advice for people and engineers wanting to get into the sport. 921 00:49:56,868 --> 00:50:00,942 You know, you, you came through the PhD route and then you, you 922 00:50:00,942 --> 00:50:03,920 know, you sort of work towards, you say like different sports, 923 00:50:03,928 --> 00:50:07,860 then track and then team, you know, looking back, what sort 924 00:50:07,860 --> 00:50:11,418 of advice? Maybe let's break it down from a 925 00:50:11,418 --> 00:50:13,880 is it? Yeah, well, first of all, high 926 00:50:13,888 --> 00:50:17,610 level advice and then maybe we can pick apart some stuff. 927 00:50:17,618 --> 00:50:23,339 Yeah, I think about this a lot. I I really try and, yeah, take 928 00:50:23,347 --> 00:50:26,257 responsibility on myself to, to look back at, you know, when I 929 00:50:26,265 --> 00:50:29,066 was younger and what were the reasons why I, I'm in the 930 00:50:29,074 --> 00:50:32,601 fortunate position I am now. And I really try and give back 931 00:50:32,609 --> 00:50:36,120 to that because for me, some of the things I really reflect on 932 00:50:36,128 --> 00:50:39,765 is I had really good mentors. Like I had people who went 933 00:50:39,773 --> 00:50:43,300 through that process and really allowed me to connect, to 934 00:50:43,308 --> 00:50:45,646 discuss, to learn, to evolve, grow. 935 00:50:45,654 --> 00:50:51,155 And I think that was fundamental to where I am today, having them 936 00:50:51,155 --> 00:50:53,222 mentorships. If it's just having a coffee, 937 00:50:53,230 --> 00:50:55,551 picking the phone up, what do you think about this? 938 00:50:55,559 --> 00:50:56,920 Oh, I have a friend who does this. 939 00:50:56,928 --> 00:50:58,670 You know, why don't you have some conversations? 940 00:50:58,678 --> 00:51:02,040 I think that I'd really encourage that spirit of, you 941 00:51:02,048 --> 00:51:05,020 know, mentorship is really important and I think it's 942 00:51:05,028 --> 00:51:07,669 responsible both for young practitioners, but also for 943 00:51:07,677 --> 00:51:11,194 experienced practitioners like myself to, to also give back, I 944 00:51:11,194 --> 00:51:15,382 think is really important. I think the other thing is work 945 00:51:15,382 --> 00:51:18,958 ethic and, and, and doing your time like it's something that I 946 00:51:18,958 --> 00:51:22,640 really, you know, pride myself on and was something that really 947 00:51:22,640 --> 00:51:25,878 allowed me to move forward. You know, I was the first person 948 00:51:25,878 --> 00:51:28,830 to say yes to a volunteer opportunity to fill up bottles 949 00:51:28,838 --> 00:51:33,295 on the side of a rugby pitch, you know, or if it was to go to 950 00:51:33,295 --> 00:51:37,248 a swim meet in, in, you know, wherever and at 6:00 AM in the 951 00:51:37,256 --> 00:51:39,972 morning, just to, to be embedded within sport opportunities. 952 00:51:39,980 --> 00:51:43,590 And I didn't, and I really tried to take on as many opportunities 953 00:51:43,590 --> 00:51:46,480 as I could when I was younger just to see and feel and 954 00:51:46,488 --> 00:51:48,796 understand why I wanted to work in professional sport. 955 00:51:48,804 --> 00:51:52,705 And that goes a long way because when people see you're just 956 00:51:52,713 --> 00:51:57,038 willing to, to say yes and, and to, to understand and learn, I 957 00:51:57,046 --> 00:52:01,439 think can be really valuable. And, and that's a trait that I 958 00:52:01,447 --> 00:52:05,560 really look for in people. I look for that kind of willing 959 00:52:05,560 --> 00:52:08,270 spirit. I think a lot of people in my 960 00:52:08,278 --> 00:52:11,689 experience, you can train them for the, for the skills that you 961 00:52:11,689 --> 00:52:14,344 need, but actually the, the character and personality of 962 00:52:14,352 --> 00:52:17,265 someone is kind of ingrained. And I think if you can show 963 00:52:17,273 --> 00:52:20,360 that, you know, you're willing to, to work, to, to listen to, 964 00:52:20,368 --> 00:52:23,768 to put, to put effort in, to be passionate about something. 965 00:52:23,776 --> 00:52:27,426 I, I go for that any day over someone who has, you know, five 966 00:52:27,426 --> 00:52:30,024 years experience of doing the job already, You know, I really 967 00:52:30,024 --> 00:52:32,555 look for, for that. So that would be some of the 968 00:52:32,563 --> 00:52:35,142 things I would say mentorship really and and that kind of 969 00:52:35,150 --> 00:52:37,115 spirit of just willing to, to do. 970 00:52:37,123 --> 00:52:41,667 And what about from a practical point of view? 971 00:52:41,675 --> 00:52:47,640 What sort of are you looking more for like engineers, more 972 00:52:47,648 --> 00:52:52,574 for sports science, more for like data science? 973 00:52:52,582 --> 00:52:57,704 Is there certain sort of skill sets and maybe degrees that put 974 00:52:57,704 --> 00:53:01,060 you, I guess traditionally sports science would have been 975 00:53:01,068 --> 00:53:04,595 the route in to a sport. Is that still the case or do you 976 00:53:04,595 --> 00:53:06,976 think it's more about like engineering and data science 977 00:53:06,984 --> 00:53:09,784 now? I'd say historically you're 978 00:53:09,792 --> 00:53:12,700 correct. It was sports science and, and 979 00:53:12,708 --> 00:53:16,215 really probably was, yeah, the first investment I'd say from 980 00:53:16,223 --> 00:53:20,105 professionals, at least in cycling was sports science and 981 00:53:20,113 --> 00:53:22,654 understanding sports derived things, physiologists. 982 00:53:22,662 --> 00:53:27,515 And what you saw is then people generally then sat like myself 983 00:53:27,523 --> 00:53:30,632 across many spectrums. You know, we did data science, 984 00:53:30,640 --> 00:53:33,814 we did performance analysis. We kind of did the bits that we 985 00:53:33,814 --> 00:53:36,768 did some nutrition, maybe we did different things to really 986 00:53:36,768 --> 00:53:39,672 allow performance to move forward and having that 987 00:53:39,672 --> 00:53:41,880 generalized skill set was probably the way in. 988 00:53:41,880 --> 00:53:45,960 I'd say, you know, 5 or 10 years ago, I'd say now sport within 989 00:53:45,960 --> 00:53:48,240 cycling in particular, there's enough investment and 990 00:53:48,240 --> 00:53:51,400 understanding that these really specified roles are coming in 991 00:53:51,400 --> 00:53:54,800 and become really important. And I think for people who have 992 00:53:54,800 --> 00:53:57,720 them specific skills and their passion for sport, there's some 993 00:53:57,720 --> 00:53:59,400 really unique opportunities growing. 994 00:53:59,400 --> 00:54:03,360 So for instance, data science, you know, I, I know a bit of, of 995 00:54:03,360 --> 00:54:06,400 data science, but not to the level of a data scientist. 996 00:54:06,400 --> 00:54:08,720 And I think if you can come in with them skills, but also the 997 00:54:08,840 --> 00:54:12,360 conceptual understanding of cycling, you, there's massive 998 00:54:12,360 --> 00:54:13,560 potential for that in the future. 999 00:54:13,560 --> 00:54:16,880 And the same with engineers, you know, having aerodynamic 1000 00:54:16,880 --> 00:54:20,680 engineers, design engineers, Mechanical Engineers that have 1001 00:54:20,920 --> 00:54:24,440 this desire to work in cycling and this conceptual 1002 00:54:24,440 --> 00:54:27,240 understanding of cycling, I see more and more opportunities for 1003 00:54:27,240 --> 00:54:30,520 them either within professional teams or within partners that 1004 00:54:30,520 --> 00:54:33,680 work with teams. And you see that's definitely a 1005 00:54:33,680 --> 00:54:36,560 growing field now really that high level science within, 1006 00:54:36,560 --> 00:54:39,200 within sport and particularly with cycling, it's more and more 1007 00:54:39,200 --> 00:54:43,920 opportunities. And is there are there any 1008 00:54:43,920 --> 00:54:47,280 recommendations? You know, when people sometimes 1009 00:54:47,280 --> 00:54:50,760 ask me about Formula One, sometimes I say, OK, well if you 1010 00:54:50,760 --> 00:54:55,087 can't get into Formula One, try and do with a lower 1011 00:54:55,087 --> 00:54:57,528 quote-unquote quote, lower formula first just to get a 1012 00:54:57,528 --> 00:54:59,870 practice spin. Is that something people can do 1013 00:54:59,870 --> 00:55:02,910 with cycling? Or is that a slight almost gap 1014 00:55:02,918 --> 00:55:05,810 that you know, it's either you've done a university course 1015 00:55:05,810 --> 00:55:09,627 or you work for a cycling team, but how do you get the 1016 00:55:09,635 --> 00:55:12,462 experience to know? Is there any things that you're 1017 00:55:12,462 --> 00:55:15,824 aware of that people can clue themselves up on? 1018 00:55:15,832 --> 00:55:18,832 Cycling-specific knowledge. Yeah, yes, it's definitely 1019 00:55:18,840 --> 00:55:23,470 difficult to make that bridge like you said, I'd say 1 The 1020 00:55:23,478 --> 00:55:26,876 thing that I've seen successful people do is using the 1021 00:55:26,884 --> 00:55:31,492 opportunities they have through their time as a student to allow 1022 00:55:31,492 --> 00:55:34,544 for opportunities to interact with with professional sports. 1023 00:55:34,552 --> 00:55:37,240 So, you know, if you're an undergraduate or a master's 1024 00:55:37,248 --> 00:55:40,614 student and you know, you have to do a placement or you have to 1025 00:55:40,614 --> 00:55:43,259 do a final year project, trying to drive that final year 1026 00:55:43,259 --> 00:55:45,544 project in a direction where you can interact with a 1027 00:55:45,544 --> 00:55:47,560 professional team is a really nice way. 1028 00:55:47,560 --> 00:55:50,495 Because if you can approach them and say, you know, I need to 1029 00:55:50,495 --> 00:55:54,360 do 200 hours of X, Y, Z. I need to do simulation, I 1030 00:55:54,360 --> 00:55:57,696 need to do wind-tunnel tests, I need to do in the field 1031 00:55:57,704 --> 00:55:59,546 research on this topic. And I think it's really 1032 00:55:59,554 --> 00:56:02,326 interesting for you and we can shape the question to answer 1033 00:56:02,334 --> 00:56:04,802 your problems. They're the kind of things that 1034 00:56:04,802 --> 00:56:06,900 would get me really excited, you know, students that have 1035 00:56:06,900 --> 00:56:10,695 that initiative, that have that capacity to drive to drive 1036 00:56:10,695 --> 00:56:13,788 this thing forward. And it's a, you know, it can be 1037 00:56:13,788 --> 00:56:16,438 a three month interview. And even within our team, we 1038 00:56:16,446 --> 00:56:19,467 have one member that came directly from that kind of 1039 00:56:19,475 --> 00:56:21,220 process. You know, he showed 1040 00:56:21,228 --> 00:56:24,820 initiative, stepped through it as a as a master's student and 1041 00:56:24,828 --> 00:56:27,485 really secured an opportunity straight from graduating in, in 1042 00:56:27,485 --> 00:56:30,809 professional sport because he showed that initiative to yeah 1043 00:56:30,817 --> 00:56:34,050 on, on how to move, move himself forward. 1044 00:56:34,058 --> 00:56:37,740 So I'd say really try and shape the experiences you have towards 1045 00:56:37,740 --> 00:56:41,488 sport and, and bring a question and a solution rather 1046 00:56:41,488 --> 00:56:43,440 than just, you know, asking for experience. 1047 00:56:43,448 --> 00:56:46,770 I think that's something that's can really help you break into 1048 00:56:46,778 --> 00:56:49,783 professional sport and, and also don't worry when you get a no, 1049 00:56:49,791 --> 00:56:54,052 you know, I think if I remember my initial period, I applied for 1050 00:56:54,052 --> 00:56:58,085 so many job opportunities and, and yeah, and, and sometimes 1051 00:56:58,093 --> 00:57:00,670 it's not the right time, the right place and, and that's 1052 00:57:00,678 --> 00:57:03,034 completely fine. And, and I really believe they 1053 00:57:03,042 --> 00:57:06,455 shape you to the person you are, you know, and, and yeah, don't, 1054 00:57:06,455 --> 00:57:08,692 don't give up when it, when it becomes difficult. 1055 00:57:08,700 --> 00:57:12,200 I think that's just something that really allows you to to 1056 00:57:12,208 --> 00:57:17,010 break into difficult industry. No, that's, that's a great piece 1057 00:57:17,010 --> 00:57:20,861 of advice. And no, I, I actually, I mean 1058 00:57:20,869 --> 00:57:25,661 the big picture, I always, and I guess the reason why I, we're so 1059 00:57:25,661 --> 00:57:29,615 keen to speak to you and, and generally talk about cycling is 1060 00:57:29,615 --> 00:57:34,230 I feel like engineering or sort of sports side of engineering 1061 00:57:34,238 --> 00:57:38,840 almost is some people turn away from engineering because it's 1062 00:57:38,848 --> 00:57:43,790 almost perceived as not being exciting or it's not being fun 1063 00:57:43,798 --> 00:57:47,780 and they see football or whatever or cycling as being 1064 00:57:47,788 --> 00:57:49,681 fun. And I suppose one of the things 1065 00:57:49,681 --> 00:57:53,895 I've always been a fan of is that if you can link those two 1066 00:57:53,903 --> 00:57:57,295 things, then it's like you have the pleasure of working on 1067 00:57:57,303 --> 00:57:59,309 something that you actually like. 1068 00:57:59,317 --> 00:58:03,388 And I think Formula One was traditionally always that thing. 1069 00:58:03,388 --> 00:58:06,440 But I think it's it, it has, 1070 00:58:06,600 --> 00:58:08,720 it's just hard to get into. That's just the one. 1071 00:58:08,720 --> 00:58:12,440 And there are so many aerodynamicists working in a 1072 00:58:12,440 --> 00:58:16,465 team 50, I don't know, maybe 70 that you're just working on, 1073 00:58:16,465 --> 00:58:20,160 you know, the equivalent of optimizing a spoke on a wheel, 1074 00:58:20,160 --> 00:58:23,960 let's say, where I guess if they work for someone like your 1075 00:58:23,960 --> 00:58:26,960 company, they're going to be working the whole thing 1076 00:58:26,960 --> 00:58:30,640 probably. So it's like it's more rewarding 1077 00:58:30,680 --> 00:58:36,120 maybe actually to sort of go into a cycling thing maybe than 1078 00:58:36,120 --> 00:58:39,640 Formula One in a way. So it's almost, maybe I'm 1079 00:58:39,760 --> 00:58:42,800 encouraging if there's people listening to maybe consider 1080 00:58:43,120 --> 00:58:45,440 getting into the sort of cycling side of engineering because it 1081 00:58:45,440 --> 00:58:48,320 could be more fulfilling potentially than your 1082 00:58:48,320 --> 00:58:52,320 traditional Formula One. Yeah, it definitely offers that 1083 00:58:52,320 --> 00:58:55,400 opportunity to go through the whole process as well. 1084 00:58:55,400 --> 00:58:58,600 You know, it is a sport. We, you know, we're much less 1085 00:58:58,600 --> 00:59:01,360 budget, we're more, you know, agile with our resource. 1086 00:59:01,360 --> 00:59:03,960 And yeah, if you're in aero analysis within cycling, you 1087 00:59:03,960 --> 00:59:07,407 work everything from, you know, conceptual CFD all the way to 1088 00:59:07,407 --> 00:59:09,520 to real world validation with a human being. 1089 00:59:09,520 --> 00:59:13,080 And you're you get to have all them touch points across that 1090 00:59:13,080 --> 00:59:14,640 that piece. And I think it makes you a much 1091 00:59:14,720 --> 00:59:17,000 better practitioner when it's like that, you know, when you 1092 00:59:17,000 --> 00:59:20,320 can understand from really complex kind of, you know, 1093 00:59:20,640 --> 00:59:23,867 fundamentals all the way down to convincing a human being of 1094 00:59:23,867 --> 00:59:25,952 the work you're doing and getting their feedback and 1095 00:59:25,952 --> 00:59:29,680 having a holistic approach. That to me is what gets me out 1096 00:59:29,680 --> 00:59:31,320 of bed every day. You know, I get to do this 1097 00:59:31,320 --> 00:59:34,360 really complex science, but actually apply it and then 1098 00:59:34,720 --> 00:59:37,920 ultimately seeing it in in competition and, you know, 1099 00:59:38,280 --> 00:59:40,520 watching it on TV or be there in person. 1100 00:59:40,520 --> 00:59:43,585 And, you know, having your heart rate at 180 beats a minute 1101 00:59:43,585 --> 00:59:46,317 when when they're going into a final and thinking, yeah, I've 1102 00:59:46,317 --> 00:59:48,440 played a small part in that. That's, that's a really nice 1103 00:59:48,440 --> 00:59:49,920 feeling. And I would definitely encourage 1104 00:59:50,240 --> 00:59:53,520 people who are interested to, yeah, to reach out and and to 1105 00:59:53,520 --> 00:59:55,520 look at opportunities inside because it's definitely a 1106 00:59:55,520 --> 00:59:58,600 growing space moving forward. Great. 1107 00:59:58,640 --> 01:00:02,040 Well, yeah, thanks so much Kurt, for for for chatting today. 1108 01:00:02,040 --> 01:00:06,139 I'm hoping people, you know, got the same that I have this, 1109 01:00:06,139 --> 01:00:11,687 which is just this excitement, I guess for for cycling and you 1110 01:00:11,687 --> 01:00:15,994 know, For Tudor, I think it's great when there's these new 1111 01:00:15,994 --> 01:00:19,160 relatively new teams coming in trying to sort of shake it up. 1112 01:00:19,240 --> 01:00:22,200 And I think it's it's good because it makes the more 1113 01:00:22,200 --> 01:00:25,220 established teams aware they've got to shake up and it. 1114 01:00:25,220 --> 01:00:26,840 And it's good also for people 1115 01:00:26,840 --> 01:00:28,640 who wanted to get into the sport, that there's more 1116 01:00:28,640 --> 01:00:33,080 companies, more jobs. So yeah, thank you so much for 1117 01:00:33,080 --> 01:00:37,040 speaking and educating us all on on what it's like to be a Pro 1118 01:00:37,040 --> 01:00:38,880 Cycling team. Perfect. 1119 01:00:38,920 --> 01:00:39,360 Thanks, Neil.