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 in Formula One to some of the world's top academics to 6 00:00:16,880 --> 00:00:20,960 understand how fluid dynamics, machine learning, supercomputing 7 00:00:21,360 --> 00:00:23,000 are bringing in a new era 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 new 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 level sort of 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 Bergen 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 --> 00:01:54,840 I think it's pretty universally accepted that Tudor are actually 29 00:01:54,840 --> 00:02:00,840 one of the up and coming teams who I think have a very good 30 00:02:00,840 --> 00:02:05,680 chance in the next sort of two to five years of winning Grand 31 00:02:05,680 --> 00:02:07,840 Tours and some of the biggest races. 32 00:02:09,039 --> 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 --> 00:02:28,280 process and science to to really extract the maximum performance 36 00:02:28,320 --> 00:02:31,280 out of their riders. And of course the equipment 37 00:02:32,640 --> 00:02:36,760 based in based in Switzerland with a very famous owner in 38 00:02:36,760 --> 00:02:39,960 Fabian Cancellara, who of course is one of the world's most 39 00:02:39,960 --> 00:02:46,240 famous cyclist with amazing palmares and and Tudor obviously 40 00:02:46,240 --> 00:02:49,760 is one of the world's sort of top, top watch brands. 41 00:02:50,280 --> 00:02:54,200 It's a, it's a very interesting company, but really what we're 42 00:02:54,360 --> 00:02:59,840 talking about today is about what what is cycling, I suppose 43 00:02:59,840 --> 00:03:01,880 a little bit just to start off with. 44 00:03:01,880 --> 00:03:03,360 That's how we started the conversation. 45 00:03:03,520 --> 00:03:07,320 But really diving into the areas where technology makes a 46 00:03:07,320 --> 00:03:10,400 difference, where science makes a difference, and ultimately 47 00:03:10,400 --> 00:03:13,400 where there is innovation potential, which is the whole 48 00:03:13,400 --> 00:03:17,280 point of of Kurt's job. So we go through, you know, 49 00:03:17,280 --> 00:03:22,960 things like nutrition, thermal, so how the human body reacts to 50 00:03:23,000 --> 00:03:25,680 heat and cold. We talk about some of the 51 00:03:25,720 --> 00:03:28,880 influence of aerodynamics around the development. 52 00:03:28,880 --> 00:03:32,000 You hear some of the stuff they're doing, their use of CFD 53 00:03:32,000 --> 00:03:37,360 in terms of, you know, mannequin peddling mannequins, how the 54 00:03:37,440 --> 00:03:40,600 strategy happens. You hear some about the number 55 00:03:40,600 --> 00:03:45,480 of race days that they have, the logistical challenges, hopefully 56 00:03:45,480 --> 00:03:49,040 all just to give you a better sense of why I again, I perceive 57 00:03:49,040 --> 00:03:52,840 now cycling as being, if you're into Formula One, I always say 58 00:03:52,840 --> 00:03:56,600 get into cycling because I really do think it's great human 59 00:03:56,600 --> 00:04:00,200 and technological sport. But at the end we talk about 60 00:04:00,200 --> 00:04:03,400 something that again, you, you know, it's a common theme of 61 00:04:03,400 --> 00:04:07,680 these podcasts is advice for people wanting to get into to 62 00:04:07,680 --> 00:04:10,680 the sport of cycling. But I'd say just in general 63 00:04:10,680 --> 00:04:13,840 advice for people wanting to do well in engineering and science 64 00:04:13,920 --> 00:04:16,920 and in any of the sort of sports engineering side. 65 00:04:16,920 --> 00:04:22,000 So, yeah, I, I, I really enjoyed this conversation. 66 00:04:22,000 --> 00:04:24,680 I, I actually learned some things from it and I was even 67 00:04:24,680 --> 00:04:29,120 more motivated with all the latest technological advances. 68 00:04:29,520 --> 00:04:34,040 So I, I hope you are too. I'm going to put some links in 69 00:04:34,040 --> 00:04:36,640 the chat about Tudor and so you can learn a little bit more 70 00:04:36,640 --> 00:04:39,880 about the team because again, I do think it's interesting and 71 00:04:39,960 --> 00:04:42,400 hopefully from there you'll make your way to learning a little 72 00:04:42,400 --> 00:04:46,280 bit also about the sport if you're not so familiar with Pro 73 00:04:46,280 --> 00:04:49,920 Cycling. So yeah, today sit back and 74 00:04:49,920 --> 00:04:54,600 enjoy this episode with Kurt Picken Taylor of Tudor Pro 75 00:04:54,600 --> 00:04:56,720 Cycling. Maybe you could tell a little 76 00:04:56,720 --> 00:05:00,280 bit more about yourself and Tudor Pro Cycling. 77 00:05:01,120 --> 00:05:04,200 Some people listening are probably really into cycling and 78 00:05:04,320 --> 00:05:06,640 proper geeks and know about the different teams. 79 00:05:06,640 --> 00:05:09,240 But maybe just to level set everybody, maybe you could just 80 00:05:09,240 --> 00:05:13,040 say a little bit about you, what you do at Tudor and who are 81 00:05:13,040 --> 00:05:16,080 Tudor Pro Cycling. Yeah, absolutely, Neil. 82 00:05:17,040 --> 00:05:19,680 So really my background comes from from academic. 83 00:05:20,360 --> 00:05:23,920 So rather than some people in cycling who've come from kind of 84 00:05:23,920 --> 00:05:26,280 being a professional athlete themselves, mine's more from 85 00:05:26,280 --> 00:05:30,720 from an academic background. Did a masters and then a PhD at 86 00:05:30,720 --> 00:05:33,480 Loughborough University in the UK and that was really around 87 00:05:33,480 --> 00:05:36,960 kind of Physiology and nutrition around cycling really. 88 00:05:36,960 --> 00:05:40,720 So understanding kind of from a human component and that really 89 00:05:40,720 --> 00:05:43,880 kind of enticed me into wanting to work within, within cycling. 90 00:05:44,280 --> 00:05:47,280 I was really fortunate at that point in time to be able to work 91 00:05:47,280 --> 00:05:52,520 with people on the track. So people like Dan Bigham, who's 92 00:05:52,520 --> 00:05:54,920 kind of a performance engineer now working with in psych and 93 00:05:54,920 --> 00:05:57,640 also and, and doing some really interesting things about that 94 00:05:57,640 --> 00:06:01,480 human equipment interaction and, and looking at how to move 95 00:06:01,480 --> 00:06:04,600 forward, performance forward. And, and it attracts a really 96 00:06:04,600 --> 00:06:07,320 nice environment for that because it's, it's measured, you 97 00:06:07,320 --> 00:06:09,800 know, it's controlled. It's like a science experiment 98 00:06:09,800 --> 00:06:13,000 every time you go on the board. So it's really has this culture 99 00:06:13,000 --> 00:06:16,520 for for innovation and that was something that I enjoyed so 100 00:06:16,520 --> 00:06:18,360 much. I really then decided I wanted 101 00:06:18,360 --> 00:06:22,280 to work within within cycling. And then I had the opportunity 102 00:06:22,280 --> 00:06:24,920 to go to Canada. So I worked for the Canadian 103 00:06:24,920 --> 00:06:28,440 federation on the track towards the Tokyo Olympic Games. 104 00:06:28,800 --> 00:06:31,120 And that was a really amazing experience in this kind of 105 00:06:31,200 --> 00:06:34,680 performance scientist role. So sitting in between the human, 106 00:06:34,680 --> 00:06:38,200 the equipment, the whole system innovation really and looking at 107 00:06:38,200 --> 00:06:43,560 that as a as a system and that was such a great experience 108 00:06:43,560 --> 00:06:47,000 towards that games. And yeah, really had a positive 109 00:06:47,000 --> 00:06:50,280 impact on on where I saw myself moving forward. 110 00:06:50,800 --> 00:06:53,800 Then COVID hit and yeah, the whole world kind of changed. 111 00:06:53,800 --> 00:06:58,240 So that was really a point where we decided that we had to come 112 00:06:58,240 --> 00:07:01,320 back to Europe and then had an opportunity to work within a 113 00:07:01,320 --> 00:07:05,520 professional cycling team more as a coach, which was Team DSM 114 00:07:05,520 --> 00:07:07,640 at the time. I worked there for two years, 115 00:07:07,640 --> 00:07:09,920 mainly in that physiological kind of coaching role. 116 00:07:09,920 --> 00:07:13,240 And then the opportunity with judo Pro Cycling came up to kind 117 00:07:13,240 --> 00:07:16,280 of sit back in that more holistic kind of space. 118 00:07:16,280 --> 00:07:20,120 So working with the physical and technical components of cycling, 119 00:07:20,120 --> 00:07:25,320 which is where I kind of see myself really as as a scientist, 120 00:07:25,320 --> 00:07:28,160 like not as a as an engineer, not as a physiologist, but 121 00:07:28,160 --> 00:07:30,560 really as a scientist. You can kind of, you know, make 122 00:07:30,560 --> 00:07:33,720 experiments, understand A versus B, and then find the right 123 00:07:33,720 --> 00:07:36,480 people with the X-Men team knowledge to kind of drive 124 00:07:36,480 --> 00:07:40,240 things forward. In terms of the team, it's a 125 00:07:40,240 --> 00:07:42,040 really, it's a really interesting story. 126 00:07:42,480 --> 00:07:46,440 It's was really born out of a team called Swiss Racing 127 00:07:46,440 --> 00:07:49,240 Academy. So there was a team in the past, 128 00:07:49,240 --> 00:07:52,320 a continental level team, which is like the third tier basically 129 00:07:52,320 --> 00:07:56,840 of cycling that was there to encourage Swiss riders to be 130 00:07:56,840 --> 00:07:58,480 able to make it professional basically. 131 00:07:58,480 --> 00:08:02,120 So it was a team that was made, so they had basic conditions to 132 00:08:02,120 --> 00:08:06,400 race, to have a salary, to have bikes, and that has been there 133 00:08:06,400 --> 00:08:09,720 for many years and was really kind of a successful pathway for 134 00:08:09,720 --> 00:08:11,920 Swiss riders to get into professional cycling. 135 00:08:12,440 --> 00:08:17,120 And in 2022, essentially that was going to close. 136 00:08:17,120 --> 00:08:21,320 So they struggled to gain their funding and it happened at a 137 00:08:21,320 --> 00:08:23,400 really difficult point in terms of timing. 138 00:08:23,800 --> 00:08:27,640 And basically, the guys who were left on that team were not going 139 00:08:27,640 --> 00:08:29,800 to be able to find another team because all the teams were 140 00:08:29,800 --> 00:08:32,240 fulfilled. And then the owner of our team, 141 00:08:32,240 --> 00:08:36,120 Fabian, Fabian Kanchalara, who's a very famous and successful 142 00:08:36,120 --> 00:08:40,400 cyclist from, from Switzerland, really saw this opportunity as 143 00:08:40,840 --> 00:08:43,640 really saving, you know, the opportunity and careers of 144 00:08:43,640 --> 00:08:46,200 these, these young Swiss riders. And he put himself in their 145 00:08:46,200 --> 00:08:49,280 shoes and said, well, if I don't step in and, and give them this 146 00:08:49,280 --> 00:08:52,520 chance to, to ride, like what's going to happen to their career? 147 00:08:52,880 --> 00:08:55,360 And that's really the, the start of that process. 148 00:08:56,760 --> 00:09:00,280 Then he found out pretty quickly, you need sponsorship, 149 00:09:00,280 --> 00:09:03,560 you need help, you need support. And that's where Tudor came in. 150 00:09:04,040 --> 00:09:07,200 Tudor being the, the watch brand, part of the Hans Weld off 151 00:09:07,200 --> 00:09:11,840 foundation with Rolex as the main sponsor of, of the team. 152 00:09:12,240 --> 00:09:15,360 And that started in 2022. And now we're we're going into 153 00:09:15,360 --> 00:09:19,280 our third year of being a Tudor Pro Cycling really, which is 154 00:09:20,280 --> 00:09:21,560 it's gone from strength to strength. 155 00:09:21,560 --> 00:09:25,840 We're a pro team, so second tier technically, but with like a 156 00:09:25,840 --> 00:09:28,320 world tour mindset. So we really see ourselves 157 00:09:28,320 --> 00:09:31,280 growing towards being one of the biggest teams in the world. 158 00:09:31,680 --> 00:09:35,800 And we're investing now in the kind of future of the team. 159 00:09:35,840 --> 00:09:37,400 We have a really long term vision. 160 00:09:38,040 --> 00:09:40,560 We invest in the staff, we invest in the people, we invest 161 00:09:40,560 --> 00:09:43,600 in the science really because we know long term that's what's 162 00:09:43,600 --> 00:09:48,520 going to make us at the highest level in the sport great. 163 00:09:49,200 --> 00:09:54,880 Yeah, and I suppose at least from, from myself watching it, 164 00:09:54,880 --> 00:10:00,320 Tudor's definitely seen as one of the top teams that potential 165 00:10:00,320 --> 00:10:03,280 will get, you know, promoted, I guess, you know, in the in the 166 00:10:03,280 --> 00:10:06,520 coming years and gets the invitations to the to the sort 167 00:10:06,520 --> 00:10:10,080 of Grand Tours. So I guess to many people who 168 00:10:10,080 --> 00:10:12,560 are not deep into sport, you may people may not know the 169 00:10:12,560 --> 00:10:14,800 difference between the second tier and the top tier because 170 00:10:15,320 --> 00:10:17,880 Tudor tends to be in actually quite a few of the big races 171 00:10:17,880 --> 00:10:21,880 anyway. But you know, before maybe we 172 00:10:21,880 --> 00:10:25,640 get into some of the more detailed topics, what you know, 173 00:10:25,640 --> 00:10:28,480 what's it like working for a team? 174 00:10:28,480 --> 00:10:30,720 I imagine it's a bit like Formula One where there's a 175 00:10:30,720 --> 00:10:34,240 difference between, you know, the races, you know, the Lewis 176 00:10:34,240 --> 00:10:37,880 Hamiltons and the Julian Anna Philippe's now and the team 177 00:10:37,880 --> 00:10:40,160 behind. So what what does it look like 178 00:10:40,160 --> 00:10:43,400 to to work for a pro team? You know, like a typical week, 179 00:10:43,600 --> 00:10:47,040 you know, how much are you at the races versus back at testing 180 00:10:47,040 --> 00:10:50,360 places in factories, just to give a sense. 181 00:10:51,040 --> 00:10:53,680 Yeah, yeah. No, I'd say the first thing is 182 00:10:53,680 --> 00:10:57,280 it's not very typical. So it's, it's one of them 183 00:10:57,280 --> 00:11:00,160 industries where especially my role kind of as as head of 184 00:11:00,160 --> 00:11:02,800 innovation, it really sits across, you know, many different 185 00:11:02,800 --> 00:11:07,480 disciplines and, and yeah, with with the first thing really with 186 00:11:07,480 --> 00:11:09,400 cyclists, the season is so, so big. 187 00:11:09,440 --> 00:11:13,280 So we race from the middle of January until the end of 188 00:11:13,280 --> 00:11:16,360 October. So we can be racing at three 189 00:11:16,560 --> 00:11:20,560 races on the same day all across Europe and even across the 190 00:11:20,560 --> 00:11:22,520 world. So it's a big logistical 191 00:11:22,520 --> 00:11:24,840 challenge first of all, where where everything occurs. 192 00:11:25,920 --> 00:11:30,120 We race roughly around 250 days a year in that period. 193 00:11:30,120 --> 00:11:34,080 So it's quite a lot of time on the ground that's obviously 194 00:11:34,080 --> 00:11:37,840 without the preparation before, after logistics and things like 195 00:11:37,840 --> 00:11:40,080 that. So that during that period 196 00:11:40,080 --> 00:11:43,120 really most of the time is focused on delivery of race 197 00:11:43,120 --> 00:11:44,560 delivery of performance delivery. 198 00:11:44,560 --> 00:11:48,280 So a lot of my support then is about optimization of setups, 199 00:11:48,280 --> 00:11:51,880 making sure that all the work we've done is executed. 200 00:11:51,960 --> 00:11:54,880 We, we have a really big push on, on the application of 201 00:11:54,880 --> 00:11:56,560 innovation. I think is really important 202 00:11:56,560 --> 00:11:59,480 because we can do a lot of, you know, really cool things, but 203 00:11:59,480 --> 00:12:02,200 actually to get them to be applied at the right time with 204 00:12:02,200 --> 00:12:05,760 the right people in the right races is massive when you can 205 00:12:05,760 --> 00:12:08,440 have 3 or 4 races going on on the same day. 206 00:12:08,920 --> 00:12:10,880 So that's a big push during the season. 207 00:12:10,920 --> 00:12:14,720 We still have our innovation team that runs basically 24/7 208 00:12:14,720 --> 00:12:18,280 throughout the season as well. So we have a setup based in 209 00:12:18,280 --> 00:12:21,720 Silverstone. We have 4 full time engineers, 210 00:12:22,520 --> 00:12:26,120 we have a PhD student, we have an industrial designer, all 211 00:12:26,120 --> 00:12:28,480 working on technological development. 212 00:12:28,480 --> 00:12:32,400 So we look at all the strands which we can approach really and 213 00:12:32,400 --> 00:12:35,600 we move them forward. And we have 3 strategic themes 214 00:12:35,600 --> 00:12:38,440 with all our innovation. So we look from aerodynamics 215 00:12:38,440 --> 00:12:41,040 because we know that's the biggest force that we overcome 216 00:12:41,160 --> 00:12:43,880 as a cyclist. We look from thermal because we 217 00:12:43,880 --> 00:12:46,360 know thermal challenges are really, really important. 218 00:12:46,880 --> 00:12:49,720 And then we look from safety. So everything that we do, we 219 00:12:49,720 --> 00:12:52,480 always try and say, can we make it faster or economically, can 220 00:12:52,480 --> 00:12:54,520 we understand the thermal properties and can we ultimately 221 00:12:54,520 --> 00:12:59,000 make it safer for the riders going into race and competition. 222 00:12:59,400 --> 00:13:02,600 And that can be if we're in the wind tunnel testing, it can be 223 00:13:02,640 --> 00:13:05,720 if we're doing fabric testing in the wind tunnel, whole system 224 00:13:05,920 --> 00:13:07,560 testing. How are we doing bike 225 00:13:07,560 --> 00:13:09,560 development? How are we doing CFD 226 00:13:09,560 --> 00:13:11,960 simulations? Are we doing velodrome testing? 227 00:13:11,960 --> 00:13:15,120 Are we in the field, doing in the field measures of rolling 228 00:13:15,120 --> 00:13:19,800 resistance or tire development? Are we working with academic or 229 00:13:19,800 --> 00:13:21,520 industry partners on different projects? 230 00:13:21,520 --> 00:13:25,200 So it's really varied depending on what we have going on at that 231 00:13:25,200 --> 00:13:27,560 point in time. Yeah, I always find this 232 00:13:27,560 --> 00:13:32,720 fascinating, and I guess This is why so many people I know have 233 00:13:32,720 --> 00:13:37,080 this love of cycling who also tend to be into things like 234 00:13:37,080 --> 00:13:39,400 Formula One, because the technology is such an 235 00:13:39,400 --> 00:13:43,680 interesting part of it. But you mentioned something 236 00:13:43,680 --> 00:13:46,640 about the thermal side and that's something that I 237 00:13:47,080 --> 00:13:52,240 personally wasn't as familiar with until I personally did the 238 00:13:52,240 --> 00:13:54,440 attack the Tour in like very hot temperatures. 239 00:13:54,480 --> 00:13:57,320 I was like, OK, thermal does actually make a lot of 240 00:13:57,320 --> 00:13:59,040 difference. So maybe could you explain a 241 00:13:59,040 --> 00:14:02,120 little bit more because I think this may actually be useful for 242 00:14:02,120 --> 00:14:04,560 day-to-day cyclists who are doing things. 243 00:14:04,800 --> 00:14:10,240 What sort of technology or learnings do you get about 244 00:14:10,360 --> 00:14:13,600 cycling in sort of more extreme conditions over, you know, very 245 00:14:13,600 --> 00:14:16,920 hot or very, very cold? But how does that influence the 246 00:14:16,920 --> 00:14:20,200 performance of a cyclist? Yeah, it's a really good 247 00:14:20,200 --> 00:14:23,840 question and it's something we see more and more is integral to 248 00:14:23,840 --> 00:14:27,960 the performance. I think that too are very 249 00:14:27,960 --> 00:14:30,080 different, you know, scenarios and situations. 250 00:14:30,320 --> 00:14:34,320 If we look at hot weather, we know that in Europe, from 251 00:14:34,600 --> 00:14:40,240 probably May until the end of August, it can be 3540° in some 252 00:14:40,240 --> 00:14:43,800 races, which we know is a really extreme environment. 253 00:14:44,120 --> 00:14:46,960 And we also know that the riders are getting fitter and stronger, 254 00:14:46,960 --> 00:14:49,200 which means they're putting out more power outputs, which 255 00:14:49,200 --> 00:14:51,040 ultimately means they're putting out more heat as well. 256 00:14:51,040 --> 00:14:53,920 Because yeah, what you see on the pedals is actually probably 257 00:14:53,920 --> 00:14:56,680 only 1/4 of the energy that's actually produced. 258 00:14:56,680 --> 00:14:59,080 The other 3/4 of that is thermal energy as well. 259 00:14:59,080 --> 00:15:02,160 So we know that you have these guys sitting in really hot 260 00:15:02,160 --> 00:15:05,880 environments making a lot of thermal energy, and something 261 00:15:05,920 --> 00:15:07,920 has to give. And ultimately that is 262 00:15:07,960 --> 00:15:10,480 performance. You know, we see more and more 263 00:15:10,480 --> 00:15:13,040 that it can be so critical to performance. 264 00:15:13,040 --> 00:15:17,040 If you overheat, things start to shut down, your body protects 265 00:15:17,040 --> 00:15:19,760 you from that and ultimately performance is part of a 266 00:15:20,040 --> 00:15:22,640 consequence of that. So we try and do a lot of 267 00:15:22,640 --> 00:15:28,320 research around heat. We do probably a few different 268 00:15:28,320 --> 00:15:30,480 strands. So we do kind of prevention and 269 00:15:30,480 --> 00:15:32,040 preparation. I would say so. 270 00:15:32,560 --> 00:15:35,120 We train the riders to tolerate heat demands. 271 00:15:35,120 --> 00:15:38,760 We know that that is a trainable stimulus like getting fitter. 272 00:15:39,000 --> 00:15:40,480 You can also tolerate heat better. 273 00:15:40,480 --> 00:15:43,280 You get changes with your sweat response, you get changes with 274 00:15:43,280 --> 00:15:46,800 plasma volume, you get these physiological changes which 275 00:15:46,800 --> 00:15:49,280 allow you to to basically deal better with the heat. 276 00:15:50,840 --> 00:15:53,440 So we do a lot of that preparation and we've seen more 277 00:15:53,440 --> 00:15:55,520 and more in cycling. That is probably the thing 278 00:15:55,520 --> 00:15:58,520 that's really increased a lot in the last year's research around 279 00:15:58,520 --> 00:16:01,480 that area, understanding of that area, understanding the 280 00:16:01,480 --> 00:16:03,880 transients responses that can be done there. 281 00:16:03,880 --> 00:16:07,840 And then we also see we do a lot of prevention stuff. 282 00:16:07,840 --> 00:16:11,040 So we look at precooling. Can we bring down the 283 00:16:11,040 --> 00:16:13,560 temperature prior or even during exercise? 284 00:16:13,560 --> 00:16:16,160 Can we create a bigger thermal sink so that we know there's 285 00:16:16,160 --> 00:16:19,160 just more room to drive heat into? 286 00:16:20,360 --> 00:16:22,200 And there's lots of great researchers in that area. 287 00:16:22,200 --> 00:16:24,760 We work with partners quite a lot on on that. 288 00:16:25,480 --> 00:16:28,760 We do a lot of work around fabrics and helmet design and 289 00:16:28,760 --> 00:16:32,360 things like that to understand convective cooling and, and 290 00:16:32,760 --> 00:16:35,400 material components and properties to really help with 291 00:16:35,440 --> 00:16:37,320 with that. And we're doing a lot of work 292 00:16:37,320 --> 00:16:40,720 around UV radiation because we know also this, you know, the 293 00:16:40,720 --> 00:16:43,480 radiative effect of sun as well and things like that. 294 00:16:43,480 --> 00:16:46,560 So there's definitely a lot of work to be done from a heat 295 00:16:46,560 --> 00:16:49,320 perspective to really allow athletes to perform in innate 296 00:16:49,320 --> 00:16:52,080 conditions. But like you said, also in the 297 00:16:52,080 --> 00:16:53,960 cold, it's something we see more and more. 298 00:16:53,960 --> 00:16:55,960 You know, some of the biggest one day races in the world, 299 00:16:55,960 --> 00:16:59,080 they're in Belgium in the middle of March and April. 300 00:16:59,760 --> 00:17:02,040 And I can tell you now from being there first hand, you want 301 00:17:02,040 --> 00:17:05,599 every layer of clothing you have on possible because their 302 00:17:05,599 --> 00:17:07,640 conditions can be really quite harsh. 303 00:17:07,640 --> 00:17:10,760 And that's something we also know if riders get cold, if they 304 00:17:10,760 --> 00:17:14,160 get wet, it also has a massive detriment on their performance. 305 00:17:14,160 --> 00:17:18,599 So it's something we work on quite a lot to also understand 306 00:17:19,040 --> 00:17:21,800 what can we do from a material perspective, from an 307 00:17:21,800 --> 00:17:26,280 intervention perspective, How do we do the logistics around that? 308 00:17:26,280 --> 00:17:28,840 You know, there's so many things that ultimately come back to 309 00:17:28,840 --> 00:17:30,200 logistics. How do you make sure you 310 00:17:30,200 --> 00:17:33,320 potentially have hot bottles that are available on the course 311 00:17:33,320 --> 00:17:37,360 when the whole peloton is strung out over over a few kilometres 312 00:17:37,360 --> 00:17:40,960 or doing clothing development to understand how to, you know, 313 00:17:40,960 --> 00:17:45,600 improve breathability or insulation in them in in them a 314 00:17:45,600 --> 00:17:48,240 harsh environment. So yeah, we really try and do 315 00:17:48,240 --> 00:17:52,120 quite a lot of work around that to understand what's going on. 316 00:17:52,720 --> 00:17:55,280 And I think on top of that, just something we've generally been 317 00:17:55,280 --> 00:17:58,360 doing with the team is we do a lot of work to understand real 318 00:17:58,360 --> 00:18:00,720 world conditions. So it's something that's been a 319 00:18:00,840 --> 00:18:04,040 big project that we do around everything is we have all these 320 00:18:04,040 --> 00:18:06,960 tools and techniques to, you know, to simulate in science. 321 00:18:06,960 --> 00:18:10,800 We try and take out the variables to to get answers, but 322 00:18:10,800 --> 00:18:14,160 we're trying to also understand how we tune them variables to 323 00:18:14,160 --> 00:18:15,440 understand things moving forward. 324 00:18:15,440 --> 00:18:19,600 So thermal being a massive piece, but yeah, your wind 325 00:18:20,160 --> 00:18:22,400 turbulence intensities, all these different things we're 326 00:18:22,400 --> 00:18:25,440 trying to understand so we can really make more informed 327 00:18:25,440 --> 00:18:28,560 decisions with the tools we use and the data that we drive out 328 00:18:28,560 --> 00:18:29,960 through our through our techniques. 329 00:18:31,120 --> 00:18:37,360 And maybe linked to that then, So what about, you know, we've 330 00:18:37,480 --> 00:18:40,360 seen a lot of people now tracking and I think there's 331 00:18:40,360 --> 00:18:46,960 some brand names that are shown on certain TV show commentary, 332 00:18:46,960 --> 00:18:49,120 you know, where they talk about their recovery, their sleep 333 00:18:49,120 --> 00:18:51,640 recovery and nutrition, things like that. 334 00:18:51,640 --> 00:18:57,000 How much of that do you think has contributed or maybe here's 335 00:18:57,000 --> 00:18:58,160 the big, here's the big question. 336 00:18:58,800 --> 00:19:02,760 You look at the current riders and look at them breaking 337 00:19:02,760 --> 00:19:06,200 records and and seeming to go faster and faster. 338 00:19:07,200 --> 00:19:12,600 How much of that do you think is down to bike technology? 339 00:19:13,280 --> 00:19:22,320 So aerodynamics, how much of it is down to training and how much 340 00:19:22,320 --> 00:19:26,880 of it is down to things like nutrition and sleep? 341 00:19:27,000 --> 00:19:30,720 Like what? Do you see them all equal or do 342 00:19:30,720 --> 00:19:34,400 you think some have are more important than others? 343 00:19:35,200 --> 00:19:40,200 Yeah, I think they've all played their part in improving cycling 344 00:19:40,200 --> 00:19:42,000 over the last kind of 10 years, I would say. 345 00:19:42,000 --> 00:19:46,680 I mean, taking them individually, nutrition has been 346 00:19:46,680 --> 00:19:51,040 a massive driver for sure. If you look at where cycling was 347 00:19:51,040 --> 00:19:53,920 10 years ago and where it is now in terms of definitely all the 348 00:19:53,920 --> 00:19:57,720 research around carbohydrate intake, how to increase uptake, 349 00:19:57,720 --> 00:20:01,760 how to understand fueling, that's dramatically changed. 350 00:20:01,760 --> 00:20:04,240 And that we really know has helped drive performance 351 00:20:04,240 --> 00:20:05,720 forward. Because if you can have more 352 00:20:05,720 --> 00:20:08,320 carbohydrate availability and you can oxidize more 353 00:20:08,320 --> 00:20:10,320 carbohydrate, you can generate more energy. 354 00:20:10,320 --> 00:20:15,040 And I think that has been a, a big push with performance. 355 00:20:15,960 --> 00:20:18,960 And I think you see now that the training volumes that are able 356 00:20:18,960 --> 00:20:22,960 to be sustained the the physical level within racing and and just 357 00:20:22,960 --> 00:20:24,880 what you see mainly under fatigue. 358 00:20:24,920 --> 00:20:27,240 I think that's the biggest thing that we've really seen a shift 359 00:20:27,240 --> 00:20:30,560 is. Not only the fresh capacity of 360 00:20:30,560 --> 00:20:32,960 riders, but what they can do after four or five, six hours, 361 00:20:32,960 --> 00:20:35,760 what they can do after days, weeks of stage racing. 362 00:20:36,120 --> 00:20:38,880 I think that a lot of that is down to really optimizing 363 00:20:38,880 --> 00:20:41,320 nutrition. And you can see even since I've 364 00:20:41,320 --> 00:20:44,520 been working in professional cycling, the investment from 365 00:20:44,520 --> 00:20:47,000 teams around the area. You know, we have two 366 00:20:47,000 --> 00:20:52,920 nutritionists, we have 4 chefs, we have a food truck, we have 367 00:20:53,520 --> 00:20:56,400 nutrition sponsors, we have nutrition partners, we have 368 00:20:56,400 --> 00:20:59,880 academic nutrition partners. We have data scientists that 369 00:20:59,880 --> 00:21:03,000 look at all the data that we generate around nutrition. 370 00:21:03,000 --> 00:21:05,440 Actually, you know, we measure hydration status. 371 00:21:05,440 --> 00:21:10,440 We look at energy expenditure to make sure that we match on a day 372 00:21:10,440 --> 00:21:14,080 on day, on a meal, on meal basis across, you know, a Grand Tour 373 00:21:14,080 --> 00:21:16,040 for instance. And a lot of that has really 374 00:21:16,040 --> 00:21:17,560 helped drive performance forward. 375 00:21:17,560 --> 00:21:22,720 We see riders can train more, get sick less and perform much 376 00:21:22,720 --> 00:21:24,160 better, especially under fatigue. 377 00:21:24,160 --> 00:21:26,680 And a lot of that I think is down to nutrition over the last 378 00:21:26,680 --> 00:21:32,920 10 years, definitely aerodynamics and equipment 379 00:21:32,920 --> 00:21:34,400 development has moved forward a lot. 380 00:21:34,600 --> 00:21:37,960 You know, I think there was some teams early on that kind of 381 00:21:37,960 --> 00:21:40,600 clicked this. And I think, yeah, you know, it 382 00:21:40,600 --> 00:21:43,600 started really on the track. I think if you look at equipment 383 00:21:43,600 --> 00:21:45,960 development and where you see performance, I think British 384 00:21:45,960 --> 00:21:48,520 Cycling were kind of the the real front runners of that from 385 00:21:48,880 --> 00:21:51,560 probably 2000 and four, 2008 onwards on the track. 386 00:21:51,560 --> 00:21:54,800 And then they're starting to understand the physics involved. 387 00:21:55,240 --> 00:21:58,160 And as you know, there's such massive potential there. 388 00:21:58,160 --> 00:22:02,240 The rider is, you know, 80% of probably the drag in the system. 389 00:22:02,240 --> 00:22:05,320 And then what you wrap the rider in is a big part of that as 390 00:22:05,320 --> 00:22:06,840 well. So it's there's a lot of 391 00:22:06,840 --> 00:22:10,720 opportunities there that are now starting to be more and more 392 00:22:10,720 --> 00:22:12,880 understood. And we just see that the peloton 393 00:22:12,880 --> 00:22:17,560 just goes faster and faster. And for me, knowing the 394 00:22:17,560 --> 00:22:20,720 relationship between power and speed is, is cubic. 395 00:22:21,160 --> 00:22:24,200 It can't all come from power. You know, it's not that riders 396 00:22:24,200 --> 00:22:27,920 are all of a sudden getting to the, you know, to the cube more 397 00:22:27,920 --> 00:22:30,400 powerful, but actually the, you know, the, the demands are 398 00:22:30,400 --> 00:22:33,160 coming down as well because we're getting more aerodynamic. 399 00:22:33,160 --> 00:22:35,160 We're understanding that speed relationship. 400 00:22:35,920 --> 00:22:38,160 So that's been a big driver moving forward. 401 00:22:38,600 --> 00:22:41,240 And I'd say because of that, that's why as a team we're 402 00:22:41,240 --> 00:22:43,600 really, really focused on the safety part as well, because we 403 00:22:43,600 --> 00:22:47,240 just do so much, so many innovations to make our riders 404 00:22:47,240 --> 00:22:50,240 faster, fit and stronger, but we're also then putting them at 405 00:22:50,240 --> 00:22:52,240 more risk. You know, if you can go down, if 406 00:22:52,240 --> 00:22:55,360 you can go down climbs 10K an hour faster now, if you can take 407 00:22:55,360 --> 00:22:58,680 corners faster, if you can do this faster, that faster, we 408 00:22:58,680 --> 00:23:00,240 should also look after the riders more. 409 00:23:00,240 --> 00:23:03,320 So that's really why every innovation we do, we also take 410 00:23:03,320 --> 00:23:05,520 on that responsibility to make sure that we try and keep them 411 00:23:05,520 --> 00:23:08,600 safe as well. And I think, yeah, every team 412 00:23:08,720 --> 00:23:10,200 should do that. But we take that really 413 00:23:10,200 --> 00:23:14,720 seriously at Tudor Pro Cycling. Yeah, that's a very, yeah. 414 00:23:14,720 --> 00:23:16,800 There's definitely a sort of hot topic, isn't it, on the 415 00:23:18,040 --> 00:23:20,520 equipment versus the rider versus everything. 416 00:23:20,520 --> 00:23:23,760 It's, yeah, one I guess you could dedicate an entire 417 00:23:24,200 --> 00:23:27,600 conversation to. But one thing I did on that 418 00:23:27,600 --> 00:23:33,800 point of maybe training, I was listening to Gary Thomas on, you 419 00:23:33,800 --> 00:23:37,440 know, on his podcast and I think he was talking with Pavel 420 00:23:37,440 --> 00:23:40,640 Sivakoff about like the different training and they were 421 00:23:40,640 --> 00:23:43,360 talking about the sort of Team Sky where they basically just 422 00:23:43,360 --> 00:23:50,440 starved themselves and and went out comparing to now Pavel was 423 00:23:50,440 --> 00:23:52,960 talking about the sort of zone 2. 424 00:23:53,920 --> 00:23:56,680 But I always thought it was surprising because I assume 425 00:23:56,680 --> 00:23:58,320 that, OK, all the team do that anyway. 426 00:23:58,320 --> 00:24:02,920 But it it sort of made clear that he was describing that 427 00:24:02,920 --> 00:24:06,080 there was they sent a lot of junk miles that people would 428 00:24:06,080 --> 00:24:07,440 just go out. And because they're chatting 429 00:24:07,440 --> 00:24:10,240 with mates and they're drafting and they're so strong, the 430 00:24:10,240 --> 00:24:13,600 riders that they were probably only in zone 1 where now they're 431 00:24:13,600 --> 00:24:15,840 trying. And he says he was, he almost 432 00:24:15,840 --> 00:24:18,720 starts just training on his own because it's it's impossible to 433 00:24:18,720 --> 00:24:20,480 do. Is that something that you've 434 00:24:20,480 --> 00:24:25,400 seen as well as a very recent shift towards this more rigorous 435 00:24:26,120 --> 00:24:31,080 focus on extracting the maximum amount of all the time you're on 436 00:24:31,080 --> 00:24:35,840 the bike? Yeah, it's really interesting 437 00:24:35,840 --> 00:24:38,800 with training methodologies, there's, there's many ways to do 438 00:24:38,800 --> 00:24:40,760 it. And I think the longer I've 439 00:24:40,760 --> 00:24:44,000 worked in professional cycling, the more I've realized that it's 440 00:24:44,000 --> 00:24:46,560 really tailoring it to each individual rider. 441 00:24:46,560 --> 00:24:49,560 That's the most important thing. And the reason I say that is 442 00:24:50,280 --> 00:24:53,280 it's, you know, they have the same demands, you know, 443 00:24:53,280 --> 00:24:54,840 relative. I mean, a sprinter's obviously 444 00:24:54,840 --> 00:24:57,000 different to a climber or a classics rider, but they're 445 00:24:57,000 --> 00:24:59,800 endurance cyclists first of all. So there's this key kind of 446 00:25:00,280 --> 00:25:02,840 physiological underpinning of what you're trying to achieve to 447 00:25:02,840 --> 00:25:04,960 and then you've got these specific components on top. 448 00:25:05,480 --> 00:25:08,560 But I think we're a lot of or where maybe even when I was 449 00:25:08,560 --> 00:25:13,520 younger, people see training as is, is as you're training the 450 00:25:13,520 --> 00:25:15,840 machine, you know, you have these inputs and you have an 451 00:25:15,840 --> 00:25:19,000 output. And what we know now more and 452 00:25:19,000 --> 00:25:21,840 more and what I know working with with humans is that the 453 00:25:21,840 --> 00:25:24,120 input you put in doesn't always necessarily end up being the 454 00:25:24,120 --> 00:25:26,160 output. And the reason being is that, 455 00:25:26,560 --> 00:25:29,640 you know, training is the one lever we can adjust as a coach 456 00:25:29,640 --> 00:25:31,440 or as someone working with in cycling. 457 00:25:31,840 --> 00:25:34,560 But what we can't adjust is the stress on their on their 458 00:25:34,560 --> 00:25:38,360 everyday life, their family, did they sleep well? 459 00:25:38,360 --> 00:25:42,160 What's their nutrition like? Are they happy? 460 00:25:42,160 --> 00:25:43,720 Are they depressed? There's all these different 461 00:25:43,720 --> 00:25:45,520 factors that go into a human being. 462 00:25:45,520 --> 00:25:48,960 And that what we understand more is that humans are very 463 00:25:48,960 --> 00:25:52,000 complicated systems. They're not just, they're not 464 00:25:52,000 --> 00:25:55,120 just individual inputs, but they have all this, these inputs 465 00:25:55,120 --> 00:25:56,920 actually interact with each other as well. 466 00:25:57,880 --> 00:26:02,440 And I think it's more about, I find tailoring the training 467 00:26:02,640 --> 00:26:04,720 relative to that. So you have your idea, you have 468 00:26:04,720 --> 00:26:07,800 your plan, you have your overall vision and goals and 469 00:26:07,800 --> 00:26:11,640 periodization, things like that. But it's been able to to tweak 470 00:26:11,640 --> 00:26:14,560 and tailor that relative to what's going on within that 471 00:26:14,560 --> 00:26:16,840 rider's life. Because, you know, you might 472 00:26:16,840 --> 00:26:18,920 have the best plan in the world, but if they're not eating 473 00:26:18,920 --> 00:26:22,320 properly or they're stressed at home, or, you know, they're 474 00:26:22,320 --> 00:26:24,480 running a second business on the side that you don't know about, 475 00:26:24,480 --> 00:26:27,240 then actually your optimal training might not be correct. 476 00:26:27,320 --> 00:26:30,320 Because, yeah, it's good on paper and it moves forward. 477 00:26:30,840 --> 00:26:33,680 And I would say every training methodology can have its 478 00:26:33,680 --> 00:26:36,320 benefits. It's something that I really 479 00:26:36,360 --> 00:26:39,320 reflected on quite a lot. Now, working in different 480 00:26:39,320 --> 00:26:41,960 environments and different teams, you see lots of different 481 00:26:41,960 --> 00:26:46,080 ways of achieving success. And ultimately I've seen things 482 00:26:46,080 --> 00:26:49,440 that, you know, maybe I wouldn't actually have done, but I've 483 00:26:49,440 --> 00:26:51,080 also seen them be very successful. 484 00:26:51,360 --> 00:26:55,960 And I've also started to, to, to learn and understand from, from 485 00:26:55,960 --> 00:26:58,600 them experiences that you can do things in many different ways. 486 00:26:59,960 --> 00:27:03,040 And yeah, some teams have certain philosophies and, and 487 00:27:03,040 --> 00:27:05,320 some riders go really, really well for them philosophies and 488 00:27:05,320 --> 00:27:08,520 other riders don't. And my philosophy is always to 489 00:27:08,520 --> 00:27:10,600 try and make the individual rider better. 490 00:27:10,760 --> 00:27:15,760 So I and I think when I look at kind of successful coaches or, 491 00:27:15,800 --> 00:27:18,800 or people that I really respect, it's the ones that make all 492 00:27:18,800 --> 00:27:20,640 their riders better, not just one. 493 00:27:20,800 --> 00:27:24,040 And I think that's where that individualisation, that 494 00:27:24,040 --> 00:27:27,480 communication with a rider, that understanding of where they're 495 00:27:27,480 --> 00:27:31,400 at and tailoring their training to them is stronger rather than 496 00:27:31,400 --> 00:27:34,640 just saying, OK, this is my training philosophy, we do it or 497 00:27:34,640 --> 00:27:37,400 or you don't. Yeah, that's a good point. 498 00:27:37,400 --> 00:27:40,360 And I guess this is what's, I guess maybe to people listening 499 00:27:40,360 --> 00:27:42,040 or to watching this who are into cycling. 500 00:27:42,040 --> 00:27:47,240 It's always the tricky thing because we there's always a 501 00:27:47,240 --> 00:27:52,240 temptation to follow a specific guide because you hear that 502 00:27:52,240 --> 00:27:58,840 somebody else does it, but you don't know whether should you 503 00:27:58,840 --> 00:28:01,440 just follow it and you just need to suck it up and just, you 504 00:28:01,440 --> 00:28:05,360 know, deal with the suffering, or is it just not well suited to 505 00:28:05,360 --> 00:28:09,680 you and you would be better doing something else? 506 00:28:09,680 --> 00:28:12,400 It's, you know, there's so much not misinformation, but there's 507 00:28:12,400 --> 00:28:14,800 so many different theories out there, isn't there, that it's 508 00:28:14,800 --> 00:28:20,240 hard for an amateur cyclist to really know what to follow. 509 00:28:21,360 --> 00:28:22,760 It's it's. Yeah, definitely. 510 00:28:22,760 --> 00:28:26,640 Sensationalized as well. I think so, especially when you, 511 00:28:26,760 --> 00:28:29,560 you know, you have a full time job and a family and and 512 00:28:29,560 --> 00:28:32,240 everything else and you're trying to do this as on the 513 00:28:32,240 --> 00:28:35,040 side, it is really difficult. You want to try and extract as 514 00:28:35,040 --> 00:28:38,520 much as you can out of it. And that's where I think it can 515 00:28:38,520 --> 00:28:41,040 be difficult because professional riders, they ride 516 00:28:41,040 --> 00:28:42,640 the bike, that's their full time job. 517 00:28:43,000 --> 00:28:45,520 And actually the other thing they can do is they can recover 518 00:28:45,520 --> 00:28:48,080 professionally. And a lot of amateurs can't do 519 00:28:48,080 --> 00:28:49,800 that. And I think that's the the 520 00:28:49,800 --> 00:28:53,000 challenge is you want to do what the pros are doing, but actually 521 00:28:53,000 --> 00:28:56,000 you can't do the recovery part. And we know that adaptations, 522 00:28:56,000 --> 00:28:57,480 they don't actually occur when you're on the bike. 523 00:28:57,480 --> 00:29:00,640 The stress happens then, but the adaptations happen afterwards. 524 00:29:00,640 --> 00:29:04,040 And if you can't have the adaptive processes, then maybe 525 00:29:04,040 --> 00:29:06,440 the training doesn't fulfill what you want it to achieve 526 00:29:06,440 --> 00:29:08,680 because you can't do the other proportion of that. 527 00:29:10,560 --> 00:29:12,640 Yeah, no, that, that makes complete sense. 528 00:29:13,720 --> 00:29:18,440 So what maybe going a little bit more into the, you know, the 529 00:29:18,440 --> 00:29:21,400 bike side of things. Where do you see the the sort of 530 00:29:21,400 --> 00:29:26,120 big performance areas nowadays? You know, is it, you know, in 531 00:29:26,120 --> 00:29:30,320 the bike, the fabric, you know, the tyre choice, you know, where 532 00:29:30,320 --> 00:29:34,720 some of the maybe interesting areas that that you think have 533 00:29:34,720 --> 00:29:37,480 led to some gains and maybe where are sort of future areas 534 00:29:37,480 --> 00:29:39,800 that people are starting to to explore now? 535 00:29:41,440 --> 00:29:44,000 I think the biggest thing you can look at really is, is the 536 00:29:44,000 --> 00:29:48,920 whole system approach. Like for me this is really 537 00:29:48,920 --> 00:29:52,600 critical looking at the rider and all their equipment as a 538 00:29:52,600 --> 00:29:55,800 whole system. The more kind of information or, 539 00:29:56,840 --> 00:29:59,280 or testing I've done, what you see is if you change one 540 00:29:59,280 --> 00:30:02,200 component of it, it's a cascade and everything else is 541 00:30:02,200 --> 00:30:05,480 interacting with that. And if you can't just say this 542 00:30:05,480 --> 00:30:08,320 helmet is fast, this skinsuit is fast, this bike is fast. 543 00:30:08,320 --> 00:30:11,560 It's in what context with what rider, with what demands. 544 00:30:11,560 --> 00:30:14,760 I think that that's the really kind of where I really see the 545 00:30:14,760 --> 00:30:18,680 innovation happening now on that individualized level, you know, 546 00:30:18,920 --> 00:30:22,480 because there is just such different demands on on them 547 00:30:22,480 --> 00:30:25,000 individual user cases. So, for instance, a sprinter, 548 00:30:25,000 --> 00:30:29,080 you know, we know sprinters go 7080 kilometers an hour in the 549 00:30:29,080 --> 00:30:32,440 final and we know they have to have very aggressive positions 550 00:30:32,440 --> 00:30:35,120 to try and put their heads in certain places. 551 00:30:35,120 --> 00:30:38,320 And we know because of all that, that we need to understand 552 00:30:38,320 --> 00:30:44,240 certain flow structures, certain stiffness, aerodynamics, we need 553 00:30:44,240 --> 00:30:47,800 to understand vision, we need to understand how all that 554 00:30:47,800 --> 00:30:50,400 interacts with each other. And we need to understand 555 00:30:50,520 --> 00:30:53,320 fabrics relative to that rider at them speeds. 556 00:30:54,040 --> 00:30:55,360 Whereas that is completely different. 557 00:30:55,360 --> 00:30:57,360 If you look at a climber, for instance, you know, the demands 558 00:30:57,360 --> 00:30:59,600 of a climber are going up, the climber probably coming down, 559 00:30:59,600 --> 00:31:02,720 the climber on the other side. And if we look at the whole 560 00:31:02,720 --> 00:31:05,600 system, the position, the orientation they're in, it's a 561 00:31:05,600 --> 00:31:08,960 completely different system. SO1 helmet is not going to be 562 00:31:09,640 --> 00:31:12,560 perfect for both. 1 skin suit's not going to be perfect for 563 00:31:12,560 --> 00:31:14,120 both. 1 bike's not going to be perfect for both. 564 00:31:14,120 --> 00:31:17,520 So I think what we'll see in the industry of cycling is long term 565 00:31:18,080 --> 00:31:20,120 is this individualization development. 566 00:31:20,120 --> 00:31:23,600 So can we build stuff on an individualized basis? 567 00:31:24,360 --> 00:31:27,240 Can manufacture methods cope with that? 568 00:31:27,240 --> 00:31:29,880 You know, can we find ways to really individualize it? 569 00:31:30,240 --> 00:31:33,920 And I think that's where we see real benefit in terms of the 570 00:31:34,000 --> 00:31:37,600 performance moving forward. Yeah, that is so interesting. 571 00:31:37,720 --> 00:31:41,320 I, I must admit that that sort of aligns to some of the 572 00:31:41,320 --> 00:31:44,760 findings that I found, you know, when I was working on some of 573 00:31:44,760 --> 00:31:48,600 the British Cycling stuff. It's almost an unbelievably 574 00:31:48,640 --> 00:31:53,040 complicated optimization problem because you know that the, the 575 00:31:53,040 --> 00:31:56,440 bike, the rider, the wheel, the helmet and you, what you really 576 00:31:56,440 --> 00:31:59,200 want to do is test every combination with every other 577 00:31:59,200 --> 00:32:03,360 combination. And then whereas I guess a lot 578 00:32:03,360 --> 00:32:06,800 of the time because of commercial reasons, partnership 579 00:32:06,800 --> 00:32:09,920 reasons, you're like, hey, helmet manufacturer 580 00:32:10,320 --> 00:32:15,520 independently just give me a good helmet, but you haven't 581 00:32:15,520 --> 00:32:18,440 been involved in that. So with that, what you're trying 582 00:32:18,440 --> 00:32:22,320 to say that you're trying to be more involved with the partners 583 00:32:22,320 --> 00:32:25,040 so they can, so you're not just buying off the shelf something 584 00:32:25,040 --> 00:32:27,920 they've made, but potentially it's a little bit more aligned 585 00:32:28,240 --> 00:32:32,000 to your needs and how that interacts with the other bits 586 00:32:32,000 --> 00:32:34,320 you have. Yeah, 100%. 587 00:32:34,320 --> 00:32:36,720 It's something we've really driven forward in the last years 588 00:32:36,720 --> 00:32:38,160 and it's still a continual process. 589 00:32:38,160 --> 00:32:42,160 But we have what we call like reciprocal relationships with 590 00:32:42,160 --> 00:32:44,400 our partners. So we really make sure that when 591 00:32:44,400 --> 00:32:46,920 we select our partners, their partners that want to go on this 592 00:32:46,920 --> 00:32:50,520 innovation process with us because it's not easy, you know, 593 00:32:50,800 --> 00:32:56,800 it costs money, time, effort and we're really, you know demanding 594 00:32:56,800 --> 00:32:59,360 of what we want. But we're also, which I think is 595 00:32:59,360 --> 00:33:02,280 quite unique, we also have the capacities in house to actually 596 00:33:02,720 --> 00:33:05,080 put time and resource towards them problems. 597 00:33:05,320 --> 00:33:07,560 So it's not that we just knock on the door of our partner and 598 00:33:07,560 --> 00:33:09,880 say, OK, we want a new bike or a new helmet. 599 00:33:09,960 --> 00:33:11,880 We say no, we want to go on this project with you. 600 00:33:11,880 --> 00:33:14,440 We understand the demands that we're aiming towards. 601 00:33:14,720 --> 00:33:18,360 Let's do it in a collaboration. So, you know, a perfect example 602 00:33:18,360 --> 00:33:22,400 could be when we were developing a new helmet and we were 603 00:33:22,400 --> 00:33:26,440 developing a new helmet with a, with a new partner and we had 604 00:33:26,520 --> 00:33:29,400 wind tunnel trips happening in, in, in their location. 605 00:33:29,400 --> 00:33:31,920 Wind tunnel trips with our, with ourselves in the UK. 606 00:33:31,920 --> 00:33:34,960 We had riders there, we had 3D peddling mannequins. 607 00:33:34,960 --> 00:33:38,880 We did simulation, we did all these collaboration approaches, 608 00:33:38,920 --> 00:33:43,760 thermal fit development over over over a long period of time 609 00:33:43,760 --> 00:33:46,520 to really make sure that the initial product we had was as 610 00:33:46,720 --> 00:33:48,480 evolved as possible in the time we had. 611 00:33:49,560 --> 00:33:52,400 And yeah, and we continue to try and do that across all the 612 00:33:52,400 --> 00:33:56,680 things you said, the bike, the tires, the wheels, the clothing. 613 00:33:56,680 --> 00:33:59,880 It's something that we're taking ownership of internally as a 614 00:33:59,880 --> 00:34:01,960 cycling team. And I think that's quite 615 00:34:01,960 --> 00:34:05,400 different to maybe many other cycling teams is we invest 616 00:34:05,400 --> 00:34:08,760 resource in that. You know, we have engineers, we 617 00:34:08,760 --> 00:34:13,800 have an industrial designer, we have fabric experts in house 618 00:34:13,800 --> 00:34:18,000 that complement the expertise of our partners to really make sure 619 00:34:18,000 --> 00:34:21,080 that there's investment from our side to to tailor the products 620 00:34:21,080 --> 00:34:23,920 to exactly what we need. So we really start to understand 621 00:34:23,920 --> 00:34:28,800 that and move it forward and we see that that will really be our 622 00:34:30,080 --> 00:34:32,639 way of moving forward and, and being at the forefront and it 623 00:34:32,639 --> 00:34:35,600 takes time, but I think it's the right way to do it. 624 00:34:35,600 --> 00:34:40,000 Investing in that innovation process is where we see really 625 00:34:40,000 --> 00:34:42,239 critical to to our performances in the future. 626 00:34:43,320 --> 00:34:51,920 And how easy or difficult is it or a barrier to get the riders 627 00:34:51,920 --> 00:34:55,280 involved because you've said at the same time they're off doing 628 00:34:55,760 --> 00:34:59,880 6070 race days or however long some of them do, How easy is it 629 00:34:59,880 --> 00:35:02,920 to get them to come, you know, to a test or to go? 630 00:35:02,920 --> 00:35:05,920 Is that a limiting factor sometimes? 631 00:35:07,040 --> 00:35:09,000 Yeah, there's a few things to that. 632 00:35:09,040 --> 00:35:12,640 I think the first thing we do is whenever we speak to new riders, 633 00:35:12,640 --> 00:35:16,160 we always tell them about our process, that we're, you know, 634 00:35:16,160 --> 00:35:20,400 we're an innovative team, that we take risks, that we push the 635 00:35:20,400 --> 00:35:22,240 boundaries on these things. And that ultimately that 636 00:35:22,240 --> 00:35:24,560 requires investment of time as well. 637 00:35:24,920 --> 00:35:27,800 And you know, for some riders, maybe that's not what they want 638 00:35:27,840 --> 00:35:30,840 from their cycling team. And therefore it's a 639 00:35:30,840 --> 00:35:33,720 conversation to have early on to set expectations. 640 00:35:34,440 --> 00:35:39,240 But we've also realized as we move forward that still it's, 641 00:35:39,280 --> 00:35:42,360 you know, it's impractical to expect riders to be available 642 00:35:42,400 --> 00:35:44,480 24/7 for the, for these learnings. 643 00:35:44,800 --> 00:35:46,680 So what we really try and do is we try and leverage 644 00:35:46,680 --> 00:35:48,920 methodologies that allow us to do a lot of the stuff 645 00:35:48,920 --> 00:35:51,480 beforehand. So we do a lot of simulation. 646 00:35:51,480 --> 00:35:54,600 We have 3D scans of the majority of our riders. 647 00:35:55,960 --> 00:35:57,960 So we can do a lot of digitalization. 648 00:35:57,960 --> 00:35:59,920 So we can do a lot of CFD computation. 649 00:35:59,920 --> 00:36:04,280 We can do a lot of clothing optimization fit, we can do a 650 00:36:04,280 --> 00:36:07,960 lot of understanding external to them even being needed. 651 00:36:08,760 --> 00:36:11,680 We also create mannequins and we have mannequins of, you know, 652 00:36:12,080 --> 00:36:14,440 our higher priority riders peddling mannequins that allow 653 00:36:14,440 --> 00:36:17,080 us to go to the wind tunnel and test things without them being 654 00:36:17,080 --> 00:36:19,320 there. So we have really high 655 00:36:19,320 --> 00:36:22,600 repeatability methods. You know, it's also what we find 656 00:36:22,600 --> 00:36:26,680 is with riders, I'm sure anyone working in with humans and doing 657 00:36:26,680 --> 00:36:29,360 testing, as you see that it's really difficult to get reliable 658 00:36:29,360 --> 00:36:33,000 data because naturally you're a human, you get tired, you get 659 00:36:33,000 --> 00:36:35,560 hungry. Whereas if you have a mannequin, 660 00:36:35,560 --> 00:36:38,240 you can run them for 10 hours a day and get ready for 661 00:36:38,240 --> 00:36:39,840 repeatability and not have to feed them. 662 00:36:39,840 --> 00:36:43,000 So it gives you a lot more scope and capacity to do that work. 663 00:36:43,440 --> 00:36:45,600 But there always needs to be a validation step and that's 664 00:36:45,600 --> 00:36:47,600 really important. We always make sure that all the 665 00:36:47,600 --> 00:36:51,640 work we're doing loops back to either field testing or some 666 00:36:51,640 --> 00:36:56,080 kind of simulation tool, be it wind tunnel track testing in the 667 00:36:56,080 --> 00:36:59,560 field to validate the findings that we find from doing all this 668 00:36:59,560 --> 00:37:02,800 kind of in detailed research. And for sure that costs time 669 00:37:02,800 --> 00:37:06,000 from the riders. But we try and educate our 670 00:37:06,000 --> 00:37:09,600 riders on why we're doing that. We, we empower them, we show 671 00:37:09,600 --> 00:37:11,360 them their data. You know, I think we're really 672 00:37:11,360 --> 00:37:14,360 open from that perspective. We, we give them that 673 00:37:14,360 --> 00:37:17,680 information so they understand, OK, we're asking you to do this 674 00:37:17,800 --> 00:37:20,280 and we've provided you this and this is the consequence. 675 00:37:20,640 --> 00:37:23,240 And for the majority of riders we work with, they're really 676 00:37:23,240 --> 00:37:26,760 involved in that process and they really understand it. 677 00:37:27,240 --> 00:37:29,320 I think it's one of the nice things with cycling. 678 00:37:29,960 --> 00:37:34,400 It's such a data rich sport that actually a lot of the cyclists 679 00:37:34,400 --> 00:37:36,280 understand, you know, they understand what's they 680 00:37:36,280 --> 00:37:39,400 understand what's savings, they understand speed gain. 681 00:37:39,400 --> 00:37:41,680 You know, they're even some of them, you know, they understand 682 00:37:41,680 --> 00:37:45,080 aerodynamics and they can quote you the equation for XYZ. 683 00:37:45,760 --> 00:37:48,920 And yeah, it's definitely something that's really powerful 684 00:37:48,920 --> 00:37:52,760 in cycling that that you can have that conversation and they 685 00:37:52,760 --> 00:37:55,080 know how hard they're trained to try and gain 10 watts. 686 00:37:55,080 --> 00:37:57,720 So when you can tell you can find it from something else that 687 00:37:57,720 --> 00:38:00,080 they're usually quite grateful and willing to invest that time 688 00:38:00,080 --> 00:38:03,160 in. It and do you see a shift 689 00:38:03,160 --> 00:38:06,160 between the younger riders who were just coming through from 690 00:38:06,160 --> 00:38:08,080 the development squads and the older riders? 691 00:38:08,080 --> 00:38:11,800 Is there a has has has all of this changed? 692 00:38:11,800 --> 00:38:15,160 The past 5-10 years meant that the younger riders are far more 693 00:38:15,240 --> 00:38:19,040 educated than maybe the the older generation are. 694 00:38:20,120 --> 00:38:22,720 Yeah, it's, that's a really, really good question. 695 00:38:22,720 --> 00:38:26,320 It's something that we we see quite a lot in many different 696 00:38:26,320 --> 00:38:29,600 ways. So I think generally the younger 697 00:38:29,600 --> 00:38:32,880 generation are a lot more, like you said, maybe educate on it 698 00:38:32,880 --> 00:38:35,800 and, and, and thoughtful of it, but I'd say sometimes also 699 00:38:35,800 --> 00:38:37,880 obsessed with it, which can be quite interesting. 700 00:38:37,920 --> 00:38:42,400 You know, it's sometimes they think it's a, it's a PlayStation 701 00:38:42,400 --> 00:38:45,680 game and, and you know, it's a laboratory and, and, and it's, 702 00:38:45,680 --> 00:38:48,800 you know, it's only this equation of numbers and, and, 703 00:38:48,800 --> 00:38:50,400 and clothing and equipment and things like that. 704 00:38:50,400 --> 00:38:52,480 And what you actually see is, you know, you've also got to 705 00:38:52,480 --> 00:38:56,000 make decisions within a race. You've also got to be able to 706 00:38:56,000 --> 00:38:59,240 tactically and technically be able to execute on a bike. 707 00:38:59,240 --> 00:39:03,200 And there are things that sometimes are often overlooked, 708 00:39:03,200 --> 00:39:05,280 you know, with the younger generation that that that's what 709 00:39:05,280 --> 00:39:08,560 also wins your bike races. It's not just all this physics, 710 00:39:08,560 --> 00:39:11,400 but actually there's a it's a sport and there's decisions and 711 00:39:12,120 --> 00:39:14,720 it just we had some really interesting talks with with 712 00:39:14,720 --> 00:39:17,200 Julianne. Like Julianne is a has joined 713 00:39:17,200 --> 00:39:20,280 the team recently and historically, you know, he's not 714 00:39:20,280 --> 00:39:23,160 a man who's obsessed with data or or insights something for 715 00:39:23,160 --> 00:39:24,360 that. He's a guy who wants to race his 716 00:39:24,360 --> 00:39:28,040 bike, but he also understands the value of it and he trusts 717 00:39:28,040 --> 00:39:30,640 that if we say, OK, we're going to do XYZ, we're going to try to 718 00:39:30,640 --> 00:39:33,320 prove it, that we're working on that in the background, you 719 00:39:33,320 --> 00:39:34,600 know, and he's really open to that. 720 00:39:34,640 --> 00:39:37,360 But that was one of the things that was really important when 721 00:39:37,360 --> 00:39:39,560 he joined the team that we do this stuff. 722 00:39:40,000 --> 00:39:43,720 But he also has that passion about racing your bike and, you 723 00:39:43,720 --> 00:39:47,120 know, and educating the younger riders on tactics, technical 724 00:39:47,560 --> 00:39:49,560 positioning. There are things that we also 725 00:39:49,560 --> 00:39:50,800 know are super important as well. 726 00:39:50,800 --> 00:39:53,480 So it's definitely an interesting time in cycling from 727 00:39:53,480 --> 00:39:55,280 that regard. Yeah. 728 00:39:55,280 --> 00:39:57,440 And I think that's a really good point actually, because I feel 729 00:39:57,440 --> 00:40:04,040 in some ways that, you know, Team Sky arguably were the one 730 00:40:04,040 --> 00:40:08,280 that really held at this shift to a more like marginal gains 731 00:40:08,280 --> 00:40:12,720 obviously in data-driven, but I would argue that potentially it 732 00:40:12,720 --> 00:40:16,080 turned. Maybe it was the personalities 733 00:40:16,080 --> 00:40:18,600 who were in the team, but he was a little bit mechanical, a 734 00:40:18,600 --> 00:40:22,120 little bit the emotion maybe went out of it a little bit, 735 00:40:23,240 --> 00:40:27,080 which led to a bit of a backlash almost on some of that. 736 00:40:27,200 --> 00:40:33,000 And but now you've got people like today who clearly do a lot 737 00:40:33,000 --> 00:40:35,640 of the data stuff where you, you know, he does a lot of training 738 00:40:35,640 --> 00:40:39,320 and the team. But it it it's perceivably seems 739 00:40:39,320 --> 00:40:44,120 more impulsive and more emotional, a bit like Giuliani 740 00:40:44,120 --> 00:40:47,520 Philippe. So I guess the sport has to 741 00:40:47,520 --> 00:40:50,320 balance both, doesn't it? If it becomes too obsessed with 742 00:40:50,360 --> 00:40:54,200 all the data and sort of mechanical stuff, then the human 743 00:40:54,200 --> 00:40:58,840 side and what we love of seeing riders may sort of lose that as 744 00:40:58,840 --> 00:41:01,560 well. So I guess maybe that's the the 745 00:41:01,560 --> 00:41:04,120 balance isn't? It definitely, it's 746 00:41:04,120 --> 00:41:08,360 storytelling, you know, it's people, it's, it's, and I think 747 00:41:08,360 --> 00:41:10,720 the same thing happened with F1, you know, it's, it's, it's 748 00:41:11,000 --> 00:41:15,040 finding a way for people to to build them emotional 749 00:41:15,040 --> 00:41:17,800 relationships, to tell these stories, these experiences. 750 00:41:18,000 --> 00:41:21,360 That's just as important as all the tech that allows for them 751 00:41:21,360 --> 00:41:23,280 things to happen, you know. So it's definitely this, this 752 00:41:23,280 --> 00:41:26,080 balance for sure. Yeah, One thing that I would 753 00:41:26,080 --> 00:41:29,440 love to see, and I, I assume it's been discussed and maybe 754 00:41:29,440 --> 00:41:33,000 it's just not happened for various reasons, is I find the 755 00:41:33,000 --> 00:41:40,080 riders are so good at masking their pain that it's, you don't 756 00:41:40,080 --> 00:41:43,080 always know. And as a sort of more geeky 757 00:41:43,080 --> 00:41:46,080 person, I would love, and I know they've started to do this a 758 00:41:46,080 --> 00:41:49,240 little bit, but I would love to have their like body 759 00:41:49,240 --> 00:41:52,480 temperature, their heart rate, their power, like in real time. 760 00:41:52,760 --> 00:41:56,320 So I could sort of see how much they're suffering almost, you 761 00:41:56,320 --> 00:42:01,040 know, because sometimes you see somebody and you think they're 762 00:42:01,040 --> 00:42:03,320 doing great and then they suddenly just go and you think, 763 00:42:03,320 --> 00:42:06,600 surely, you know, he's felt that for a while, but he's just 764 00:42:06,600 --> 00:42:08,280 hidden it, you know? Do you know what I'm talking 765 00:42:08,280 --> 00:42:08,960 about? I don't know. 766 00:42:09,320 --> 00:42:12,560 The data could be. Used to make the sport more 767 00:42:12,600 --> 00:42:16,120 interactive in a way. It's a really good point and 768 00:42:16,120 --> 00:42:20,200 it's something, you know, as a, as Tudor and, and people I speak 769 00:42:20,200 --> 00:42:22,600 to have thought about a lot. It's, it's how do you improve 770 00:42:22,600 --> 00:42:26,080 that viewer engagement? You know, can you give more 771 00:42:26,080 --> 00:42:30,240 insights to allow, to allow for a better experience? 772 00:42:30,240 --> 00:42:33,240 And I think it's something that F1 did over the last, you know, 773 00:42:33,240 --> 00:42:37,680 5 or 10 years with cameras and, and having more of the, the 774 00:42:37,680 --> 00:42:40,360 radio on on on the TV and things like that. 775 00:42:40,360 --> 00:42:42,920 I think them things are that they're the really nice insights 776 00:42:42,920 --> 00:42:45,160 that you gather and you think, oh, OK, yeah, that, you know, I 777 00:42:45,160 --> 00:42:47,600 have this unique insight on what's happening in the F1 car. 778 00:42:47,600 --> 00:42:50,680 And I think cycling can, can definitely move forward. 779 00:42:50,680 --> 00:42:52,560 There are there are some initiatives, there's initiative 780 00:42:52,560 --> 00:42:56,200 called Velon, which is kind of a set a separate company that kind 781 00:42:56,200 --> 00:42:59,400 of is attached to certain races and they have like more data 782 00:42:59,400 --> 00:43:02,640 insights and they share certain insights they have in, you know, 783 00:43:03,080 --> 00:43:06,400 in video footage of the races. But apart from that, it's quite 784 00:43:06,400 --> 00:43:08,880 controlled from the UCI. So it's not something a team 785 00:43:08,880 --> 00:43:11,200 could do individually. You know, it's not like we could 786 00:43:11,280 --> 00:43:13,880 put cameras on every bike and release it to the world. 787 00:43:14,280 --> 00:43:16,560 It's very restrictive from that perspective. 788 00:43:16,560 --> 00:43:20,560 So it would take a from a UCI level from an organization to, 789 00:43:20,560 --> 00:43:23,080 to kind of take it forward. But for me, it's something that 790 00:43:23,120 --> 00:43:25,520 should definitely be done. And if it's done on a level 791 00:43:25,520 --> 00:43:28,160 playing field, there's no negative consequence of that. 792 00:43:28,160 --> 00:43:31,120 If everyone has to have a camera, then it's the same, you 793 00:43:31,120 --> 00:43:32,520 know, and then you get all these insights. 794 00:43:32,520 --> 00:43:34,440 So no, I will be definitely for that. 795 00:43:35,760 --> 00:43:39,720 So maybe 1 you, you mentioned a little bit and maybe this is 796 00:43:39,720 --> 00:43:44,840 teeing a little bit to some of the AI or machine learning side 797 00:43:44,840 --> 00:43:47,640 of things, but maybe first on the strategy side. 798 00:43:47,640 --> 00:43:52,240 So you've talked a lot about nutrition, bike design, how much 799 00:43:53,240 --> 00:43:56,560 data can be used to optimize strategy? 800 00:43:56,560 --> 00:43:59,800 You know, when someone should try, because sometimes I watch a 801 00:43:59,800 --> 00:44:06,440 race and I see somebody try to break away and I think surely 802 00:44:06,440 --> 00:44:11,160 there's an optimum power for them to just get that break, you 803 00:44:11,160 --> 00:44:13,280 know, to the elastic to get. And you think, oh, if they could 804 00:44:13,280 --> 00:44:16,400 have just gone for another 10 seconds, maybe they would have 805 00:44:16,400 --> 00:44:20,560 actually made it. Is there any way that you can 806 00:44:20,560 --> 00:44:25,000 look at that sort of more strategy side of things with the 807 00:44:25,000 --> 00:44:30,200 data-driven sport as it is now? Yeah, it's something I think a 808 00:44:30,200 --> 00:44:33,240 lot of teams are are trying to do and excited about. 809 00:44:34,480 --> 00:44:36,680 Like I said, cyclins are very data rich sports. 810 00:44:36,680 --> 00:44:38,680 So we have a lot of data. You know, we have second by 811 00:44:38,680 --> 00:44:43,320 second data on all our riders for maybe 1000 hours of training 812 00:44:43,320 --> 00:44:46,920 a year for many, many years. So we have a lot of data there 813 00:44:47,000 --> 00:44:49,120 and I think people are now starting to harness it. 814 00:44:49,720 --> 00:44:53,520 We definitely have quite a few projects that we look at, you 815 00:44:53,520 --> 00:44:56,480 know, we try and look at certain riders. 816 00:44:57,000 --> 00:44:59,920 Can they make it in certain races, you know, maybe sprinters 817 00:44:59,920 --> 00:45:01,760 for instance, can they pass certain climbs? 818 00:45:01,760 --> 00:45:04,960 What's the probability of chances of success to get to a 819 00:45:04,960 --> 00:45:07,240 certain point? Yeah. 820 00:45:07,280 --> 00:45:10,640 Do we expect a breakaway or not? I think it's quite an 821 00:45:10,640 --> 00:45:14,800 interesting one. Do we expect it to to succeed? 822 00:45:14,800 --> 00:45:17,440 Should we should we participate in that on certain stages? 823 00:45:18,720 --> 00:45:20,560 I think there's, there's lots of things that can be done. 824 00:45:20,560 --> 00:45:26,000 There's a lot of stuff around race choice and, and picking 825 00:45:26,000 --> 00:45:28,440 certain races for certain riders, understanding where 826 00:45:28,440 --> 00:45:31,480 their kind of potential is, you know, for, for results. 827 00:45:32,920 --> 00:45:36,280 So yeah, there's definitely a lot of optimization for, for 828 00:45:36,280 --> 00:45:38,800 those kind of data insights from data that's driven there. 829 00:45:39,160 --> 00:45:42,680 And then I think also with AI and, and the other kind of 830 00:45:42,680 --> 00:45:44,880 emerging techniques, there's, there's lots of stuff to be done 831 00:45:44,880 --> 00:45:48,560 around, around all the CFD computation stuff that we do. 832 00:45:48,920 --> 00:45:52,440 We've found that really in the earlier processes of that, but 833 00:45:53,000 --> 00:45:55,360 every time we run a simulation, every time we generate some 834 00:45:55,360 --> 00:45:58,760 data, we know that there could be long term potential insights 835 00:45:58,760 --> 00:46:00,040 in that data. So it's really about 836 00:46:00,040 --> 00:46:04,680 understanding how to, to sequence the store to, to, to 837 00:46:04,720 --> 00:46:07,720 evolve to know that maybe, you know, maybe not now, but in one 838 00:46:07,720 --> 00:46:10,640 year, 2 year, five years, there's, there's insights that 839 00:46:10,640 --> 00:46:13,560 can be gathered from that. And I think it's, yeah, making 840 00:46:13,560 --> 00:46:16,360 sure you're in the the right place now to set them things up 841 00:46:16,480 --> 00:46:19,120 so that in the future it is definitely a possibilities, 842 00:46:19,120 --> 00:46:21,280 that's for sure. So would it be fair to say that 843 00:46:21,280 --> 00:46:28,800 probably cycling has for the past, you know, 2-3, four years 844 00:46:28,800 --> 00:46:32,800 been moving far more to a data-driven attack, But we're, 845 00:46:32,840 --> 00:46:37,600 we're only just entering now the age of really AI for it. 846 00:46:37,600 --> 00:46:42,360 That would it be fair to say that most of cycling is probably 847 00:46:42,360 --> 00:46:44,760 always just now really getting into potential. 848 00:46:44,760 --> 00:46:48,400 So that could be something in the coming years that that could 849 00:46:48,400 --> 00:46:50,400 be used because as we talked about that sort of design 850 00:46:50,400 --> 00:46:52,840 optimization, you know, you've got so many different choices 851 00:46:52,840 --> 00:46:57,880 that seems or even logistics, I guess AI is a classic tool for 852 00:46:57,880 --> 00:47:01,680 optimizing things. Yeah, yeah, it definitely is 853 00:47:01,680 --> 00:47:03,480 something that I think we'll see more and more of. 854 00:47:03,480 --> 00:47:07,040 I think the sport itself is getting more professional, more 855 00:47:07,040 --> 00:47:09,560 funding. It's having, you know, more 856 00:47:10,440 --> 00:47:13,680 people like myself working sport, you know, kind of sitting 857 00:47:13,680 --> 00:47:16,720 in between the lines of of scientists that are kind of 858 00:47:16,720 --> 00:47:19,680 integrated. And yeah, I'd say most of the 859 00:47:19,720 --> 00:47:22,160 highest level teams now are starting to understand that and 860 00:47:22,160 --> 00:47:25,440 invest some of their resource in that and not just in better 861 00:47:25,440 --> 00:47:28,480 riders or, you know, or things like that. 862 00:47:29,520 --> 00:47:34,040 So what how about for for Tudor in particular, what does the, 863 00:47:34,160 --> 00:47:38,240 the sort of future hold? What, what's the big target, I 864 00:47:38,240 --> 00:47:42,440 guess this year and the coming years that that is driving all 865 00:47:42,440 --> 00:47:45,000 this towards? Do you have some very specific 866 00:47:45,320 --> 00:47:48,600 things that the team is trying to, you know, focus on and and 867 00:47:48,640 --> 00:47:53,320 and succeed? Yeah, I think as a team, I mean 868 00:47:53,320 --> 00:47:55,360 we have, we have quite a lot of strategy. 869 00:47:55,360 --> 00:47:57,160 I think in terms of where we want to go. 870 00:47:57,160 --> 00:47:59,880 We're we're really fortunate that we're a long term team. 871 00:47:59,960 --> 00:48:03,440 We have a long term vision and and a sustainable long term 872 00:48:03,440 --> 00:48:06,400 vision, which I think is quite unique in cycling. 873 00:48:07,880 --> 00:48:12,240 I think the first priority of the team is really to be in a 874 00:48:12,240 --> 00:48:14,680 position to allow us to have the full race calendar. 875 00:48:15,400 --> 00:48:17,080 So for people who don't understand cycling, if you're 876 00:48:17,080 --> 00:48:20,040 not a World Tour team, if you don't want the top 18 teams, 877 00:48:20,360 --> 00:48:24,000 then essentially you're kind of at the will of the race 878 00:48:24,000 --> 00:48:26,440 organizers to invite you to the biggest races. 879 00:48:27,720 --> 00:48:32,080 So we know if we achieve a certain rating every year, being 880 00:48:32,080 --> 00:48:35,240 one of what's called the top 2 pro teams, then that will allow 881 00:48:35,240 --> 00:48:37,560 us to have a full race calendar. And then once we have a full 882 00:48:37,560 --> 00:48:42,240 race calendar, it then opens up all the opportunities in terms 883 00:48:42,240 --> 00:48:44,000 of where we want to go and how we want to do stuff at the 884 00:48:44,000 --> 00:48:45,640 moment. Because we're a brand new team, 885 00:48:46,600 --> 00:48:49,000 we have to rely on them invitations, which can make 886 00:48:49,000 --> 00:48:51,760 planning and strategy quite challenging sometimes. 887 00:48:52,320 --> 00:48:56,280 So that's our first real goal. And really the long term goal, 888 00:48:56,280 --> 00:48:59,320 especially from my perspective is around the innovation team is 889 00:48:59,320 --> 00:49:02,640 really to just be a world leading innovation team with 890 00:49:02,640 --> 00:49:07,080 regards to performance. So a safety, aerodynamics, 891 00:49:07,200 --> 00:49:09,600 thermal from all the opportunities, having this whole 892 00:49:09,600 --> 00:49:13,320 system, individualized approach around key riders, looking at 893 00:49:13,320 --> 00:49:17,320 them as a whole system is really where the next, you know, 5-10 894 00:49:17,320 --> 00:49:20,000 years look like. And we can really do that 895 00:49:20,000 --> 00:49:23,160 ultimately, because we have a sustainable platform to launch 896 00:49:23,160 --> 00:49:25,560 from. You know, it's, I can imagine 897 00:49:25,560 --> 00:49:28,160 it's quite hard if you're in a team that's unstable to think, 898 00:49:28,280 --> 00:49:30,560 you know, I'm going to do this now and it might not pay off in 899 00:49:30,560 --> 00:49:34,200 five years, but we, we're in a real good place that we can do 900 00:49:34,200 --> 00:49:35,640 that. And I think that really allows 901 00:49:35,640 --> 00:49:39,320 us to be a front runner in the future and really invest in this 902 00:49:39,320 --> 00:49:42,160 kind of data-driven science driven approach. 903 00:49:43,640 --> 00:49:48,360 So maybe turning maybe towards the end of the of this chat, 904 00:49:48,360 --> 00:49:51,080 towards the top of that, I think is I personally am always 905 00:49:51,080 --> 00:49:54,760 interested in which is the advice for people and engineers 906 00:49:54,760 --> 00:49:58,960 wanting to get into the sport. You know, you, you came through 907 00:49:58,960 --> 00:50:02,640 the PhD route and then you, you know, you sort of work towards, 908 00:50:02,640 --> 00:50:05,200 you say like different sports and then track and then thing, 909 00:50:05,520 --> 00:50:08,640 you know, looking back, what sort of advice? 910 00:50:08,960 --> 00:50:12,120 Maybe let's break it down from a is it? 911 00:50:12,440 --> 00:50:15,320 Yeah, well, first of all, high level advice and then maybe we 912 00:50:15,360 --> 00:50:20,760 can pick apart some stuff. Yeah, I think about this a lot. 913 00:50:21,120 --> 00:50:24,920 I I really try and, yeah, take responsibility on myself to, to 914 00:50:24,920 --> 00:50:27,400 look back at, you know, when I was younger and what were the 915 00:50:27,560 --> 00:50:30,320 reasons why I, I'm in the fortunate position I am now. 916 00:50:30,760 --> 00:50:34,440 And I really try and give back to that because for me, some of 917 00:50:34,440 --> 00:50:37,800 the things I really reflect on is I had really good mentors. 918 00:50:37,800 --> 00:50:41,400 Like I had people who went through that process and really 919 00:50:41,400 --> 00:50:45,200 allowed me to connect, to discuss, to learn, to evolve, 920 00:50:45,200 --> 00:50:48,320 grow. And I think that was fundamental 921 00:50:48,320 --> 00:50:51,560 to where I am today, having them mentorships. 922 00:50:51,560 --> 00:50:54,880 If it's just having a coffee, picking the phone up, what do 923 00:50:54,880 --> 00:50:56,720 you think about this? Oh, I have a friend who does 924 00:50:56,720 --> 00:50:58,120 this. You know, why don't you have 925 00:50:58,120 --> 00:51:00,040 some conversations? I think that I'd really 926 00:51:00,040 --> 00:51:03,640 encourage that spirit of, you know, mentorship is really 927 00:51:03,640 --> 00:51:06,120 important and I think it's responsible both for young 928 00:51:06,160 --> 00:51:08,800 practitioners, but also for experienced practitioners like 929 00:51:08,800 --> 00:51:12,560 myself to, to also give back, I think is really important. 930 00:51:13,680 --> 00:51:16,840 I think the other thing is work ethic and, and, and doing your 931 00:51:16,840 --> 00:51:20,720 time like it's something that I really, you know, pride myself 932 00:51:20,720 --> 00:51:24,240 on and was something that really allowed me to move forward. 933 00:51:24,240 --> 00:51:27,280 You know, I was the first person to say yes to a volunteer 934 00:51:27,280 --> 00:51:31,000 opportunity to fill up bottles on the side of a rugby pitch, 935 00:51:31,000 --> 00:51:35,080 you know, or if it was to go to a swim meet in, in, you know, 936 00:51:35,200 --> 00:51:39,000 wherever and at 6:00 AM in the morning, just to, to be embedded 937 00:51:39,000 --> 00:51:42,240 within sport opportunities. And I didn't, and I really tried 938 00:51:42,240 --> 00:51:45,160 to take on as many opportunities as I could when I was younger 939 00:51:45,160 --> 00:51:47,800 just to see and feel and understand why I wanted to work 940 00:51:47,800 --> 00:51:51,120 in professional sport. And that goes a long way because 941 00:51:51,120 --> 00:51:54,920 when people see you're just willing to, to say yes and, and 942 00:51:54,920 --> 00:51:58,800 to, to understand and learn, I think can be really valuable. 943 00:51:58,800 --> 00:52:03,320 And, and that's a trait that I really look for in people. 944 00:52:03,320 --> 00:52:05,880 I look for that kind of willing spirit. 945 00:52:05,880 --> 00:52:09,760 I think a lot of people in my experience, you can train them 946 00:52:09,960 --> 00:52:12,920 for the, for the skills that you need, but actually the, the 947 00:52:12,920 --> 00:52:16,120 character and personality of someone is kind of ingrained. 948 00:52:16,120 --> 00:52:18,080 And I think if you can show that, you know, you're willing 949 00:52:18,080 --> 00:52:22,960 to, to work, to, to listen to, to put, to put effort in, to be 950 00:52:22,960 --> 00:52:25,920 passionate about something. I, I go for that any day over 951 00:52:25,920 --> 00:52:28,680 someone who has, you know, five years experience of doing the 952 00:52:28,680 --> 00:52:30,920 job already, You know, I really look for, for that. 953 00:52:30,920 --> 00:52:33,720 So that would be some of the things I would say mentorship 954 00:52:33,720 --> 00:52:36,560 really and and that kind of spirit of just willing to, to 955 00:52:36,560 --> 00:52:40,440 do. And what about from a practical 956 00:52:40,440 --> 00:52:44,120 point of view? What sort of are you looking 957 00:52:44,120 --> 00:52:51,160 more for like engineers, more for sports science, more for 958 00:52:51,160 --> 00:52:55,400 like data science? Is there certain sort of skill 959 00:52:55,400 --> 00:52:59,240 sets and maybe degrees that put you, I guess traditionally 960 00:52:59,240 --> 00:53:03,240 sports science would have been the route in to a sport. 961 00:53:03,240 --> 00:53:05,440 Is that still the case or do you think it's more about like 962 00:53:05,440 --> 00:53:07,360 engineering and data science now? 963 00:53:08,600 --> 00:53:10,080 I'd say historically you're correct. 964 00:53:10,080 --> 00:53:14,880 It was sports science and, and really probably was, yeah, the 965 00:53:14,880 --> 00:53:17,280 first investment I'd say from professionals, at least in 966 00:53:17,280 --> 00:53:21,800 cycling was sports science and understanding sports derived 967 00:53:21,800 --> 00:53:25,640 things, physiologists. And what you saw is then people 968 00:53:25,640 --> 00:53:28,640 generally then sat like myself across many spectrums. 969 00:53:28,640 --> 00:53:31,960 You know, we did data science, we did performance analysis. 970 00:53:31,960 --> 00:53:35,200 We kind of did the bits that we did some nutrition, maybe we did 971 00:53:35,200 --> 00:53:39,120 different things to really allow performance to move forward and 972 00:53:39,120 --> 00:53:41,880 having that generalized skill set was probably the weigh in. 973 00:53:41,880 --> 00:53:45,960 I'd say, you know, 5 or 10 years ago, I'd say now sport within 974 00:53:45,960 --> 00:53:48,240 cycle in particular, there's enough investment and 975 00:53:48,240 --> 00:53:51,400 understanding that these really specified roles are coming in 976 00:53:51,400 --> 00:53:54,800 and become really important. And I think for people who have 977 00:53:54,800 --> 00:53:57,720 them specific skills and their passion for sport, there's some 978 00:53:57,720 --> 00:53:59,400 really unique opportunities growing. 979 00:53:59,400 --> 00:54:03,360 So for instance, data science, you know, I, I know a bit of, of 980 00:54:03,360 --> 00:54:06,400 data science, but not to the level of a data scientist. 981 00:54:06,400 --> 00:54:08,720 And I think if you can come in with them skills, but also the 982 00:54:08,840 --> 00:54:12,360 conceptual understanding of cycling, you, there's massive 983 00:54:12,360 --> 00:54:13,560 potential for that in the future. 984 00:54:13,560 --> 00:54:16,880 And the same with engineers, you know, having aerodynamic 985 00:54:16,880 --> 00:54:20,680 engineers, design engineers, Mechanical Engineers that have 986 00:54:20,920 --> 00:54:24,440 this desire to work in cycling and this conceptual 987 00:54:24,440 --> 00:54:27,240 understanding of cycling, I see more and more opportunities for 988 00:54:27,240 --> 00:54:30,520 them either within professional teams or within partners that 989 00:54:30,520 --> 00:54:33,680 work with teams. And you see that's definitely a 990 00:54:33,680 --> 00:54:36,560 growing field now really that high level science within, 991 00:54:36,560 --> 00:54:39,200 within sport and particularly with cycling, it's more and more 992 00:54:39,200 --> 00:54:43,920 opportunities. And is there are there any 993 00:54:43,920 --> 00:54:47,280 recommendations? You know, when people sometimes 994 00:54:47,280 --> 00:54:50,760 ask me about Formula One, sometimes I say, OK, well if you 995 00:54:50,760 --> 00:54:55,480 can't get into Formula One, try and do with a lower quote UN 996 00:54:55,480 --> 00:54:58,040 quote, lower formula first just to get a practice spin. 997 00:54:58,520 --> 00:55:00,320 Is that something people can do with cycling? 998 00:55:00,320 --> 00:55:04,760 Or is that a slight almost gap that you know, it's either 999 00:55:04,760 --> 00:55:07,280 you've done a university course or you work for a cycling team, 1000 00:55:07,280 --> 00:55:10,800 but how do you get the experience to know? 1001 00:55:10,800 --> 00:55:14,120 Is there any things that you're aware of that people can clue 1002 00:55:14,120 --> 00:55:16,960 themselves up on? Cycling Pacific Knowledge. 1003 00:55:17,000 --> 00:55:21,120 Yeah, yes, it's definitely difficult to make that bridge 1004 00:55:21,160 --> 00:55:25,120 like you said, I'd say 1 The thing that I've seen successful 1005 00:55:25,120 --> 00:55:28,280 people do is using the opportunities they have through 1006 00:55:28,360 --> 00:55:33,280 their time as a student to allow for opportunities to interact 1007 00:55:33,280 --> 00:55:36,440 with with professional sports. So, you know, if you're an 1008 00:55:36,440 --> 00:55:38,440 undergraduate or a master's student and you know, you have 1009 00:55:38,440 --> 00:55:42,240 to do a placement or you have to do a final year project, trying 1010 00:55:42,240 --> 00:55:44,680 to drive that final year project in a direction where you can 1011 00:55:44,680 --> 00:55:47,560 interact with a professional team is a really nice way. 1012 00:55:47,560 --> 00:55:50,720 Because if you can approach them and say, you know, I need to do 1013 00:55:51,000 --> 00:55:55,480 200 hours of XYZI, need to do simulation, I need to do winter 1014 00:55:55,480 --> 00:55:58,800 tests, I need to do in the field research on this topic. 1015 00:55:58,800 --> 00:56:00,440 And I think it's really interesting for you and we can 1016 00:56:00,440 --> 00:56:03,080 shape the question to answer your problems. 1017 00:56:03,680 --> 00:56:05,920 They're the kind of things that would get me really excited, you 1018 00:56:05,920 --> 00:56:08,120 know, students that have that initiative, that have that 1019 00:56:08,120 --> 00:56:12,240 capacity to drive to drive this thing forward. 1020 00:56:12,240 --> 00:56:14,560 And it's a, you know, it can be a three month interview. 1021 00:56:14,560 --> 00:56:18,000 And even within our team, we have one member that came 1022 00:56:18,000 --> 00:56:19,760 directly from that kind of process. 1023 00:56:19,760 --> 00:56:22,680 You know, was it showed initiative, stepped through it 1024 00:56:22,680 --> 00:56:26,040 as a as a master's student and really secured an opportunity 1025 00:56:26,040 --> 00:56:28,640 straight from graduating in, in professional sport because he 1026 00:56:28,640 --> 00:56:33,840 showed that initiative to yeah on, on how to move, move himself 1027 00:56:33,840 --> 00:56:35,520 forward. So I'd say really try and shape 1028 00:56:35,520 --> 00:56:40,400 the experiences you have towards sport and, and bring a question 1029 00:56:40,400 --> 00:56:43,120 and A and a solution rather than just, you know, asking for 1030 00:56:43,120 --> 00:56:45,040 experience. I think that's something that's 1031 00:56:45,240 --> 00:56:48,040 can really help you break into professional sport and, and also 1032 00:56:48,040 --> 00:56:51,520 don't worry when you get a no, you know, I think if I remember 1033 00:56:51,520 --> 00:56:56,160 my initial period, I apply for so many jobs opportunities and, 1034 00:56:57,120 --> 00:56:59,240 and yeah, and, and sometimes it's not the right time, the 1035 00:56:59,240 --> 00:57:01,240 right place and, and that's completely fine. 1036 00:57:01,240 --> 00:57:05,120 And, and I really believe they shape you to the person you are, 1037 00:57:05,160 --> 00:57:07,960 you know, and, and yeah, don't, don't give up when it, when it 1038 00:57:07,960 --> 00:57:10,520 becomes difficult. I think that's just something 1039 00:57:10,520 --> 00:57:13,320 that really allows you to to break into difficult industry. 1040 00:57:14,760 --> 00:57:17,760 No, that's, that's a great piece of advice. 1041 00:57:17,760 --> 00:57:23,960 And no, I, I actually, I mean the big picture, I always, and I 1042 00:57:23,960 --> 00:57:27,360 guess the reason why I, we're so keen to speak to you and, and 1043 00:57:27,360 --> 00:57:32,320 generally talk about cycling is I feel like engineering or sort 1044 00:57:32,320 --> 00:57:36,520 of sports side of engineering almost is some people turn away 1045 00:57:37,080 --> 00:57:41,040 from engineering because it's almost perceived as not being 1046 00:57:41,040 --> 00:57:46,080 exciting or it's not being fun and they see football or 1047 00:57:46,080 --> 00:57:48,120 whatever or, or second as being fun. 1048 00:57:48,120 --> 00:57:51,240 And I suppose one of the things I've always been a fan of is 1049 00:57:51,480 --> 00:57:55,960 that if you can link those two things, then it's like you have 1050 00:57:55,960 --> 00:57:58,360 the pleasure of working on something that you actually 1051 00:57:58,920 --> 00:58:01,640 like. And I think Formula One was 1052 00:58:01,640 --> 00:58:06,440 traditionally always that thing. But I think it's it, it has, 1053 00:58:06,600 --> 00:58:08,720 it's just hard to get into. That's just the one. 1054 00:58:08,720 --> 00:58:12,440 And there are so many aerodynamicists working in a 1055 00:58:12,440 --> 00:58:16,800 team 50, I don't know, maybe 70 that you're just working on, you 1056 00:58:16,800 --> 00:58:20,160 know, the equivalent of optimizing a spoke on a wheel, 1057 00:58:20,160 --> 00:58:23,960 let's say, where I guess if they work for someone like your 1058 00:58:23,960 --> 00:58:26,960 company, they're going to be working the whole thing 1059 00:58:26,960 --> 00:58:30,640 probably. So it's like it's more rewarding 1060 00:58:30,680 --> 00:58:36,120 maybe actually to sort of go into a cycling thing maybe than 1061 00:58:36,120 --> 00:58:39,640 Formula One in a way. So it's almost, maybe I'm 1062 00:58:39,760 --> 00:58:42,800 encouraging if there's people listening to maybe consider 1063 00:58:43,120 --> 00:58:45,440 getting into the sort of cycling side of engineering because it 1064 00:58:45,440 --> 00:58:48,320 could be more fulfilling potentially than your 1065 00:58:48,320 --> 00:58:52,320 traditional Formula One. Yeah, it definitely offers that 1066 00:58:52,320 --> 00:58:55,400 opportunity to go through the whole process as well. 1067 00:58:55,400 --> 00:58:58,600 You know, it is a sport. We, you know, we're much less 1068 00:58:58,600 --> 00:59:01,360 budget, we're more, you know, agile with our resource. 1069 00:59:01,360 --> 00:59:03,960 And yeah, if you're in error analysis within cycling, you 1070 00:59:03,960 --> 00:59:07,720 work everything from, you know, conceptual CFD all the way to to 1071 00:59:07,720 --> 00:59:09,520 real world validation with a human being. 1072 00:59:09,520 --> 00:59:13,080 And you're you get to have all them touch points across that 1073 00:59:13,080 --> 00:59:14,640 that piece. And I think it makes you a much 1074 00:59:14,720 --> 00:59:17,000 better practitioner when it's like that, you know, when you 1075 00:59:17,000 --> 00:59:20,320 can understand from really complex kind of, you know, 1076 00:59:20,640 --> 00:59:24,160 fundamentals all the way down to convincing a human being of the 1077 00:59:24,160 --> 00:59:26,400 work you're doing and getting their feedback and having a 1078 00:59:26,400 --> 00:59:29,680 holistic approach. That to me is what gets me out 1079 00:59:29,680 --> 00:59:31,320 of bed every day. You know, I get to do this 1080 00:59:31,320 --> 00:59:34,360 really complex science, but actually apply it and then 1081 00:59:34,720 --> 00:59:37,920 ultimately seeing it in in competition and, you know, 1082 00:59:38,280 --> 00:59:40,520 watching it on TV or be in their present. 1083 00:59:40,520 --> 00:59:43,840 And, you know, having your heart rate at 180 beats a minute when 1084 00:59:44,280 --> 00:59:46,520 when they're going into a final and thinking, yeah, I've played 1085 00:59:46,520 --> 00:59:48,440 a small part in that. That's, that's a really nice 1086 00:59:48,440 --> 00:59:49,920 feeling. And I would definitely encourage 1087 00:59:50,240 --> 00:59:53,520 people who are interested to, yeah, to reach out and and to 1088 00:59:53,520 --> 00:59:55,520 look at opportunities inside because it's definitely a 1089 00:59:55,520 --> 00:59:58,600 growing space moving forward. Great. 1090 00:59:58,640 --> 01:00:02,040 Well, yeah, thanks so much Kurt, for for for chatting today. 1091 01:00:02,040 --> 01:00:06,480 I'm hoping people, you know, got the same that I have this, which 1092 01:00:06,480 --> 01:00:12,160 is just this excitement, I guess for for cycling and you know, 1093 01:00:12,160 --> 01:00:16,760 Petuda, I think it's great when there's these new relatively new 1094 01:00:16,760 --> 01:00:19,160 teams coming in trying to sort of shake it up. 1095 01:00:19,240 --> 01:00:22,200 And I think it's it's good because it makes the more 1096 01:00:22,200 --> 01:00:24,680 established teams sort of whereas they've got to shake up 1097 01:00:24,680 --> 01:00:26,840 and it. And it's good also for people 1098 01:00:26,840 --> 01:00:28,640 who wanted to get into the sport, that there's more 1099 01:00:28,640 --> 01:00:33,080 companies, more jobs. So yeah, thank you so much for 1100 01:00:33,080 --> 01:00:37,040 speaking and educating us all on on what it's like to be a Pro 1101 01:00:37,040 --> 01:00:38,880 Cycling team. Perfect. 1102 01:00:38,920 --> 01:00:39,360 Thanks. Now.