Improvements in top-100 running times are a combination of many somewhat independent changes in talent-pool, technology, training, race organization, etc. It's entirely possible shoes were necessary to continue the trend of improvement. Just because times stayed on trend doesn't mean that new advances aren't contributing to that trend.
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41
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Salvitore Stitchmo wrote:
Ray wrote:
Allie Kieffer recently posted results of her participating in a study comparing her running in 3 of the top super shoes. The Alpha Fly 3 showed a 5.8% increase over the control shoe. The other shoes tested were the Adios Pro 2 (.8%) and the Vaporfly 3 (3.7%). That's is a huge benefit! Couldn't tell what the control shoe was other than it was a current model Saucony.
Okay. Uhh and what, because Allie Kieffer ran better in her AlphaFly 3's that's the proof behind the numbers? I think what amazes me most is how people just absorb the numbers without any contemplation of circumstances possibly around them.
First of all what's the 5.8% "increase" in? vV02max (velocity @V02max?), velocity at sub V02max? An arbitrary running economy metric? Secondly what are the details of the test - did she do it all on the same day? Maybe she did the test in the AF's first when she was freshest? Maybe she simply liked the look of the AF's more than the others which gave her a completely unquantifiable placebo effect benefit before she even ran. Maybe they did the testing over a number of days - was her biorhythm the exact same day of the test? What time of day was it?
My point is, there is a massive difference between a lab test on a robot and lab test on a living breathing human whose state is constantly changing and this will always be the issue in testing these shoes. Not only do we have responder theory but also we have to take into account factors even at the human level irrespective of their level of response.
And those results would validate what I said above - 5.8% "increase" in AF's vs 0.8% in Adidas Pro when fundamentally there is no difference in the makeup of the shoes apart from a small difference in foam type (not 5% different) and a useless forefoot air bag? Those numbers are meaningless.
Just pointing out a post by Allie today. If you'd like the answer to your questions, maybe you can do some research? Just a thought.
20 -
DataNerd wrote:
NCAA male track data. Super Spikes introduced 2021, fully adopted by 2022 outdoor season.
100th NCAA Outdoor Track Performance
Year 1500 5000 10000
2023 03:42.47 13:49.80 29:05.27
2022 03:42.11 13:46.80 29:04.04
2021 03:43.15 13:52.11 29:18.77
2020 season cancelled
2019 03:45.62 14:03.28 29:32.21
2018 03:45.22 14:03.58 29:42.61
2017 03:45.44 14:04.27 29:43.43
2016 03:44.93 14:02.40 29:42.32
2015 03:44.61 14:04.40 29:46.66
2014 03:45.33 14:05.11 29:38.94
2013 03:45.68 14:06.41 29:47.66
2012 03:45.79 14:04.37 29:47.91
2011 03:46.34 14:07.59 29:56.68
2010 03:45.98 14:04.39 29:51.28But this is like the NFL analytics that tell you it's better to go for it on 4th and 4 in a road playoff game when you can kick a 40 yard FG. This is just a data set and there are so many factors that could be behind this - like just think a little more holistically then what is easy and right in front of you.
And the most obvious one to me is that concept that we as humans are an incredible species that with the right stimulus and incentive can and do evolve to set new plateaus and shift paradigms of performance.
Just like when nobody thought a 4min mile was possible until it was and Bannister breaking that barrier not only showed it was possible but set a new level of incentives that the best milers in the world quickly adapted themselves to before joining him. In the late 90's driving a golf ball 300 yards was basically unheard of unless you were John Daly or Tiger Woods - until Woods in particular ushered in shift in training and dedication and now it's hard to make a cut on tour unless you have the clubhead speed to hit it 300+ when you need to.
The level of college distance running has exploded since 2020 but you can't simply say it's just spikes. The depth is better, these kids are adopting training methods, principals and methodologies used by pro's and this open source world we live in means if you want to know how Ingebrigtsen is training, or Kipchoge, or Cheptegei, or Nuguse, or Kipyegon - you can find it out 60 seconds of internet searching. I remember trying to find pro schedules in the early 2000's and it was really hard - stuff like that made it seem like those guys were just superhuman, but now we can see what the best are doing and have that to shoot for.
Again it's the theme of this thread - nobody is denying product isn't helping, but to simply attribute it all to it under this assumption that the evolution of running performance is just stagnant is simply short sighted.
53 -
Ray wrote:
Just pointing out a post by Allie today. If you'd like the answer to your questions, maybe you can do some research? Just a thought.
I don't need answers to it. I don't really care what her opinion of those shoes are.
02 -
camminady wrote:
I don't really ever post here but I happen to have something to contribute here.
I'm a data scientist and have once put some effort into scraping which lists top performances for all kinds of sports. I quickly put together this interactive graphicIt shows the performances (y-axis in seconds, sorry no time for making this nice) over the last 23 years for men and women for 10k, hm, m. The slider at the bottom lets you place the start point of the super shoe era. Then the linear fits in each chart get updated with the corresponding data.
Took me a while to figure it out, but this is pretty cool. I take it the data is taken from your all-athletics site, and that it's probably most accurate to leave the slider on the 2017 year. One can see a relative lack of events centered around the 2021 grid line, and the slopes of the super-shoe trend lines seem to align with my findings as well.
10 -
Thanks for the feedback! I just want to clarify, this is not my website where the data is coming from. The website is by Peter Larsson. I just wrote some python code to parse the data. :)
20 -
NotKevinMcHale wrote:
A glance at your data shows that men's marathon times had stagnated for several years before super shoes and started falling again during the super shoe years. The average time during the period of stagnation (2011-2017) is 2:07:30 which is only 15 seconds faster than the predicted NoShoeEffect time for 2023.
AvgTime NoShoeEffect
2001 2:09:57
2002 2:09:33
2003 2:08:50
2004 2:09:43
2005 2:09:49
2006 2:09:31
2007 2:09:02
2008 2:08:37
2009 2:08:12
2010 2:08:07
2011 2:07:45
2012 2:06:58
2013 2:07:33
2014 2:07:19
2015 2:07:42
2016 2:07:42
2017 2:07:28 2:07:48
2018 2:06:54 2:08:03
2019 2:06:08 2:07:47
2020 2:06:58 2:09:12
2021 2:06:02 2:08:21
2022 2:05:53 2:08:12
2023 2:05:27 2:07:45This illustrates the challenge of finding the most appropriate method of drawing the trend line, as it can change quite a bit depending on when you start and how you calculate it. If one starts at 2011, then the drop after 2017 becomes more significant. So, this time around I just tried to go back as many years as possible and do it the same for each event, even though that tends to place an undue amount of importance on the earlier years in the series, since runners from then are (mostly) not even racing anymore.
But the main point, as in this example, is that if the average time fell 2:51 in the seven years between 2005 and 2012 and no one complained about that (or maybe they did?), then it shouldn't matter if the average time fell 2:15 in the seven years between 2016 and 2023, even if it was because of the shoes.10 -
Salvitore Stitchmo wrote:
DataNerd wrote:
NCAA male track data. Super Spikes introduced 2021, fully adopted by 2022 outdoor season.
100th NCAA Outdoor Track Performance
Year 1500 5000 10000
2023 03:42.47 13:49.80 29:05.27
2022 03:42.11 13:46.80 29:04.04
2021 03:43.15 13:52.11 29:18.77
2020 season cancelled
2019 03:45.62 14:03.28 29:32.21
2018 03:45.22 14:03.58 29:42.61
2017 03:45.44 14:04.27 29:43.43
2016 03:44.93 14:02.40 29:42.32
2015 03:44.61 14:04.40 29:46.66
2014 03:45.33 14:05.11 29:38.94
2013 03:45.68 14:06.41 29:47.66
2012 03:45.79 14:04.37 29:47.91
2011 03:46.34 14:07.59 29:56.68
2010 03:45.98 14:04.39 29:51.28...The level of college distance running has exploded since 2020 but you can't simply say it's just spikes. The depth is better, these kids are adopting training methods, principals and methodologies used by pro's and this open source world we live in means if you want to know how Ingebrigtsen is training, or Kipchoge, or Cheptegei, or Nuguse, or Kipyegon - you can find it out 60 seconds of internet searching. ...
Again it's the theme of this thread - nobody is denying product isn't helping, but to simply attribute it all to it under this assumption that the evolution of running performance is just stagnant is simply short sighted.
Please note that my post was factual and verifiable. My source was tfrrs. I did not give my opinion about what the data means.
There is a clear shift in the 100th fastest time that exactly coincides with the introduction of the shoes. ~2 seconds in the 1500, ~10 seconds in the 5000, and ~30 seconds in the 10000. Those are significant changes after 10 years of minimal changes.
There may be other factors. However, there was no other technology change (track surfaces, etc.). There was not a massive turnover of coaches and it is unlikely that most of them suddenly made a radical change in their training plans. Well, they might be able to do more / harder workouts in shoes that are easier on the athlete's legs.
If the shoes had a minimal effect, there would be a decent number of runners running in the older style shoes for comfort, price, etc. But that is not the case. Without the shoes, a runner is no longer competitive, so the old style is gone - no longer available. Using the old style would be like giving about a 10 second head start to the 5000 runner with the new shoes.
The road shoes have had the same effect - no longer in use despite much higher cost.
41 -
DataNerd wrote:
Salvitore Stitchmo wrote:
...The level of college distance running has exploded since 2020 but you can't simply say it's just spikes. The depth is better, these kids are adopting training methods, principals and methodologies used by pro's and this open source world we live in means if you want to know how Ingebrigtsen is training, or Kipchoge, or Cheptegei, or Nuguse, or Kipyegon - you can find it out 60 seconds of internet searching. ...
Again it's the theme of this thread - nobody is denying product isn't helping, but to simply attribute it all to it under this assumption that the evolution of running performance is just stagnant is simply short sighted.
Please note that my post was factual and verifiable. My source was tfrrs. I did not give my opinion about what the data means.
There is a clear shift in the 100th fastest time that exactly coincides with the introduction of the shoes. ~2 seconds in the 1500, ~10 seconds in the 5000, and ~30 seconds in the 10000. Those are significant changes after 10 years of minimal changes.
There may be other factors. However, there was no other technology change (track surfaces, etc.). There was not a massive turnover of coaches and it is unlikely that most of them suddenly made a radical change in their training plans. Well, they might be able to do more / harder workouts in shoes that are easier on the athlete's legs.
If the shoes had a minimal effect, there would be a decent number of runners running in the older style shoes for comfort, price, etc. But that is not the case. Without the shoes, a runner is no longer competitive, so the old style is gone - no longer available. Using the old style would be like giving about a 10 second head start to the 5000 runner with the new shoes.
The road shoes have had the same effect - no longer in use despite much higher cost.
Here is the same data from the World Athletics world top-100 lists. Similar, but not as pronounced. Here, it's 1.2 seconds improvement in the 1500, 6 seconds in the 5000, and 14.7 seconds in the 10000 (or 0.56%, 0.75%, 0.88%, respectively), by taking the averages of 2021-2023 and comparing it against the averages of 2010-2019.
Year 1500 5000 10000
2023 03:33.4 13:06.6 27:34.0
2022 03:34.9 13:07.8 27:28.0
2021 03:34.2 13:12.2 27:32.3
2020 03:36.2 13:19.3 27:48.0
2019 03:35.5 13:14.4 27:41.8
2018 03:35.8 13:17.5 27:55.9
2017 03:35.6 13:16.3 27:45.2
2016 03:35.7 13:14.6 27:38.7
2015 03:35.3 13:15.9 27:44.1
2014 03:35.5 13:17.3 27:55.8
2013 03:35.0 13:15.0 27:49.7
2012 03:34.8 13:11.7 27:36.5
2011 03:35.0 13:13.7 27:39.2
2010 03:35.4 13:11.9 27:53.700 -
DataNerd wrote:
Salvitore Stitchmo wrote:
...The level of college distance running has exploded since 2020 but you can't simply say it's just spikes. The depth is better, these kids are adopting training methods, principals and methodologies used by pro's and this open source world we live in means if you want to know how Ingebrigtsen is training, or Kipchoge, or Cheptegei, or Nuguse, or Kipyegon - you can find it out 60 seconds of internet searching. ...
Again it's the theme of this thread - nobody is denying product isn't helping, but to simply attribute it all to it under this assumption that the evolution of running performance is just stagnant is simply short sighted.
Please note that my post was factual and verifiable. My source was tfrrs. I did not give my opinion about what the data means.
There is a clear shift in the 100th fastest time that exactly coincides with the introduction of the shoes. ~2 seconds in the 1500, ~10 seconds in the 5000, and ~30 seconds in the 10000. Those are significant changes after 10 years of minimal changes.
There may be other factors. However, there was no other technology change (track surfaces, etc.). There was not a massive turnover of coaches and it is unlikely that most of them suddenly made a radical change in their training plans. Well, they might be able to do more / harder workouts in shoes that are easier on the athlete's legs.
If the shoes had a minimal effect, there would be a decent number of runners running in the older style shoes for comfort, price, etc. But that is not the case. Without the shoes, a runner is no longer competitive, so the old style is gone - no longer available. Using the old style would be like giving about a 10 second head start to the 5000 runner with the new shoes.
The road shoes have had the same effect - no longer in use despite much higher cost.
To make the NCAA comparison/analysis more complete, I scraped the data from the site you referenced and used the same approach Keith did with the IAAF data. One exception to Keith's approach, I fit the trend line using 2010-2019 performances. This includes men's and women's 1500m, 5000m, and 10000m.
A few interesting observations, which seem to align with what I said regarding men and women and performance limits. The women are improving at a faster rate compared to the men overall. That would suggest the men are closer to their performance limit. However, the men do see a more consistent and substantive drop after 2020... could be that contracting COVID (or getting the vaccine) had a more significant biochemical stimulus for male endurance performance LOL
Keith, if you'd like, I can send you the code and data to include on your website?
This post was edited 3 minutes after it was posted.10 -
Boing boing shoes are cheating. Run faster, recover quicker.
11 -
Salvitore Stitchmo wrote:
DataNerd wrote:
NCAA male track data. Super Spikes introduced 2021, fully adopted by 2022 outdoor season.
100th NCAA Outdoor Track Performance
Year 1500 5000 10000
2023 03:42.47 13:49.80 29:05.27
2022 03:42.11 13:46.80 29:04.04
2021 03:43.15 13:52.11 29:18.77
2020 season cancelled
2019 03:45.62 14:03.28 29:32.21
2018 03:45.22 14:03.58 29:42.61
2017 03:45.44 14:04.27 29:43.43
2016 03:44.93 14:02.40 29:42.32
2015 03:44.61 14:04.40 29:46.66
2014 03:45.33 14:05.11 29:38.94
2013 03:45.68 14:06.41 29:47.66
2012 03:45.79 14:04.37 29:47.91
2011 03:46.34 14:07.59 29:56.68
2010 03:45.98 14:04.39 29:51.28But this is like the NFL analytics that tell you it's better to go for it on 4th and 4 in a road playoff game when you can kick a 40 yard FG. This is just a data set and there are so many factors that could be behind this - like just think a little more holistically then what is easy and right in front of you.
And the most obvious one to me is that concept that we as humans are an incredible species that with the right stimulus and incentive can and do evolve to set new plateaus and shift paradigms of performance.
Just like when nobody thought a 4min mile was possible until it was and Bannister breaking that barrier not only showed it was possible but set a new level of incentives that the best milers in the world quickly adapted themselves to before joining him. In the late 90's driving a golf ball 300 yards was basically unheard of unless you were John Daly or Tiger Woods - until Woods in particular ushered in shift in training and dedication and now it's hard to make a cut on tour unless you have the clubhead speed to hit it 300+ when you need to.
The level of college distance running has exploded since 2020 but you can't simply say it's just spikes. The depth is better, these kids are adopting training methods, principals and methodologies used by pro's and this open source world we live in means if you want to know how Ingebrigtsen is training, or Kipchoge, or Cheptegei, or Nuguse, or Kipyegon - you can find it out 60 seconds of internet searching. I remember trying to find pro schedules in the early 2000's and it was really hard - stuff like that made it seem like those guys were just superhuman, but now we can see what the best are doing and have that to shoot for.
Again it's the theme of this thread - nobody is denying product isn't helping, but to simply attribute it all to it under this assumption that the evolution of running performance is just stagnant is simply short sighted.
Great point. You see this attitude in every single super spike thread.
To attribute any increases in depth, any improvements in performance in the last several years entirely to footwear is simplistic at best. Seeing that the 100th time got faster and then crying “shoes” is not analysis.
Someone commented that there haven’t been any radical changes in training which I thought was funny. How many people not named Ingebrigtsen were doing double threshold five years ago?
Spikes are just one of the many factors at play.
20 -
As a professional mathematician, I can say this study is a high school level analysis. There is no inference at all here, and therefore very little to take away from it.
11 -
moultonk wrote:
NotKevinMcHale wrote:
A glance at your data shows that men's marathon times had stagnated for several years before super shoes and started falling again during the super shoe years. The average time during the period of stagnation (2011-2017) is 2:07:30 which is only 15 seconds faster than the predicted NoShoeEffect time for 2023.
AvgTime NoShoeEffect
2001 2:09:57
2002 2:09:33
2003 2:08:50
2004 2:09:43
2005 2:09:49
2006 2:09:31
2007 2:09:02
2008 2:08:37
2009 2:08:12
2010 2:08:07
2011 2:07:45
2012 2:06:58
2013 2:07:33
2014 2:07:19
2015 2:07:42
2016 2:07:42
2017 2:07:28 2:07:48
2018 2:06:54 2:08:03
2019 2:06:08 2:07:47
2020 2:06:58 2:09:12
2021 2:06:02 2:08:21
2022 2:05:53 2:08:12
2023 2:05:27 2:07:45This illustrates the challenge of finding the most appropriate method of drawing the trend line, as it can change quite a bit depending on when you start and how you calculate it. If one starts at 2011, then the drop after 2017 becomes more significant. So, this time around I just tried to go back as many years as possible and do it the same for each event, even though that tends to place an undue amount of importance on the earlier years in the series, since runners from then are (mostly) not even racing anymore.
But the main point, as in this example, is that if the average time fell 2:51 in the seven years between 2005 and 2012 and no one complained about that (or maybe they did?), then it shouldn't matter if the average time fell 2:15 in the seven years between 2016 and 2023, even if it was because of the shoes.
I saw that too. There are a few interesting trends in there. Thanks for doing the work to design, gather, prepare, and present the data.
10 -
right on wrote:
Great point. You see this attitude in every single super spike thread.
To attribute any increases in depth, any improvements in performance in the last several years entirely to footwear is simplistic at best. Seeing that the 100th time got faster and then crying “shoes” is not analysis.
Someone commented that there haven’t been any radical changes in training which I thought was funny. How many people not named Ingebrigtsen were doing double threshold five years ago?
Spikes are just one of the many factors at play.
And it's not just training but it's also that we have seen a massive shift in the preferred physiological makeup of the 1500m runner/miler. For decades the consensus was you were an 800/1500m guy or a 5000/10000m guy. And this goes all the way back to your Peter Snell, Jim Ryuns and your Zatopek, Virens and of course with respect to the 1500, the most era which was Ovett, Coe and Cram. But that world class 800/1500 athlete is a rarity on the mens side - you have Wightman at 1.43/3.29 and just prior to him Tim C at 1.43/3.28 but again, they are now outliers. Because the best milers are all studs over 3000/5000m too. Jakob, Katir, Farah, Kerr, Nuguse, Nordas - George Mills just ran 12.58! For years we believed that 1500m excellence was more suited to athletes with the requisite anaerobic power of the 800m runner and we now realize it's better suited to athletes with the requisite anaerobic threshold of the 3/5000m runner. Nobody realized the principals that went into elite 5000m running would actually be better suited for the mile than those of the 800, but turns out they are.
So I would argue that not only have we seen radical changes in training for the 1500m/mile we have seen a radical shift in the modern 1500m athlete which has pertained to that too.
This post was edited 1 minute after it was posted.20 -
Hard2Find wrote:
To make the NCAA comparison/analysis more complete, I scraped the data from the site you referenced and used the same approach Keith did with the IAAF data. One exception to Keith's approach, I fit the trend line using 2010-2019 performances. This includes men's and women's 1500m, 5000m, and 10000m.
A few interesting observations, which seem to align with what I said regarding men and women and performance limits. The women are improving at a faster rate compared to the men overall. That would suggest the men are closer to their performance limit. However, the men do see a more consistent and substantive drop after 2020... could be that contracting COVID (or getting the vaccine) had a more significant biochemical stimulus for male endurance performance LOL
Keith, if you'd like, I can send you the code and data to include on your website?
Ha! The COVID theory is one I hadn't thought of, but it kind of makes sense... as well as everyone getting a year off to heal their injuries, but I have to admit to suspecting the shoes more than before.
These graphs are striking and kudos to DataNerd for getting the data together in the first place. If you want to reach out through the comment form or the About page on my site, I'll find some place to post it.
Does anyone have an idea of the percentage of NCAA athletes wearing bonafide super-spikes vs. super-shoes vs. regular shoes among the top-100 in the 1500, 5000 and 10000? I'd guess it's close to 100% spikes (super and otherwise) in the 1500, but the longer events? For example, in the Men's 5000 Final, what are they wearing?10 -
Take the 51 top men's marathon times, 2:04 flat and down, and you'll see that they are virtually all within the last decade. A couple of them are accounted for by the Boston tailwinds in 2011, low 2:03, and others are probably dependent in part on drugs, so that the effect of the shoes could have been muddied by the presence of heavily doped athletes prior to 2016 and the emergence of the shoes on the roads. The only non-aided course results in the list prior to 2016 and the shoes are:
Geb 2008, 2:03:59 (and this was the former 5000m and 10000m wr holder, so the big drop was expected when he moved to the marathon), Kipchoge in 2015 at 2:04:00, Emmanuel Mutai 2013, 2:03:55, and 2014, 2:03:13, Wilson Kipsang in 2015, 2:03:23 and 2013 2:03:42, Dennis Kimetto coming from out of nowhere to run 2:03:45 in 2013 and 2:02:57 in 2014, Patrick Makau, 2:03:38, 2011.
Makau was linked to doping according to multiple articles; Kipsang was banned. So, out of the six 2:04:00 or under marathoners prior to 2016, at least 1/3 were doping.
1 2:00:35 Kelvin Kiptum KEN 02.12.99 1 Chicago 08.10.2023 2 2:01:09 Eliud Kipchoge KEN 05.11.84 1 Berlin 25.09.2022 3 2:01:25 Kelvin Kiptum KEN 02.12.99 1 London 23.04.2023 4 2:01:39 Eliud Kipchoge KEN 05.11.84 1 Berlin 16.09.2018 5 2:01:41 Kenenisa Bekele ETH 13.06.82 1 Berlin 29.09.2019 6 2:01:53 Kelvin Kiptum KEN 02.12.99 1 Valencia 04.12.2022 7 2:02:37 Eliud Kipchoge KEN 05.11.84 1 London 28.04.2019 8 2:02:40 Eliud Kipchoge KEN 05.11.84 1 Tokyo 06.03.2022 9 2:02:42 Eliud Kipchoge KEN 05.11.84 1 Berlin 24.09.2023 10 2:02:48 Birhanu Legesse ETH 09.11.94 2 Berlin 29.09.2019 11 2:02:55 Mosinet Geremew ETH 12.02.92 2 London 28.04.2019 12 2:02:57 Dennis Kimetto KEN 22.04.84 1 Berlin 28.09.2014 12 2:02:57 Titus Ekiru KEN 02.01.92 1 Milano 16.05.2021 14 2:03:00 Evans Chebet KEN 05.03.88 1 Valencia 06.12.2020 14 2:03:00 Gabriel Gerald Geay TAN 10.09.96 2 Valencia 04.12.2022 16 2:03:02a Geoffrey Mutai KEN 07.10.81 1 Boston 18.04.2011 17 2:03:03 Kenenisa Bekele ETH 13.06.82 1 Berlin 25.09.2016 18 2:03:04 Lawrence Cherono KEN 07.08.88 2 Valencia 06.12.2020 19 2:03:05 Eliud Kipchoge KEN 05.11.84 1 London 24.04.2016 20 2:03:06a Moses Mosop KEN 17.07.85 2 Boston 18.04.2011 21 2:03:13 Emmanuel Mutai KEN 12.10.84 2 Berlin 28.09.2014 21 2:03:13 Wilson Kipsang Kiprotich KEN 15.03.82 2 Berlin 25.09.2016 21 2:03:13 Amos Kipruto KEN 16.09.92 2 Tokyo 06.03.2022 21 2:03:13 Vincent Kipkemoi KEN 03.01.99 2 Berlin 24.09.2023 25 2:03:16 Mule Wasihun ETH 20.10.93 3 London 28.04.2019 25 2:03:16 Birhanu Legesse ETH 09.11.94 3 Valencia 06.12.2020 27 2:03:23 Wilson Kipsang Kiprotich KEN 15.03.82 1 Berlin 29.09.2013 28 2:03:24 Tadese Takele ETH 03.08.02 3 Berlin 24.09.2023 29 2:03:29 Alexander Mutiso KEN 10.09.96 3 Valencia 04.12.2022 30 2:03:30 Amos Kipruto KEN 16.09.92 4 Valencia 06.12.2020 31 2:03:32 Eliud Kipchoge KEN 05.11.84 1 Berlin 24.09.2017 32 2:03:34 Getaneh Molla ETH 10.01.94 1 Dubai 25.01.2019 33 2:03:36 Sisay Lemma ETH 12.12.90 3 Berlin 29.09.2019 33 2:03:36 Abdi Bashir BEL 02.10.89 1 Rotterdam 24.10.2021 35 2:03:38 Patrick Makau KEN 02.03.85 1 Berlin 25.09.2011 36 2:03:39 Tamirat Tola ETH 11.08.91 1 Amsterdam 17.10.2021 37 2:03:40 Herpasa Negasa ETH 11.09.93 2 Dubai 25.01.2019 37 2:03:40 Tamirat Tola ETH 11.08.91 4 Valencia 04.12.2022 39 2:03:42 Wilson Kipsang Kiprotich KEN 15.03.82 1 Frankfurt 30.10.2011 40 2:03:45 Dennis Kimetto KEN 22.04.84 1 Chicago 13.10.2013 41 2:03:46 Guye Adola ETH 20.10.90 2 Berlin 24.09.2017 42 2:03:47 Bashir Abdi BEL 10.02.89 1 Rotterdam 16.04.2023 43 2:03:50 Timothy Kiplagat KEN 97 2 Rotterdam 16.04.2023 44 2:03:51 Stanley Biwott KEN 21.04.86 2 London 24.04.2016 44 2:03:51 Kinde Atanaw ETH 15.04.93 1 Valencia 01.12.2019 46 2:03:52 Emmanuel Mutai KEN 12.10.84 2 Chicago 13.10.2013 47 2:03:55 Reuben Kiprop Kipyego KEN 21.08.96 2 Milano 16.05.2021 48 2:03:58 Wilson Kipsang Kiprotich KEN 15.03.82 1 Tokyo 26.02.2017 49 2:03:59 Haile Gebrselassie ETH 18.04.73 1 Berlin 28.09.2008 50 2:04:00 Eliud Kipchoge KEN 05.11.84 1 Berlin 27.09.2015 50 2:04:00 Mosinet Geremew ETH 12.02.92 1 Dubai 26.01.2018
00 -
moultonk wrote:
Ha! The COVID theory is one I hadn't thought of, but it kind of makes sense... as well as everyone getting a year off to heal their injuries, but I have to admit to suspecting the shoes more than before.These graphs are striking and kudos to DataNerd for getting the data together in the first place. If you want to reach out through the comment form or the About page on my site, I'll find some place to post it.
Haha… I was just joking about men benefiting more from contracting COVID than women (i.e. correlation doesn't imply causation). Maybe though haha
I personally think it’s a confluence of events leading to the improvements we see. One of the ideas that’s been mentioned, and that I share, is the idea that the events are becoming more talent dense. This was a dataset of the average of the top 100 performances in the various events after all.
While I think the increased depth of the events is a rather intuitive observation, particularly on the women’s side, one way you could explore this is to look at the distributions of the events (which, not unexpectedly, are significantly left skewed) pre and post super shoe. If the super shoe was the primary contributor to improvement, you’d expect both distributions to maintain approximately the same shape, but with a shift toward faster race times. Alternatively, if the boom in competition is also driving the improvement, you’d see a “reshaping” of the distribution, meaning that it will be less left skewed. This approach could provide a slightly more quantitative backed answer to your question of what type of shift occurred within the top 100 performances recently.
This post was edited 1 minute after it was posted.20 -
Salvitore Stitchmo wrote:
In the late 90's driving a golf ball 300 yards was basically unheard of unless you were John Daly or Tiger Woods - until Woods in particular ushered in shift in training and dedication and now it's hard to make a cut on tour unless you have the clubhead speed to hit it 300+ when you need to.
Golfers driving it farther is pretty much a pure technology play. The combination of the new ball and huge golf heads let you swing 120mph and find your ball. Gym work gets you 20 yards. The ball and club got you 50.
20 -
zxcvzxcv wrote:
Take the 51 top men's marathon times, 2:04 flat and down, and you'll see that they are virtually all within the last decade. A couple of them are accounted for by the Boston tailwinds in 2011, low 2:03, and others are probably dependent in part on drugs, so that the effect of the shoes could have been muddied by the presence of heavily doped athletes prior to 2016 and the emergence of the shoes on the roads. The only non-aided course results in the list prior to 2016 and the shoes are:
Geb 2008, 2:03:59 (and this was the former 5000m and 10000m wr holder, so the big drop was expected when he moved to the marathon), Kipchoge in 2015 at 2:04:00, Emmanuel Mutai 2013, 2:03:55, and 2014, 2:03:13, Wilson Kipsang in 2015, 2:03:23 and 2013 2:03:42, Dennis Kimetto coming from out of nowhere to run 2:03:45 in 2013 and 2:02:57 in 2014, Patrick Makau, 2:03:38, 2011.
Makau was linked to doping according to multiple articles; Kipsang was banned. So, out of the six 2:04:00 or under marathoners prior to 2016, at least 1/3 were doping.
1 2:00:35 Kelvin Kiptum KEN 02.12.99 1 Chicago 08.10.2023 2 2:01:09 Eliud Kipchoge KEN 05.11.84 1 Berlin 25.09.2022 3 2:01:25 Kelvin Kiptum KEN 02.12.99 1 London 23.04.2023 4 2:01:39 Eliud Kipchoge KEN 05.11.84 1 Berlin 16.09.2018 5 2:01:41 Kenenisa Bekele ETH 13.06.82 1 Berlin 29.09.2019 6 2:01:53 Kelvin Kiptum KEN 02.12.99 1 Valencia 04.12.2022 7 2:02:37 Eliud Kipchoge KEN 05.11.84 1 London 28.04.2019 8 2:02:40 Eliud Kipchoge KEN 05.11.84 1 Tokyo 06.03.2022 9 2:02:42 Eliud Kipchoge KEN 05.11.84 1 Berlin 24.09.2023 10 2:02:48 Birhanu Legesse ETH 09.11.94 2 Berlin 29.09.2019 11 2:02:55 Mosinet Geremew ETH 12.02.92 2 London 28.04.2019 12 2:02:57 Dennis Kimetto KEN 22.04.84 1 Berlin 28.09.2014 12 2:02:57 Titus Ekiru KEN 02.01.92 1 Milano 16.05.2021 14 2:03:00 Evans Chebet KEN 05.03.88 1 Valencia 06.12.2020 14 2:03:00 Gabriel Gerald Geay TAN 10.09.96 2 Valencia 04.12.2022 16 2:03:02a Geoffrey Mutai KEN 07.10.81 1 Boston 18.04.2011 17 2:03:03 Kenenisa Bekele ETH 13.06.82 1 Berlin 25.09.2016 18 2:03:04 Lawrence Cherono KEN 07.08.88 2 Valencia 06.12.2020 19 2:03:05 Eliud Kipchoge KEN 05.11.84 1 London 24.04.2016 20 2:03:06a Moses Mosop KEN 17.07.85 2 Boston 18.04.2011 21 2:03:13 Emmanuel Mutai KEN 12.10.84 2 Berlin 28.09.2014 21 2:03:13 Wilson Kipsang Kiprotich KEN 15.03.82 2 Berlin 25.09.2016 21 2:03:13 Amos Kipruto KEN 16.09.92 2 Tokyo 06.03.2022 21 2:03:13 Vincent Kipkemoi KEN 03.01.99 2 Berlin 24.09.2023 25 2:03:16 Mule Wasihun ETH 20.10.93 3 London 28.04.2019 25 2:03:16 Birhanu Legesse ETH 09.11.94 3 Valencia 06.12.2020 27 2:03:23 Wilson Kipsang Kiprotich KEN 15.03.82 1 Berlin 29.09.2013 28 2:03:24 Tadese Takele ETH 03.08.02 3 Berlin 24.09.2023 29 2:03:29 Alexander Mutiso KEN 10.09.96 3 Valencia 04.12.2022 30 2:03:30 Amos Kipruto KEN 16.09.92 4 Valencia 06.12.2020 31 2:03:32 Eliud Kipchoge KEN 05.11.84 1 Berlin 24.09.2017 32 2:03:34 Getaneh Molla ETH 10.01.94 1 Dubai 25.01.2019 33 2:03:36 Sisay Lemma ETH 12.12.90 3 Berlin 29.09.2019 33 2:03:36 Abdi Bashir BEL 02.10.89 1 Rotterdam 24.10.2021 35 2:03:38 Patrick Makau KEN 02.03.85 1 Berlin 25.09.2011 36 2:03:39 Tamirat Tola ETH 11.08.91 1 Amsterdam 17.10.2021 37 2:03:40 Herpasa Negasa ETH 11.09.93 2 Dubai 25.01.2019 37 2:03:40 Tamirat Tola ETH 11.08.91 4 Valencia 04.12.2022 39 2:03:42 Wilson Kipsang Kiprotich KEN 15.03.82 1 Frankfurt 30.10.2011 40 2:03:45 Dennis Kimetto KEN 22.04.84 1 Chicago 13.10.2013 41 2:03:46 Guye Adola ETH 20.10.90 2 Berlin 24.09.2017 42 2:03:47 Bashir Abdi BEL 10.02.89 1 Rotterdam 16.04.2023 43 2:03:50 Timothy Kiplagat KEN 97 2 Rotterdam 16.04.2023 44 2:03:51 Stanley Biwott KEN 21.04.86 2 London 24.04.2016 44 2:03:51 Kinde Atanaw ETH 15.04.93 1 Valencia 01.12.2019 46 2:03:52 Emmanuel Mutai KEN 12.10.84 2 Chicago 13.10.2013 47 2:03:55 Reuben Kiprop Kipyego KEN 21.08.96 2 Milano 16.05.2021 48 2:03:58 Wilson Kipsang Kiprotich KEN 15.03.82 1 Tokyo 26.02.2017 49 2:03:59 Haile Gebrselassie ETH 18.04.73 1 Berlin 28.09.2008 50 2:04:00 Eliud Kipchoge KEN 05.11.84 1 Berlin 27.09.2015 50 2:04:00 Mosinet Geremew ETH 12.02.92 1 Dubai 26.01.2018
Dude, nobody is arguing the shoes haven't made a significant impact and especially on the roads - I don't know what else to tell you.
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