Impact of Aging on Performance

Like all physical competitions, cycling is impacted by aging. Younger riders improve their race craft, get access to better coaching/training, and physically mature. Older riders suffer injuries and physical deterioration and succumb to mental pressures of years spent training, travelling, and competing. Younger riders get faster and smarter. Older riders get slower and more worn-down.

Research on many team sports indicate varied “peak” ages for players between early 20s and 30s for different sports. For example, this Baseball Prospectus piece reviews three different approaches and finds somewhere between 26-28 as peak age for hitters. This CJ Turturo piece examines the impact of aging in NHL hockey and finds age 22 as peak for forwards, age 24 for defenders, and age 27 for goalies (part II of that document). Others in studies quoted by Turturo have found 25 for forwards, 22 for defenders, and 24 for all skaters. In 2013, I found golfers peak in their early 30s, which makes sense as golfer is less of an physically demanding sport compared to baseball or hockey. In a later study, I found different aging curves for different skillsets within golf.

I applied similar methodology to these studies above to identify the aging curve in cycling, from which we can derive a peak age and determine how much we should expect young cyclists to improve and old cyclists to decline. Using the delta method where a rider season is compared to the following rider season identified a peak around 26-27 with riders improving before that age and declining after that age. Using the GAM method where a curve is fit to all rider careers identified 26-28 as the peak with riders improving before those ages and declining after 28. The two methods differ in the steepness of the aging curves; delta method shows a steeper curve of improvement < age 25, while GAM method shows a less steep curve of improvement at those ages and a much sharper decline from age 35 onwards.

Methodology and Data

I gathered PCS points per season (raw total) for each rider between 2010 and 2021. PCS points are awarded for race finishes, GC finishes, and points/mountains jersey finishes. The top points scorers tend to reflect who is considered the top riders, but in my opinion they overweight success in one day races and underweight success in stage races (in the individual stages). Nevertheless, they are a well-accepted and discussed data point which is available consistently going back over a decade.

One thing to consider is accumulating PCS points is part performance and part opportunity. A rider who at age 22 races for a Continental level team as the leader in U23 races and at age 23 races for a World Tour team as a domestique will have fewer opportunities to earn points (though improved performance may cancel that out and there are always freaks like Pogacar and Evenepoel).

I also adjusted points earned in 2020 and 2021 to account for the impact of Coronavirus on races being held. 2020 had 14% fewer points earned and 2021 had 3% fewer points earned than an average season.

Important to note: I am using age on June 30th of that season as the age for that season when binning, but otherwise am using continuous ages relative to that June 30th date. Eg, Peter Sagan (January 1990 DOB) is considered as a discrete age 32 in 2022 (as he will be 32 on June 30th) and a continuous age of 32.4 in 2022 (as he will be 32 and 5 months on June 30th). Some other websites report current age and/or use discrete ages which will make ages look lower.

DELTA METHOD

For the delta method, I simply compared points accumulated by a rider in year 1 to those accumulated by that rider in year 2. I used the rider’s age on June 30 of year to determine the rider’s age for that season. The delta method just measures the change between year 1 and year 2, averages across all riders at that age, and ascribes the total average change to aging. My yearly age samples for seasons in the mid-20s were over 1500 and were over 500 for all seasons between 20-33 and over 100 for all seasons between 19-38.

Riders improved their PCS points from 19-20, 20-21, and 21-22 by an average of 88% (eg, 100 points to 188 points). Age 22-23 and 23-24 earned improvements of an average of 38%, followed by 15% from age 24-25. At that point, performance was fairly steady from 25-26 to 28-29 at between up 5% and down 4%. The peak age seems to be from 26 into 27.

Performance starts declining more significantly as a rider moves into their 30s (an average of -12% down for 29-30, 30-31, 31-32, 32-33, and 33-34). The sharper declines follow that, averaging 25% down from age 34 onwards.

GAM METHOD

For the GAM method, I built a non-linear model which aims to approximate the average aging curve for the full population of riders across their career. The model is in the form of PCS_PTS ~ s(age) + rider so that the overall model finds the average curve over a career; the rider term allows for the height of the curve to vary between massively successful riders like Froome and Cancellara and lower level riders who have scored few points. I included all seasons where riders were between 19 and 38 years old (the ages for which I had > 100 rider samples) and all riders with 4+ seasons in my 12 year sample (using 4+ or 6+ seasons did not impact results).

The aging curve produced was very similar to the delta method. What differed was that the growth curve for riders at 23-24 and under was also much shallower (average of 30% from 19-20, 20-21, 21-22 instead of the 88% from delta method and average of 15% from 22-23 and 23-24 instead of 38% from delta method). The decline curve was sharper after age 35 with 35-36, 36-37, and 37-38 meaning an average decline of 48% instead of 25% shown by delta method.

This GAM method graph should be interpreted slightly differently as the average progression for a rider throughout their career. The Delta method graph just shows the average change in points season to season at each age. Notably, older ages feature better riders (eg, age 34 is actually the peak for average PCS Points per season because you’ve filtered down to riders who have aged better than the average rider).

What does this mean for 2022?

Summarizing the results of these two approaches, we can see 1) riders tend to improve in earning PCS Points thru age 24 into age 25, 2) riders tend to earn similar PCS Points from age 25 through age 29, and 3) riders start declining in PCS Points earned from 30 onwards, accelerating from age 32-33 onwards.

Among top riders who are in that age 32-34 range we have sprinters like Elia Viviani, Giacomo Nizzolo, and Matteo Trentin, punchier riders like Diego Ulissi and Ion Izagirre, and climbers like Mikel Landa, Primoz Roglic, and Rafal Majka. The most prominent rider who switched teams over the winter was Peter Sagan who will be 32 for the entire season. Some of these riders will decline – some precipitously – while others will fend off age and produce just as strong as season as 2021.

In the aggregate though, these aging curves suggest teams which are more comprised of 30+ year old riders will fall-off more than those with younger riders. Among the World Tour teams, Israel Start-up Nation had the oldest roster in 2021 and now again in 2022 with their 30.8 year old average. Based on this aging curve, their riders are set to decline by 5% on average from their 2021 point totals. Since last year, their major additions were Nizzolo (age 33), Jakob Fuglsang (age 37), and Hugo Houle (age 31).

Team TotalEnergies races at the Pro Tour level and is the team which signed Peter Sagan (along with several of his mid to late 30s support riders). Their average team age ballooned from 28.9 in 2021 to 30.6 in 2022. They are also in-line for a 5% overall decline in their performance versus 2021. Those aren’t huge declines, but considering the salaries being paid to stars like Nizzolo, Fuglsang, and Sagan and the performances expected, they will be fighting against that current to produce.

The younger teams most likely to improve collectively in 2022 mostly race at that Pro Tour level. Equipo Kern Pharma, Sport Vlaanderen, UNO-X, and Bardiani will all average under 25 years old in 2022. Those four are projected to improve just by aging by 7-9% in 2022 versus their 2021 performance.

However the most interesting team is Team DSM in the World Tour. DSM has added eight riders in 2022 – six of them under 25 – while they lost their two oldest riders from 2021. They are the only World Tour team with an average age under 27 in 2022 (25.7 years old). They are expected to improve collectively by around 5% versus 2021 performance by the aging curve. Riders like Kevin Vermaerke, Thymen Arensmen, Mark Donovan, and Andreas Leknessund all fit the bill of having previous World Tour experience + being aged 23 and under.