Continuing my exploration of the recent pro cycling analytics papers, today I’m going to dig into three related papers on measuring intensity to monitor fatigue. The goal is to apply these findings to build an intensity metric that can be applied globally to see which riders have experienced higher or lower intensities at a given point in the season.
I will examine:
The datasets here are nine riders from single cycling team within the 2016 Giro (paper C), twelve riders from a single cycling team within the 2016 Giro and/or 2016 Vuelta (paper A), and twenty riders (presumably from the same team) in a range of World Tour and lower (HC, Level 1) level races (paper B). Paper A also included a baseline training data-set from two weeks prior to each race. The authors gathered power output, heart rate, and relative perceived exertion data from each race and calculated intensity metrics.
Relative perceived exertion (RPE) is of particular interest as it provides a data point which is not publicly available in the ways that power data (for example from Strava) or riding speed is for many pros. For those unfamiliar, RPE is simply the athlete’s assessment of the difficulty of their workout on a scale of 1-10 where 10 is the most difficult.
The RPE was obtained 30 min after the exercise bout based on the question: “How hard was your workout?”pg 2 Sanders and Heijbor (2017)
Intensity in Grand Tours
Paper A analyzes the intensity metrics in four groups: a baseline two weeks prior to a grand tour and then week 1, week 2, and week 3 of grand tours. They find the intensity as measured by RPE increases from 3.5 in baseline training to 6.0 in week 1, 7.0 in week 2, and 7.4 in week 3 – where week 3 is significantly different from week 1 (and all three weeks from the baseline). Power output – both mean watts and normalized power in watts – differed significantly in weeks 2 and 3 from week 1.
This matches what we typically see in grand tours where the first week is easier than subsequent weeks. Eg, of eight stages in the 2016 Giro classified as mountain stages by ProCyclingStats only one was in week 1 (stages 1-7), while three were in week 2 (stages 8-14) and four in week 3 (stages 15-21). This was similar to 2016 Vuelta where all seven of mountains stages came in the final two weeks.
Paper C digs into the differences between different stage types using the same type of data-set just from the 2016 Giro. They divide stages into four types: flat, semi-mountainous, mountainous, and time trials which seem – based on sample size – to largely correspond to the aforementioned PCS categorization. A mountain stage had to either have 35km+ of total climbing and/or a 10km+ finishing climb, while a flat stage could not have more than 13km of climbing and could not end uphill.
RPE by stage types showed flat stages easier at 5.8, semi-mountainous/hilly at 6.5, mountain stages at 7.8, and time trials at 6.8. The gap between mountain and flat stages was significant. Power output also increased significantly between each of the three road stages with mountain > semi-mountainous > flat.
So we have some basic findings:
- Baseline training leading into a grand tour (and presumably in taper mode) is about a 3.5 on RPE
- Flat stages – as are typical in the first weeks of grand tours – rate around 6.0 in RPE
- Hillier stages rate around 6.5
- Time trials will be rated around 6.5-7.0 – presumably higher for those riding them with intent to compete for podium/in team time trials
- Mountain stages will rate closer to 8.0
Influence of Category
This is the most interesting paper of the bunch as it leverages the vast array of races a World Tour team will enter throughout the year to attempt to tease out intensity differences by category. Pro cycling is organized with a the highest level being the World Tour of the most elite ~35-40 or so events including the grand tours and the five one-day monuments at the top of the heap. Below that level is three additional levels of .HC, .1, and .2 races. A World Tour team will typically compete only in the first two levels in a season with maybe a quarter to half the teams in a given race at the .HC level being World Tour teams and a lower percentage being World Tour teams in Level 1 races.
A note, the RPE values in this study are collected on a different 6-20 scale from the 1-10 scale used in the other two papers.
The authors show two sets of a results utilizing RPE; one focusing on one-day races comparing monuments (the five most prestigious one day races) with three other levels of one-day races (World Tour, HC, Level 1) and another for grand tours compared to three other levels of stage races (World Tour, HC, Level 1).
They find a RPE of approximately 18 for the monuments, vs 17 for World Tour races and 16 for HC/Level 1 races. The monuments differ significantly from each of the three lower levels and World Tour also differs significantly from Level 1 races. Monuments tend to be much longer races (268 km on average vs 219 km average for World Tour and <200 km average for HC/Level 1 races) which can explain the differences in intensity.
We do not see a similar stratification for stage races. Of stage races, the grand tours actually average the lowest RPE (14.5), and they stand-out as significantly lower in terms of max/mean heart rate (power output is not significantly different in a high or low sense). This is likely to do with team strategy for which I can’t explain better than the authors.
When comparing single-day races with multi-day races, it is clear that for all the race categories the single-day races are higher in volume, load and intensity compared to the multi-day races. Race regulations are an important contributor to this. Volume and load are higher competing in single-day races because race regulations allow longer races within all the single-day race categories compared to the multi-day race categories.
Furthermore, the higher intensities within the single-day races could be caused by differences in race tactics between the single-day and multi-day races. In a single-day race, a cycling team has one goal and that is to finish as high as possible and thus the whole team (race leader and domestiques) will work without any necessity to hold back for other days to come. Within a multi-day race, a team has different goals per stage and this will depend on their overall goal. For example, when a team brings a sprinter as a team leader to a multi-day race, on the flat stages the support riders will likely have to work on the front of the peloton which will result in an increased exercise intensity and load whilst the support riders for a climber will have a higher exercise load on the climbing stages when working for their leader.
Overall race length (i.e. number of stages) can be a cause for the slightly higher intensity measures (absolute and relative PO, IF) in the 2.1 race category compared to higher level multi-day stage races. On average, the lower category races are shorter and some have only two-race days. The more days a multi-day race consists of, the more riders will most likely aim to spread their energy over multiple days (and aim to minimise energy expenditure on days where it’s possible).pg 11-12 van Erp and Sanders (2019)
Some more findings:
- One day races see significant stratification between monuments > other World Tour races > other one day races where monuments are about 8% higher RPE than World Tour and 12% higher than HC/Level 1.
- Stage races overall do not see this stratification – likely because of strategic pacing the riders implement over the length of the race. I presume stages ridden most competitively will be similar to one day races, while those ridden less competitively will be lower than average. Overall, the level for stage races is about 8% below the HC/Level 1 one-day races.
Implementing an intensity measure globally
These papers provide a solid foundation for a global RPE metric. Difficulty of the profile can increase the RPE by about 33% between a typical flat stage and a typical mountain stage in a grand tour. In addition, monuments and World Tour one-day races will be raced with between 4% and 12% higher intensity than HC/Level 1 one-day races. Stage races on average will not be raced differently by level, however certain stages will be ridden with higher intensity than others such that the combined average is approximately 8% below a HC/Level 1 one-day race.
There’s a big missing piece here; how do we estimate which stages in a stage race were ridden with higher vs lower intensity in stage races?
Different riders will ride differently depending on their team orders/role; eg, a domestique for a team focused on their sprinter like Quick Step will surely have higher RPE on a flat stage where he is responsible for bringing back the breakaway or leading out a sprinter than on a mountain stage where he isn’t protecting a GC leader. If riders could be classified as primarily flat or primarily climbing riders this would be an easier determination to make.
We could also use finishing position and/or presence in a breakaway to estimate higher RPE than normal. Eg, Michal Kwiatkowski’s stage 18 victory in the Tour de France came in a long breakaway over four high mountains where he was in a small group for most of the stage. He certainly had a higher RPE than in stage 17 when he finished 130th in the gruppetto on a similar high mountain stage.
2020 Road World Championships
This idea of recent rider-specific intensity is particularly relevant this week. The Road World Championships are being held with the men’s road race on Sunday – just a week after the Tour de France. While the startlist isn’t completely final, a large majority of the contenders per the betting odds competed at the Tour – meaning 21 days of racing in the last 30 days as of this Sunday. Typically worlds are held two weeks following the Vuelta a Espana (and two months after the Tour) which means the amount of racing in many of the contenders’ legs will be higher than normal.
Top contenders like Jakob Fuglsang, Thomas Pidcock, and Diego Ulissi did not ride the Tour. Fuglsang rode several one-day classics – high RPE events – in August followed by a week-long stage race in mid-September. Pidcock rode the U23 Giro d’Italia at the turn of August into September. Ulissi has ridden two stage races for a combined ten races worth of effort in the past month – most spent riding as one of the leaders. In each case, these riders have roughly half the race days in their legs as co-favorites Wout van Aert and Julian Alaphilippe.