Power Output by Rider Types

In my last post I introduced simple rider clusters based on a handful of features calculated for each rider from race result data. These clusters divided riders into six groups – sprinters, sprint train, puncheurs, domestiques, climbers, and mountain helpers. Three of these groups are leaders who are more likely to be going for race wins and three are helpers who are assisting the leaders. One follow-up that became possible was to analyze power outputs based on these rider types.

By Time Duration

Leveraging over seven thousand power files, I can link rider types to power outputs over different time durations. I chose to look at 10, 30, 60, 120, 300, 600, 1200, and 2400 seconds which covers the full spread of efforts from sprints to longer efforts like the final of a one day classic or high mountain climb. For each power file I extracted the best power output from these time durations, calculated watts per kg using weights from procyclingstats.com, and adjusted those relative to average for all riders. I had data from 169 riders with at least 10 power files from 2019 and 2020.

An example from four riders with 2019-20 data

An example of the curves produced for four riders are above. Smith packs a better sprint than the other three riders, but tails-off on efforts outside two minutes. Kamna excels on 10 minute plus efforts. De Gendt is second best at pretty much all points. Declercq is well off the highest outputs between 1-5 minutes, but is close on longer efforts.

29% of the data came from domestiques, 29% from mountain helpers, 16% from sprint trains (so 74% from helpers), 12% from puncheurs, 8% from sprinters, and 6% from climbers (so 26% from leaders).

I looked at both the 80th percentile of power output (so the better performances for a rider) and the median. As you would expect, the 80th percentile data produced wider spread between power outputs versus average.

Power outputs by time duration for rider clusters

Sprinters produce over 10% more power than average riders in 10 second efforts – while puncheurs and sprint train riders were both above average here.

Puncheurs were consistently above average at all time periods, while domestiques were consistently below average.

Climbers peaked with about 7% more power than average in 20+ minute efforts, while mountain helpers were about 4% higher than average. At 10 second efforts, climbers were about 13 percentage points behind sprinters, while at 1200 seconds climbers were about 13 percentage points ahead of sprinters.

None of this is earth-shattering information; if anything, this shows the validity of rider clusters based on simply result data because we’re seeing the expected power outputs. Classifying riders as members of sprint train or mountain helpers is a valid distinction; they are producing different power outputs over different time durations.

By Stage Types

We can also break-down overall power output in a race based on the type of stage it is. I’ve simply broken down the races into three types: those ending in a bunch sprint (20+ rider group), non-bunch sprints on hilly parcours, and non-bunch sprints on mountainous parcours. The dividing line between hilly and mountains is roughly Fleche Wallonne or Giro dell’Emilia.

The metric here is relative weighted average power – so power output relative to a rider’s own average across all races. In this case, 120% is basically max effort – the efforts required of a winning breakaway rider or top 5 in mountain stage – and 80% is a low effort day like a flat bunch sprint finish in a grand tour. For example, the three big breakaway days for Neilson Powless in the 2020 Tour de France were 114%, 116%, and 114% efforts, while he did 82%, 89%, and 78% on three flatter days in the bunch.

Climbers have the widest gap between efforts in mountain races and bunch sprint races

Of course, flatter stages require lower power outputs in general for all riders as discussed in a previous post. But, we can identify some significant differences between the clusters. Climbers are clearly different from other clusters in their mountain/bunch sprint outputs, while mountain helpers are clearly different from sprinters/domestiques/sprint trains.

Climber types have the widest gap between performance by parcours. In bunch sprint races they produce ~92% of their average weighted average power. In mountainous races, they are over 105% of their average weighted average power. Domestiques have the narrowest gap between bunch sprint days and mountain days.

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