Until data improves, saying exactly what it means is fraught with risk

File photo dated 28-05-2018 of Kylian Mbappe-Lottin, France PRESS ASSOCIATION Photo. Issue date: Friday July 13, 2018. The 19-year-old France winger has been earmarked as the player to fill Cristiano Ronaldo and Lionel Messi's boots, and it is not hard to see why.�See PA story WORLDCUP Hits and Misses. Photo credit should read Adam Davy/PA Wire.
File photo dated 28-05-2018 of Kylian Mbappe-Lottin, France PRESS ASSOCIATION Photo. Issue date: Friday July 13, 2018. The 19-year-old France winger has been earmarked as the player to fill Cristiano Ronaldo and Lionel Messi's boots, and it is not hard to see why.�See PA story WORLDCUP Hits and Misses. Photo credit should read Adam Davy/PA Wire.
0
Have your say

A reminder that football isn’t a jogging contest – so read a tweet in response to the data released after France beat Argentina in the World Cup. The stats showed how little ground had been covered by Kylian Mbappé, below right – he ran only 7.6km, 81 per cent of it at a gentle canter of less than 5kph. His team-mates all ran more, and faster. Yet Mbappé’s had been a man of the match performance.

Data has added a new dimension to a lot of sports, but, as in the above case, it isn’t always clear what it means. The conundrum is particularly acute in cycling, in which there has been an explosion in data and an urgent desire to use it to interpret and understand performances, in particular whether a rider is clean or doped.

BARDONECCHIA - JAFFERAU, ITALY - MAY 25: Christopher Froome of Great Britain and Team Sky / Colle Delle Finestre (2178m)/ during the 101st Tour of Italy 2018, Stage 19 a 185km stage from Venaria Reale to Bardonecchia - Jafferau 1908m / Giro d'Italia / on May 25, 2018 in Turin, Italy. (Photo pool by Tim de Waele/Getty Images)

BARDONECCHIA - JAFFERAU, ITALY - MAY 25: Christopher Froome of Great Britain and Team Sky / Colle Delle Finestre (2178m)/ during the 101st Tour of Italy 2018, Stage 19 a 185km stage from Venaria Reale to Bardonecchia - Jafferau 1908m / Giro d'Italia / on May 25, 2018 in Turin, Italy. (Photo pool by Tim de Waele/Getty Images)

The evolution of data in cycling has been fascinating. In the 1980s the only real metric available to riders was speed. Small handlebar-mounted computers could tell you, thanks to a magnet on the wheel, how fast you were going. With a magnet on the crank they could measure cadence as well.

This data, though interesting, was extremely limited. Speed didn’t tell you whether the road was going up or down, or whether the wind was blowing. You couldn’t judge a performance on speed.

Next, in the early 90s, came heart rate monitors. This heralded a revolution in training; it made it harder to convince yourself that you were training hard just because you were going fast. But, again, heart rate data was limited: it was only really relevant to the individual. You couldn’t compare riders’ performances or even their efforts based on their respective heart rates.

Then came power monitors: devices to measure the watts generated and put through the pedals. Power data is oblivious to whether the road is up or down, whether there is a crosswind, headwind or tailwind, or indeed any other variable that affects performance. It was the game changer.

These days, though other data is used, riders pay most attention to the power they are producing when training and, more and more, also when racing. It has transformed racing because riders and their teams better understand what they can, and cannot, do, down to a small range of watts. Of course, making calculations has always been part of cycling. But there are fewer errors now. Everything is measured and precise. The peloton knows exactly when they have to chase a breakaway and even when they will catch them. Only rarely are there speculative attacks from long range by favourites in the mountains.

There is less spontaneity and there are fewer surprises, the one notable recent exception being at the Giro d’Italia, when Chris Froome attacked alone with 80km and two climbs remaining. Froome was gambling because he had nothing to lose – it looked like he had fallen out of overall contention – but it paid off because his main rival, Tom Dumoulin, was too calculating in his pursuit. It might be too optimistic to hope that this will encourage more risk taking by the favourites when the Tour de France reaches the Alps on Tuesday.

Last week, a fascinating study was published about the benefits of riding in a peloton. The slipstreaming effects are well known, of course, but they had never been accurately measured until a team from the Eindhoven University of Technology, led by Belgian professor Bert Blocken, studied them. Using 121 model cyclists, and with input from a couple of professional teams, the scientists demonstrated that a cyclist in the middle of a pack of riders will experience only 5 to 10 per cent of the air resistance. If the peloton is travelling at 54kph, a rider in the sweet spot – a few rows from the front – will be coasting, barely pedalling, making the equivalent effort of rding at 12 to 15kph if he was on his own.

This will not be a revelation to the riders. They know where the best place to ride is. It can sometimes explain a crash – they are all trying to ride in the sweet spot, they get too close, there’s a touch of wheels, someone goes down. There’s a knack to riding in the peloton that some possess and others, even some leading professionals, do not. Those who struggle with this can waste an awful lot of energy (watts), and also nervous energy, in compensating. Over three weeks of a Grand Tour, that makes an enormous difference.

Riding efficiently in a peloton is one of the skill elements to cycling that is frequently overlooked, just as the endurance element to football can be ignored. Put another way, football is about more than skill and cycling is not solely about endurance. Of course football is not decided by the team that can cover the most ground over a match. But strength and endurance are certainly important over the course of a season or a World Cup.

Inevitably, given the country’s recent history, there was scepticism at the World Cup about the Russian team. The data from their matches was studied like a subliminal text, as though it contained some hidden truth. There may well be clues and hints, but the bottom line is that we cannot determine whether a football team is doping simply from the stats relating to how much ground the players have covered.

This sort of detective work has been the norm in cycling for a few years. Times on climbs are scrutinised, watts are estimated, comparisons are made with previous performances (especially performances we now know to have been drug-assisted), conclusions are drawn.

There has been an explosion in data but the information is not always accurate and it is often incomplete, which is why there are demands for teams and riders to be more transparent. It is why Team Sky released a deluge of information relating to Froome’s ride at the Giro, from WhatsApp messages on fuelling and weight loss strategies to power data. Still the picture painted by the data remains pixellated. It is difficult to factor in everything: a rider’s weight, their efficiency, the wind, road conditions and improvements in bikes and equipment. A big issue is the lack of accurate comparative data with previous eras.

The data will get better and more complete, and the picture it paints will gradually come into focus. Until then, trying to say exactly what it means is fraught with risk, even if we can all agree that football is not a jogging contest.