Charles Reep was a retired RAF Wing Commander who loved football.
Specifically, Swindon Town. And it ached to see them losing – something the team made a habit of in the 1949/50 season.
So frustrated was Wing Cdr Reep with one particular performance, that for the second half he pulled out his notepad and started making notes on the players – their movements, their positions, the shape of their play. He identified small changes that he thought could help the team grab a few more goals.
He was decades ahead of his time.
Now, behind the biggest football teams in the world, lies a sophisticated system of data gathering, metrics and number-crunching. Success on the pitch – and on the balance sheet – is increasingly becoming about algorithms.
The richest 20 clubs in the world bring in combined revenues of 5.4bn euros ($7.4bn, Â£4.5bn), according to consultancy firm Deloitte. And increasingly, data is being seen as crucial to maximising that potential income by getting the most from football’s prized investments – the players.
Data and football have had a strained relationship over the years.
Back in the 1950s, Swindon didn’t have much time for Wing Cdr Reep’s approach. But west London side Brentford did.
Prozone’s software offers real-time match tracking, and is used by over 300 clubs worldwide
The club was facing a relegation battle. Wing Cdr Reep was taken on as an advisor – and with his counsel, the team turned their fortunes around and were safe from relegation at the close of the season.
A triumph, you would think – but his approach, despite the measurable success, drew considerable scorn.
His data suggested that most goals were scored from fewer than three direct passes, and he therefore recommended the widely-despised “long-ball” game.
In other words, the ugliest type of football imaginable. Hoof the ball forward, hope you get a lucky break, and poke it into the net.
“Unfortunately it kind of brought statistics and football into disrepute,” says Chris Anderson, author of The Numbers Game, an analytical and historical look at the use of data in football.
“Because people pooh-poohed the idea of the long ball game in football and thought it responsible for the England team not doing nearly as well as they should have for all these years.”
Wing Cdr Reep passed away in 2002. Were he alive today, he would likely be a welcome guest at German football club TSG Hoffenheim, where the “big data” revolution is changing everything about how they prepare for a match.
Through a partnership with SAP – which specialises in handling “big data” for business – the club has incorporated real-time data measurements into its training schedule.
“It’s a very new way of training,” says Stefan Lacher, head of technology at SAP.
The data can be analysed in real-time by data experts – and training schedules can be adapted
“The entire training area becomes accessible virtually by putting trackers on everything that’s important – on the goals, on the posts. Every player gets several of them – one on each shinpad – and the ball of course has a sensor as well.
“If you train for just 10 minutes with 10 players and three balls – it produces more than seven million data points, which we can then process in real time.”
SAP’s software is able to crunch that data, and suggest tweaks that each individual player can make.
“It’s about better understanding the strengths and weaknesses of the players,” Mr Lacher says, “and spending more time working on the weaknesses and making better use of the strengths.
“It’s moving from gut feeling to facts and figures.”
But it’s in the boardroom where football data has an even more critical role to play in the success of the team, says Dr Paul Neilson from football technology specialists Prozone.
“One of the most important things within elite sport is making sure your players are available for training and matches as much as possible, and that is about mitigating injury risks,” he says.
“If you’re doing that you should be able to reduce the risk of physical overload, and reduce the risk of injury.
The data can be relayed to players so they can work on their weaknesses
“When you’re paying players as much as players get paid, it’s very important to make sure they’re on the pitch as much as possible.”
Non-playing players is a massive financial concern for football clubs. The famous example is the case of Jonathan Woodgate, who left Newcastle United in 2004 to join Spanish giants Real Madrid – for a tasty Â£13.4m.
Plagued by injury, Woodgate played for Real just nine times before leaving in 2007. That’s just under Â£1.5m per game – without his weekly wages taken into consideration.
Prozone’s research lab wants to reduce this risk for clubs by using data to analyse body movements and spot, before a physio can, where future injuries may occur.
In young players, analysis of movement can also provide an early warning system for those who may develop career-threatening injuries.
Collecting this data is a sophisticated task. Prozone’s approach relies on a complex network of cameras fitted around the stadium, picking up player movements from several angles at once.
Football managers and coaches like to think it’s their instinct, not geeky data, that gets results. And so, uptake of data analysis in football has been a slow process.
“Football, particularly in the UK, can be a little bit conservative,” says Dr Neilson.
“You look at rugby, and the head coach/manager will often be in the stand for all the game and be surrounded by data and technology and video analysis.
Players at Hoffenheim attach sensors to their kit to monitor their movements
“Compare that with football and the manager is still very much in the dugout, trying to affect the players personally, in terms of instructions and shouting – and very much being part of the sometimes chaotic nature of football.”
This culture clash means there are no managers that prowl the touchline with a tablet – yet. But behind the scenes it’s a very different picture.
Prozone provides intricate data for more than 300 football clubs around the world, including every team in the lucrative English Premier League.
But to make sense of it all requires talent – and Dr Neilson believes that soon, fans will come to admire – or despise – their club’s data scientist in the same way they treat the manager now.
“In a typical football club you have technical people like your sports analysis staff, or sports science staff. They are very analytical, very objective and process driven.
“At the opposite end of the scale you have the decision makers – the chief executive who writes the cheques, the manager that makes the weekly decision in terms of team selection.
“The challenge is connecting those two worlds – so the decision makers trust in that data.”
Sadly, Wing Cdr Reep didn’t live to see the true appreciation of his craft.
And to this day, his long-ball philosophy is criticised by many who say that his data collection was far too primitive to come to such sweeping conclusions.
But nevertheless, his work pioneered what has become a cornerstone of the modern, beautiful game.
Somewhere, in the not-so-distant future, at a football club losing three-nil at home – the fans are chanting “you’re getting sacked in the morning”. Not at the manager, but at the man with the big data.
Follow Dave Lee on Twitter @DaveLeeBBC
Originally posted via “Big Data: Would number geeks make better football managers?”