Unless you have been in a cave or just hate football (soccer to the uninitiated 🙂 ), you know by now that Argentina just beat the Dutch. But did you know how many woodwork ( the goal used to be made of wood and not metal) shots there were – shots that hit the goal but didn’t go in? Or that Argentina made 639 passes compared to 818 for the Dutch? And by the way, Netherland covered slightly more distance than Argentina but significantly more distance with possession of the ball? Or the completion rate of the passes and whether they were long, medium or short? And on and on and on. Big Data has come to football and it may change the game as we know it. I grew up playing soccer(despite what I look like now) and coached a travelling soccer club in Naperville(where the term soccer mom was invented and is fiercely competitive) and all I can remember is get the ball in the goal and stay on sides.
While the analytics movement started with baseball (remember Moneyball) and moved to other sports, the application of data analytics has also reached football in a big way. Here is a small example of how it is being applied to understand not just the effort being expended by a team and each individual player but also the effectiveness of that effort. While Netherlands had a clear lead in ball possession, passes(both attempts and completed), and other categories, Argentina had more attempts on goal, more shots on target, equal number of corners, equal deliveries in penalty area etc. If you knew enough about football, you could look at the post match data and draw a mental picture of what the match was like – and you would come very close? You can tell the style of play of each team (controlled ball possession vs. counter attacks or individual attacks) by just looking at the data? You can develop a counter strategy for each opponent based on statistical analysis.
Thanks to missile tracking technology, the analytics are being applied at an individual level also. STATS is the company that has been tracking every football player in every single match through a system used for tracking missiles. Kopp mentions that Michael Bradley from the US covered 10.4 miles in a game while Lionel Messi covered 6.6 miles for the same amount of minutes in a different game – that’s quite a stark difference. That means Bradley covered 3.8 miles more in just one game – that is a difference of 60%!!! Does that make Bradley a better player-a better athlete? While some of the difference relates to their different positions, the different styles that each team plays, match conditions, opponent etc., it does not explain everything? Clearly, Messi is doing a lot more with his effort in terms of effectiveness than Bradley. His runs are shorter but faster? He is able to conserve energy and then use it for short bursts of activity? His running is often with the ball than without. There are clearly many factors in play but the data does point to the difference between effort and effectiveness. It clearly will make each manager rethink their team composition, their strategy, their training methods etc. etc. Brian Kopp goes on to say that 2 of the top players at the World Cup in terms of distance covered are Americans so clearly the effort is there. But the effort may exact a huge price in terms of energy left to expend towards the end of the game – where many games are decided.
So would you rather have Lionel Messi or Bradley on your team? Are you measuring your people on effort or effectiveness? What have you done recently to understand what competencies your organization needs and put in a training program to develop those competencies? You could have a number of people who are running up and down the pitch expending tremendous effort but not having any impact at all? Do you understand how to measure the effectiveness of your people and put in place a Competency Based Talent Management program?