Net Wins: In the Analytics Revolution of the Beautiful Game by Ryan O’Hanlon
Released October 2022.
net profits convinced me of two things. The first is that football lags significantly behind other major sports in integrating data into the game. Second, from an analytical point of view, football is miles ahead of higher education.
For many of us in both education and sport, the dream of making decisions based on data rather than intuition was born in 2003 after reading Michael Lewis’ book money ball. What academic wouldn’t love to be portrayed by an older and wiser Brad Pitt in a future college-focused film written by Aaron Sorkin?
in the net profitsESPN writer and former Holy Cross soccer player Ryan O’Hanlon attempts to explain why soccer has lagged behind baseball, basketball and soccer by relying on analytics for coaching and player decisions.
I’m a huge soccer fan, but my favorite team is the US Women’s National Team (USWNT) and my favorite league is the NWSL. Ask me about the best players in the world and I’ll talk about Sophia Smith, Mallory Pugh, Rose Lavelle, Trinity Rodman, Alex Morgan and of course Megan Rapinoe.
To my chagrin, the world of women’s professional football is entirely absent from O’Hanlon’s account. reading net profits convinced me that I should look more towards the Premier League and I was wondering how I could take a mini sabbatical for the upcoming FIFA World Cup (Men).
But actually, women’s football is simply better. Women almost never dive. I’m not sure if female professional footballers are tougher than their male counterparts (I don’t doubt it), but winning a free-kick just isn’t part of women’s football like it’s the case for men. If O’Hanlon had written a book on football analysis that included women as well as men, net profits would have been a much better book.
Getting past the blind spot of not including women (which is a challenge for me), what does it do net profits What is there to say about the slow analytics revolution in football? And what does the slow pace of data-driven decision-making in football say about higher education?
As it turns out, soccer is extremely difficult to quantify. Unlike basketball, where Data (and Steph Curry) turned every team into three-point shooting machines, soccer is extremely complex. Many in the football world think the game is too fluid, dynamic and random to model.
The most reliable indicator of a particular team’s success isn’t field tactics, player speed, or passing odds — it’s the total amount a team spends on its players. Spend more money, win more games.
The fact that football is not easily subject to statistical decisions does not mean that analytics are absent from sport. O’Hanlon reports that the best teams in wealthy European leagues are pouring more and more dollars into analytics to make decisions about player acquisitions, sales (transfers) and on-pitch tactics.
If Bayern Munich, Manchester City, Barcelona and Liverpool (and I suspect USWNT coach Vlatko Andonovski) can all become football analysis enthusiasts, can’t colleges and universities follow a similar path?
Data-driven decision-making in higher education might pose an even bigger challenge than data-driven football management, but the payoffs for both would be huge.
It is often said that higher education lives in a data-free zone. I do not agree with you. Learning analytics are popping up in more and more places.
I don’t know of any large-scale online program that doesn’t focus on data. The challenge for higher education will be to take our knowledge of learning analytics from designing and running online courses and applying that knowledge to face-to-face/blended teaching.
A key to take away from net profits is that football analysis is driven less by work within clubs and more by outside football data obsessives blogging about the game.
In higher education, we may need more data-obsessed post-secondary analysts (like my friend Phil Hill) to catalyze a learning analytics revolution.
What are you reading?
