Data Analytics and Women’s World Cup
In a post-Brexit world, it’s fair to say that the vibe in the UK has been a little… fractious in recent years. But last Summer we were united for a couple of months as we collectively held our breath watching England progress through the World Cup. Whilst overall victory evaded us thanks to a semi final knockout by Croatia, Gareth Southgate’s boys had undoubtedly produced the best tournament performance we had seen in a long time.
If you thought you had to wait another 4 years to crack out your England shirt, you’re wrong. Next month the Women’s World Cup starts and the Lionesses are in it to win it. Whilst these international tournaments are all about galvanising passion and excitement, there is still a level of science and analysis that remains at its core.
Data analytics have become increasingly influential in the world of sport and although football has been slightly late to the party, it is now fully embracing the benefits that data science can bring. Data analytics in football is big business, with organisations such as Analytics FC dedicated to collecting data from games and players and using it to predict future performance. Here are just a few of the ways data is transforming the beautiful game.
One of the ways football is adopting data is by collecting data points to help them strategically scout for potential new talent when the transfer window opens. Nearly every major club has a Head of Analysis nowadays, and they collect information on everything the players do on the pitch from speed and agility to goals and heart rate. These data points are built into a database that clubs can use to search for players with high potential and who could fill a skill gap in the current team. This approach has long been used for baseball scouting in the US – the so called ‘Moneyball principle – and in the last few years it has become increasingly popular in the Premier League.
In 2012, Arsenal paid over £2million for StatDNA, a US company who specialise in sports data analytics. Their small but experienced team analyse hours worth of footage from every football game and collects detailed data points on every player. Their database is now Arsenal’s to utilise; so if Unai Emery is looking for a creative midfielder who is quicker than most and is likely to provide an impressive number of assists, the database can immediately identify the players he should approach. Brighton’s scouting set up also heavily relies on data, which is hardly surprising when considering they’re owned by Tony Bloom. Bloom is a maths whiz and former professional poker player who made his money as the brains behind bet analysis giant Starlizard.
Sports betting has always used a level of predictive analytics to assist in setting odds and picking a favourite to win, whatever the sporting event. For sports such as golf, it’s historically been easier to use data collected from previous performances to accurately hypothesise on the future. Football, however tends to have a lot more variation, and therefore accuracy has been hard to guarantee. But with the advent of wearable technology, actions and results on the pitch are easier than ever to analyse and predict – which is music to the ears of sports betting companies, like the aforementioned Starlizard, who are using this progress in technology to their advantage.
But it’s not just the betting companies that are benefiting from the influx of data coming off the football field. Amateur betters with an understanding of data science are taking predictive analytics in to their hands, beating the bookies (and making some serious money) in the process. A cursory Google brings up hundreds of blogs on the subject, with data aficionados sharing tips and hints on how to build your own statistical models to predict the outcome of games and leagues.
Real Time Tactics
Wearable technology is now common place on the football pitch. Information collected can include distance covered on the pitch, heart rate and general fitness – but these go way further than your average Apple Watch. As balls are now often fitted with sensors, this tech can asses passes completed, the power behind the ball and the number of touches players have had during a game. Insights can be gathered during training sessions and help managers decide who will be in their starting 11 and who will be languishing on the bench. They can also be useful for predicting injury, which can save clubs their money and players their
Data collated during training really comes in to its own when match day arrives. Combined with data from previous games and games played by their opponent, these stats highly influence tactical decisions before and after the game. Coaches can now receive a detailed half time data report, which can help them predict where the game is headed and whether they need to bring on an impact substitute now, or wait until the last 10 minutes of the game when the opposition defenders may be starting to tire. Southgate relied heavily on a data analysis during last year’s World Cup and there is no doubt Phil Neville will also be taking a mathematical approach when he leads the Lionesses to victory this Summer.
Data and the Women’s World Cup
Our Founder Emma has used her own expertise in data analytics to assess the chances of England’s women’s team bringing home the cup.
“The Women’s World Cup gets underway next month and as an analyst and as a huge football fan I couldn’t resist taking a look at the England team’s stats from the She Believes cup in America earlier this year to get an idea of how well they might do. They went on to win it and as of March 2019 are now ranked 3rd in the world by FIFA so expectations and belief are high, can we do even better than the third place we achieved last time?
The team never really bossed possession during the tournament, averaging 50.33% of it over the 3 games but they grew in effectiveness when they did have it with the rate they converted their shots on target into goals leaping from 29% against Brazil to 67% against the USA and 75% against Japan.
They did have a lot of shots against them though, 46 across the tournament compared to the 32 they had, but actually only 6 resulted in goals conceded. Dominating possession more could be the key to a successful World Cup, they are good when they have the ball and do cause teams problems but opponents also seem to have a fair bit of joy against them and know they’ll get chances to score. This seems particularly true in the first half of matches as this is when 67% of the goals against them were conceded. They went behind first in both their first two matches and it’s always harder when you’re having to chase the game. England did also score more of their goals in the first half, 57%, but the pressure is often on in the second half to make up for the goals already conceded.
I would love for England to win the World Cup and I really believe they have what it takes but there are some very good sides to get past first and they’ll need to be at their very best. They have one more friendly on 1st June to refine their tactics further then comes the opening match on 9th June against Scotland, which should be an absolute belter. I can’t wait.”
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