Jamie Capel-Davies, head of science and technology at ITF, says metrics don't mean much if you can't communicate them effectively in time to use them.
“One of the key things we looked at was which metrics matter most and how to communicate them effectively,” he says. “The great thing about the app is that it is very visual and also offers a reasonable level of customization.”
LaLiga uses AI and ML for excellence
LaLiga, Spain's leading football league, uses AI and ML to provide new insights to players and coaches.
With help from Microsoft, LaLiga created a data analytics platform called Mediacoach, which uses Azure infrastructure to collect, interpret and present insights from approximately 3.5 million data points collected per game in near real-time via 16 optical tracking cameras become. These cameras are installed in every stadium in the league to capture data about the positioning of players and referees as well as the movement of the ball.
“With this huge amount of data per month, we are able to offer statistics and reports,” says Ana Rosa Victoria Bruno, innovation manager at LaLiga. “With 112,000 reports in the system and 8 million pieces of information, that’s a huge amount of information for 42 clubs.”
One of the tools also made available to broadcasters for fan engagement is a goal probability model, which uses a number of variables including the player's line of sight (taking into account the positions of opposing players); Distances between ball and goalkeeper and between ball and goal; and the distance and angle to the nearest defender to measure the probability of converting a given scoring opportunity. The calculation also takes into account a player's efficiency indicator, which is based on variables such as the player's goalscoring rate per game and per shot.
Bruno's advice: Form a multidisciplinary team.
According to Bruno, it required a multidisciplinary team of football analysts, business intelligence analysts and the LaLiga analytics team to be successful. “One of the challenges is that we need not only data scientists, but also football analysts, UX experts and coaches to convert this raw data into knowledge,” she says.
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