an RAF wing commander and trained accountant named Charles Reep turned his eye for numbers to soccer. Reep, who had become interested in the sport in the 1930s and was fascinated by Herbert Chapman’s pioneering Arsenal team, had returned from the Second World War to find that the tactical revolution he’d witnessed before had stalled.
That doesn’t mean you can’t make predictions, though—and that’s one area where AI could prove particularly useful. The paper demonstrates how you can train a model on data about a specific team and lineup to predict how its players will react in a particular situation: If you knock a long ball into the right-hand channel against Manchester City, for example, Kyle Walker will run in a particular direction, while John Stones may do something else.
As part of the paper, the researchers also conducted analysis on more than 12,000 penalty kicks taken across Europe in the last few seasons—categorizing players into clusters based on their style of play, and then using that information to make predictions about where they were most likely to hit a penalty and whether they were likely to score.
Supersmart algorithms won't take all the jobs, But they are learning faster than ever, doing everything from medical diagnostics to serving up ads.There are echoes here of what Reep tried to do in the 1950s—he used his data to calculate that most goals were scored after moves of four passes or fewer, and his analysis helped usher in a style of long-ball soccer that became the hallmark of the English game for decades.
First action, stop calling football soccer
It’s quite good as it is tbf, just get rid of the racism bit.
hslu_aiml this is for you.
Baseball as well
Should suck the fun and excitement right out of the game... like they did with present-day Baseball and US Football.
its called football damn it
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