There’s a shift taking place in the soccer analytics landscape, and it’s probably overdue. For the past year or so, expected goals models based on shots have been very much in vogue. But recently, several analysts and commentators – notably Max Odenheimer, Richard Whittall, and myself – have pointed out that every situation on the field has some chance of turning into a goal. The big questions are whether these situations can be measured and, if so, whether the resulting models are superior to existing alternatives. The answer to the first question depends in large part on the quality of…
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Shot quality, shot quantity, and tactics
One of the great things about soccer is that there are many ways to score goals and win games. I’ve been thinking a lot about why teams choose different tactics, and I decided to test some of my ideas with data. The results offer food for thought. Let’s start with two assumptions, which we’ll check against the data later: 1. There is a tradeoff between shot quality and shot quantity. This implies that shot quality isn’t fixed, and there’s a cost to improving it. Teams have at least two ways of creating high-quality shots. One is to keep passing the…
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Breaking down goal difference
Soccer analysts have borrowed and created many ways of measuring the game, but they have yet to come up with the sort of unified theory that relates these metrics to each other. Points and positions can indeed be complicated to decompose, but there is a fairly straightforward way to break down goal difference. Doing so reveals which metrics fit together… and which don’t. Goal difference – the difference between goals scored and conceded – is highly correlated with positions at the end of the season, and arguably a bit less idiosyncratic. It can also be broken down into four simple components. One of these…
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