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Bayesian Thinking Through Football

How to update what you believe about a team or a player as the evidence comes in, and where the starting beliefs come from.

8 parts Beginner to Advanced

New to this? These parts are Beginner level: 1, 3 and 8.

Start at part 1

Which ground is hardest to visit? Partial pooling

Every club's home record says something about its ground, and a lot about luck. Partial pooling lets the data decide how far to trust each club's own figure. Over 26 Scottish Premiership seasons the clubs differ far less than the raw table suggests, and Hearts still come out on top.

Advanced Part 6

Was 7–0 a freak? Checking a model against the scores it predicts

Seven times since 2001/02 a Scottish Premiership side has won 7–0. A Bayesian model says each was a long shot, but also that a league should see more of them than it does. Checking the model against every score shows where it goes wrong, and how far a simple fix gets.

Advanced Part 7

Four from six. Is the new manager really better?

Rangers sacked Russell Martin after one win in seven league games; Danny Röhl won four of his first six. A Bayesian comparison puts the chance he's genuinely better at about nine in ten, not the near-certainty it felt like, and shows why more games couldn't settle it.

Beginner Part 8