In sports, score is a tally of the total points earned by competitors during a game. Many competitive sports place a premium on scoring more than your opponents, which is known as running up the score. This is a good thing, as long as the players are giving it their all and not taking shortcuts that could cost them a chance at winning the competition.
There is growing interest in quantitative analysis and modeling of sports, but few systematic efforts have been made to understand how the timing and occurrence of within-game events shape overall gameplay. The current dataset we examine, unique in its scope (every league game over 9-10 seasons) and breadth (four sports), provides a rare opportunity to study these questions in depth. We find that the tempo of scoring events – how quickly a team scores a given event – is remarkably well-described by a Poisson process, and that this pattern is common across all sports. We also investigate the dynamics of lead-size in scoring, i.e. the probability of a team winning the next scoring event while leading, and find that this probabilty effectively increases with lead size in football, hockey and basketball.
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