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Archive of posts filed under the Sports category.

How much can we learn about individual-level causal claims from state-level correlations?

Hey, we all know the answer: “correlation does not imply causation”—but of course life is more complicated than that. As philosophers, economists, statisticians, and others have repeatedly noted, most of our information about the world is observational not experimental, yet we manage to draw causal conclusions all the time. Sure, some of these conclusions are […]

Is a steal really worth 9 points?

Theodore Vasiloudis writes: I’d like to bring your attention to this article by Benjamin Morris discussing the value of steals for the NBA. The author argues that a steal should be a highly sought after statistic as it equates to higher chances of victory and is very hard to replace when a player is injured. […]

Win probabilities during a sporting event

Todd Schneider writes:

The myth of the myth of the myth of the hot hand

Phil pointed me to this paper so I thought I probably better repeat what I wrote a couple years ago: 1. The effects are certainly not zero. We are not machines, and anything that can affect our expectations (for example, our success in previous tries) should affect our performance. 2. The effects I’ve seen are […]

What is it with Americans in Olympic ski teams from tropical countries?

Every time I hear this sort of story: Morrone—listed at 48 years old, which would have made her the oldest Olympic cross-country skier of all time by seven years—didn’t even show up for the 10K women’s classic on Feb. 13, claiming injury. (She was the only one of the race’s 76 entrants who didn’t start.) […]

Econometrics, political science, epidemiology, etc.: Don’t model the probability of a discrete outcome, model the underlying continuous variable

This is an echo of yesterday’s post, Basketball Stats: Don’t model the probability of win, model the expected score differential. As with basketball, so with baseball: as the great Bill James wrote, if you want to predict a pitcher’s win-loss record, it’s better to use last year’s ERA than last year’s W-L. As with basketball […]

Basketball Stats: Don’t model the probability of win, model the expected score differential.

Someone who wants to remain anonymous writes: I am working to create a more accurate in-game win probability model for basketball games. My idea is for each timestep in a game (a second, 5 seconds, etc), use the Vegas line, the current score differential, who has the ball, and the number of possessions played already […]

What’s my Kasparov number?

A colleague writes: Personally my Kasparov number is two: I beat ** in a regular tournament game, and ** beat Kasparov! That’s pretty impressive, especially given that I didn’t know this guy played chess at all! Anyway, this got me thinking, what’s my Kasparov number? OK, that’s easy. I beat Magnus Carlsen the other day […]

How best to compare effects measured in two different time periods?

I received the following email from someone who wishes to remain anonymous: My colleague and I are trying to understand the best way to approach a problem involving measuring a group of individuals’ abilities across time, and are hoping you can offer some guidance. We are trying to analyze the combined effect of two distinct […]

Berri Gladwell Loken football update

Sports researcher Dave Berri had a disagreement with a remark in our recent discussion of Malcolm Gladwell. Berri writes: This post [from Gelman] contains the following paragraph: Similarly, when Gladwell claimed that NFL quarterback performance is unrelated to the order they were drafted out of college, he appears to have been wrong. But if you […]