I received a copy of “Who’s Bigger?: Where Historical Figures Really Rank,” by Steven Skiena, a computer scientist at Stony Brook University, and Charles Ward, an engineer at Google. Here’s the blurb I gave the publisher: Skiena and Ward provide a numerical ranking for the every Wikipedia resident who’s ever lived. What a great idea! […]

**Sports**category.

## Quantifying luck vs. skill in sports

Trey Causey writes: If you’ll permit a bit of a diversion, I was wondering if you’d mind sharing your thoughts on how sabermetrics approaches the measurement of luck vs. skill. Phil Birnbaum and Tom Tango use the following method (which I’ve quoted below). It seems to embody the innovative but often non-intuitive way that sabermetrics […]

## What’s the algorithm, Kenneth?

I can’t figure out what’s the deal with the bars for Corners. The bar labeled “7” is much less than 7 times the bar labeled “1.” At first I was guessing that maybe they’re not counting the numbered part in the bar width (which would be a pretty weird choice) but that wouldn’t work for […]

## World Cup pseudo-science

Lee Sechrest pointed me to this news article by Vitomir Miles Raguz, “Brazil Won’t Win the World Cup. A European team will win again thanks to training and statistical analysis.” Hmmm . . . “statistical analysis.” This Raguz character better coordinate stories with Nate; it seems that the statistical experts are disagreeing . . . […]

## 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 […]