Silver: Rich data, poor data in sports analytics

From Nate Silver at FiveThirtyEight on February 23, 2015, with mention of SABR member Keith Woolner:

In the 2000 edition of Baseball Prospectus, Keith Woolner identified 23 problems — avenues of analysis that had been dead ends for turn-of-the-millennium statheads. (For instance, No. 10: “Projecting minor league pitchers accurately.”) Woolner named these Hilbert Problems, after mathematician David Hilbert, who in 1900 outlined his own set of 23 vexing mathematical problems that he hoped would be solved in the 20th century.

Of Hilbert’s 23 math problems, just 10 have been answered — not a great track record for more than a century’s worth of work. While Woolner’s baseball problems don’t lend themselves to mathematics’ hard-and-fast proofs, we have become a lot better at, say, “measuring the catcher’s role in run prevention” (No. 3). There’s still a margin of error in calculating how valuable Yadier Molina is to the Cardinals; nevertheless, the progress in baseball is remarkable.

Analysts have made huge strides in “separating defense into pitching and fielding” (problem No. 1): The discovery that pitchers have relatively little control over balls in play has increased the value put on fielding and pitchers’ strikeout ability. And research into “determining optimal pitcher usage strategies” 
(No. 20) has led teams to transform struggling starters into top-shelf middle relievers with ERAs that would make Bob Gibson blush. Indeed, the shift toward pitching and defense reflects the rise of sabermetrics as much as the decline of juiced balls or juiced players.

And all of this has taken 15 years, rather than since William McKinley was president. Sure, teams could still glean more about “assessing the ‘coachability’ of players” (No. 13) or “quantifying the manager’s impact on winning” (No. 22). But baseball analysts can’t complain, unlike their counterparts in other fields.

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Originally published: February 23, 2015. Last Updated: February 23, 2015.