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March 9, 2015 5:00 am

Kershaw Day

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Jon Shepherd

A look at spring training workhorses.

Clayton Kershaw is known for his unrelenting training schedule. In past interviews, he admits that he has difficulty taking off two weeks after a season to let his body heal. Kershaw notes that he feels much worse at the end of a training-free break, so he will only let himself stay idle for a week. His reasoning is that his workouts are already a month or more behind minor-league players—whose season ends in early September—as well as those pitchers on the 20 teams that failed to make the playoffs. He's already behind most players, in fact. Therefore, he must not wait any longer; he begins his throwing, lifting, and running offseason regimen almost immediately.

Kershaw’s approach to training also appears reflected in his spring training workload as he returns to his in-season schedule. In any given year, the spring training innings leaders generally consist of those pitchers, like Kershaw, who by personal preference want the work and the routine; and those individuals for whom teams desire a longer look at, or pitchers who are trying to stretch themselves out for a new role. Last year, Alfredo Simon was a good example of the latter. The Reds decided to try Simon as a starting pitcher after he had pitched for several seasons exclusively as a reliever. The club scheduled him for more innings to establish a new routine for him, as well as to evaluate him as he turned over spring training batting orders.

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Examining an oft-cited method of predicting regular-season success from spring training stats.

This spring, you'll hear stats cited. You'll hear stats discounted, and from some of those discounters, you'll hear other stats cited. Two years ago, Ben Lindbergh and Jon Shepherd looked at one rule of thumb about spring training stats to see if it still held up.

It’s only natural to seek meaning in spring training statistics. By the time spring games roll around, we’re baseball-starved enough to believe anything. We’re also preparing for fantasy drafts, which means we’re always on the lookout for any info that could give us an edge. And contrary to the popular stathead saying, spring training stats aren’t actually meaningless—they’re just less meaningful, compared to a same-sized sample of big-league performance. Any change in a player’s performance should produce a corresponding (albeit small) change in our projection for that player. The more extreme that change in performance is, and the larger the sample, the more that projection shifts.

Read the full article...

Examining an oft-cited method of predicting regular-season success from spring training stats.

It’s only natural to seek meaning in spring training statistics. By the time spring games roll around, we’re baseball-starved enough to believe anything. We’re also preparing for fantasy drafts, which means we’re always on the lookout for any info that could give us an edge. And contrary to the popular stathead saying, spring training stats aren’t actually meaningless—they’re just less meaningful, compared to a same-sized sample of big-league performance. Any change in a player’s performance should produce a corresponding (albeit small) change in our projection for that player. The more extreme that change in performance is, and the larger the sample, the more that projection shifts.

The most commonly cited method for assessing spring training statistics was proposed and popularized by John Dewan, the owner of Baseball Info Solutions. Dewan has devoted most of his analytical efforts to quantifying fielding, but he tackles other statistical topics in his “Stat of the Week” series at the website of publisher Acta Sports. Since at least 2005, Dewan has published an annual list of players whom he thinks stand a good chance to break out in the upcoming season, based on their spring training stats.

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