We move ever closer to a catcher-framing metric that captures a player's true value.
Last year, Baseball Prospectus introduced our Regressed Probabilistic Model (or “RPM”) for catcher pitch-framing. RPM uses PITCHf/x data to increase the measured accuracy of the actual contributions made by catchers. But RPM also suffered from two limitations. First, because PITCHf/x data was not publicly available before 2008, RPM could only measure catcher framing from recent seasons. Second, it relied primarily on a piecemeal approach to identifying the individual contributions of pitchers, umpires and catchers.
This year, we are pleased to announce an improvement that will address both limitations. We propose to move RPM from a “With or Without You” (WOWY) comparison method to a mixed model we call “CSAA” —”Called Strikes Above Average.” This new model allows simultaneous consideration of pitcher, catcher, batter, umpire, PITCHf/x, and other data for each taken pitch over the course of a season, and by controlling for each of their respective contributions will predict how many called strikes above (or below) average each such participant was worth during a particular season. Although PITCHf/x data is preferable when available, the mixed model (in a revised, “Retro” form) will allow us to live without it when need be, permitting us to project regressed framing of catchers all the way back to 1988, when pitch counts were first officially tracked. This same technique developed for Retrosheet can also be applied to recent minor-league data to provide an even deeper view into the progression and value of this skill.
An experimental broadcast with a sabermetric slant got off to a slow start, but some 'in-game' adjustments gives us hope.
The news of a saber-oriented broadcast option for Game One of the NLCS gave me some mixed feelings. While it is always promising when a major broadcaster embraces "advanced" metrics, it's a little disheartening for it to be a separate offering, rather than something integrated with the primary broadcast.
Host Kevin Burkhardt was joined by a solid panel, including some of our friends. Padres manager Bud Black had the least broadcast experience of the group but offered the perspective of how advanced metrics are actually applied or understood by the men in the uniforms. Well known saber-scribe Rob Neyer was there, a man well-versed in communicating the subject matter at hand, along with two former big leaguers with a strong curiosity and appreciation of sabermetrics, Gabe Kapler and C.J. Nitkowski. Kapler, the former position player, has managing experience in pro ball. Nitkowski was a well traveled pitcher whose career included time in Japan.
Another BP meet-up in Chicago is fast approaching.
Join us in Chicago on Saturday, May 24 at Pizzeria Serio on the North Side of Chicago for three hours of pizza and baseball talk. Our focus will be on the upcoming MLB First-Year Player (Rule 4) Draft.
After two years on the shelf with a shoulder injury, Michael Pineda appears to have recovered his old stuff.
The Yankees got a major boost during the opening week when Michael Pineda took the mound for his first MLB game since 2011. When we last saw Pineda, he was wearing a Mariners uniform and facing a sudden dropoff in velocity, the first sign of the shoulder woes that have kept him out of the big leagues since his days in Seattle.
New pitches and pitchers we've gotten glimpses of already this season.
Spring: a season of renewal and rebirth. Also a time of new pitches and pitchers. A lack of bona fide new arms in the early going has slowed the usual flurry of new PITCHf/x data to ogle, but some established pitchers have made some notable changes.
The best receiving catchers (and the best receiving teams) of the upcoming season.
One of the benefits of our recently released catching defense metrics is they’re essentially ready-to-project, thanks to the regression feature of the model (the "R" in RPM). RPM also gives us two ways to assign value to framing, one using context (the ball-strike count) and one using a flat value (recently adjusted* to ~.155 runs).
[T]he expected runs produced from each plate appearance starting with a strike decreases by .029 runs and increases by .040 for every ball thrown on a first pitch. In other words, having as many of those 0-0 'striballs' called strikes can greatly impact the outcome of the game.
Harry draws on a conversation with former big-leaguer Brian Bannister to extend his PITCHf/x research on changeups from earlier in the year.
A few months ago, I started a series on changeups focused on figuring out the qualities that make a good one. Click the following links to read part one and part two.
If there was a noteworthy finding in the early stages, it was that pitchers who succeed at coaxing ground balls with their changeups generally looked dissimilar from those who missed bats with theirs. The pitchers who can do both are the best. Stephen Strasburg topped that list, so the first waft of the sniff test was passed.