Baseball Prospectus: A mixed approach to measuring catcher framing

From Jonathan Judge, Dan Brooks and SABR member Harry Pavlidis at Baseball Prospectus on February 5, 2015:

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.[1] 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.

We’re excited to tell you what a mixed model can do and some of the insights it gives us on catcher framing. But, in addition to telling you what we’ve found, we’re going to spend a fair amount of time telling you what we did and how we did it. We want to explain in detail how mixed models can help with sports modeling, and why we think they need to start being used more often.

In particular, we are hoping for your feedback. Baseball Prospectus has some of the smartest readers in the industry. Mixed models are under continued study and development in the statistical community. By working together, we can develop a better, shared understanding of how mixed models work in the sports context, to the ultimate benefit of all.

Read the full article here:

Originally published: February 5, 2015. Last Updated: February 5, 2015.