Back in 2011 I started a thread about catcher framing based on an article on BPro by Mike Fast, who is currently employed by the Astros. Yesterday, BPro published a new article by Harry Pavlidis and Dan Brooks yesterday. They have come out with a new model, Regressed Probabilistic Model. Bad news for AL East teams, McCann isn't only a very good hitting catcher, he is also excellent at framing pitches. Here's a brief explanation from the article:
Since the beginning of the PITCHf/x era, researchers have calculated framing in several different ways. We are presenting a new method that we will call the "Regressed Probabilistic Model" of framing (RPM for short). In brief, RPM works by calculating the combined probability (and associated run value) that each pitch will be called a strike; summing those probabilities (and run values) across opportunities; attributing those values to a player (catcher or pitcher); and regressing "career" values to the mean.
We will freely admit: If you haven't seen the results of previous framing studies, it can be tough to wrap your mind around the size of the impact of a good or bad framing catcher. These effect sizes are not out of line with what has been reported in the past, but they're still obscenely large. Everyone agrees that Mike Trout was either a deserving MVP or a deserving runner-up in each of the past two seasons, which the stats say were worth close to 10 wins apiece. Our data suggest that over the past five years, the teams that have employed good framers like Jonathan Lucroy, Brian McCann, and Jose Molina have received essentially "free" MVP-caliber seasons from framing alone. (Each of those catchers has been worth about two extra wins per season over that span). This is a staggering amount of value. Add in the fact that these wins are almost assuredly not properly priced into the free agent market, and the difference between having a good framing catcher or a bad framing catcher can make or break a cost-conscious team.