“Buster Posey: Elite Hitter of Baseballs Who Confuses Me More Than I Ever Thought He Would” – A Fragment

Buster Posey Puzzle

It all started with a simple question:

“When Buster Posey one day moves from behind the plate to a corner (infield) office at first base, will his bat be good enough to provide valuable returns while playing a position at which run production is at a premium?” My instincts told me “yeah, probably,” and my subsequent half-assed analytical journey provided neither harsh objection nor resounding confirmation. The largest takeaway was that Buster Posey is a special talent and that we are lucky to have the opportunity to watch him, though this is hardly news to anyone who has watched more than a few hours or baseball-related content during the past three years. Special talents tend to find ways to be special regardless of the position from which they play – Ronnie Lott was an all-pro at cornerback, free safety, and strong safety; Craig Biggio was an all-star at catcher and at second base; Kate Upton has been successful from any number of positions.

So as we attempt to answer this question, are there numbers that can tell us how Buster Posey has performed while playing first base? You’re so glad you asked!

Splits (no, not Kate Upton doing the splits)

Splits are a useful tool for isolating a how a player’s performance is affected by any number of disparate factors. For example, one can separate a player’s production at home from his production on the road and gain some insight into how much a player helps his team while wearing the home whites as opposed to the road grays. OR… a player’s production in each of the months of a baseball season can be collated – one might find that an ordinary player managed to pour it on in August and September last season, then find out that he has had a knack for getting hot in the crucible of the playoff chase throughout his career (before Joe Buck has the chance to inform you he’s a “clutch” performer). On the surface, there would seem to be a split that can immediately and succinctly answer our question: offensive production split by defensive positions played. So, given that the question is (more or less) “is Buster Posey a better hitter while playing first base or catcher?” AND there is a statistic that can be found for free on the internets that parses offensive production by positions played, we are seemingly about to put the issue to bed and not think about Buster Posey until pitchers and catcher report in February. I LOVE EASY MONEY!

Buster Posey Positional Splits courtesy of Fangraphs (click on each to view full-sized)

Traditional Statistics

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Pseudo-advanced Statistics

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What do these position splits tell us? The more traditional stats highlight that he has played over four times as many games at catcher as he has at first base – a disparity that makes quantitative comparisons somewhat difficult to conceptualize. One might also be inclined to believe that 80 games at first base is a fairly small sample size from which to draw conclusions, and one would be correct; however, let’s agree to throw such caution to the wind for a moment. What’s that there at the end? Posey has hit .299 as a catcher and .357 as a first baseman? NOW WE’RE TALKING.

Given the disparity between plate appearances at each position, perhaps we will find the second set of statistics more useful – they are almost all qualitative (ratio-based) as opposed to quantitative. We first see that Posey draws walks and strikes out at roughly the same rate regardless of position – this should not surprise us. Posey makes a lot of contact (good for suppressing strike out totals) and has developed a good deal of patience (roughly 11% of his PAs have ended in walks the past two years – up from roughly 6% his rookie season). The real disparities begin to creep up when one looks at batting average (AVG), on-base percentage (OBP), slugging-percentage (SLG) on-base-plus-slugging-percentage (OPS), isolated power (ISO), and batting average on ball in play (BABIP) – we see that all of these numbers are significantly higher when Posey plays first base. To summarize in layman’s terms: while playing first base, Posey has had significantly more balls fall in for hits (BABIP), which has yielded a higher batting average, which in turn has boosted his OBP and SLG (both of which are heavily constructed on the foundation of batting average); we also see that he has a higher ISO (calculated by subtracting AVG from SLG to ISOLATE how much of the slugging percentage is actual raw power). In short, Posey has done a lot of hitter-things better while playing first base than he does while playing catcher.

While I will not get into what those final four metrics TOO much as they are in-house Fangraphs metrics, I will highlight weighted runs created adjusted plus (wRC+): this fangraphs metric builds upon an existing Moneyball concept called “runs created.” Baseball statisticians realized that traditional run-production statistics such as “runs scored” and “runs batted in” were heavily reliant on the successes or failings of other players to be used as assessment tools – a great player surrounded by poor teammates simply is not going to have the same number of opportunities to score or drive in runs as a player surrounded by talented teammates. Runs created attempts to isolate how many runs a player actually helped generate on all by himself (an explanation of the formulae for the various iterations of runs created can be found here). Fangraphs has its own version of the runs created formula (wRC) which attempts to normalize the ballparks in which the created runs are being compiled (after all, it is harder to score in AT&T park than it is in Great American Ballpark) and offensive climate(s) of the season(s) in question (creating offense was a different proposition for Babe Ruth than it was for Barry Bonds). When comparing to league-average (that is, comparing a player’s wRC to the hypothetical Plain-Jane-Average Major League Baseball player), we can roughly gauge how much more quickly a player generated runs than his most-average of peers – this comparison gives us wRC+. wRC+ sets the league-average baseline at 100 – a number above 100 is above-average run production, and a number below 100 is below-average. Each integer roughly correlates to a percentage point – a player compiling a wRC+ of 115 is producing runs roughly 15% more quickly than the average player. In Posey’s case, he produces runs 34% more rapidly than average as a catcher and 76% more rapidly as a first baseman. We would seem to have our answer, kiddos.


Even a little bit of common sense would suggest that a player’s position is a touch on the circumstantial side. Oh sure, Posey probably has less on his mind as a first baseman (catching the ball) than as a catcher (catching the ball, gameplans and hitter scouting reports, the stuff and confidence of his pitchers that day, the positioning of his infielders) and he undoubtedly takes less of a beating. These factors were certainly on my mind as I began my query. Perhaps Posey can focus a little more on hitting and gets less worn down over the course of games (and, hypothetically, over the course of a season) while playing first base. It is not a stretch to think that these factors would have SOME positive bearing on his offensive production, but a roughly 42% improvement? Something else must be at play.



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