It’s way past time to move on–I know, I know! But I wanted to add just one more piece to the fielding-measurement picture: the performance of Ultimate Zone Rating, or UZR. I realize now that what I’ve said up to this point might make it look I’m talking only about how Baseball Reference (BBR) computes the fielding component of WAR. So let’s expand the focus a bit. First of all, let’s consider the difference between how FanGraphs and BBR measure the fielding component of WAR. There isn’t much up to 2002. Up until then, they both use as the basis of their formulas Sean Smith’s Total Zone Ratings. Accordingly, they both do a great job in picking up the substantial amount that fielding contributed to averting runs throughout most of the 20th...

Everyone knows (and is correct to believe) that Brooks Robinson is the greatest fielding third baseman ever. But how should all the other major leaguers who’ve manned the hot corner be ranked in fielding skill? This is another topic suited for illustrating the impact of rfield inflation. Three of the next four places on Baseball Reference’s list of all-time position leaders in runs saved are occupied by third basemen who played either most of or their entire careers after the late 1990s: Adrian Beltré, Scott Rolen, and the still active Nolan Arenado. There is thus a high likelihood that the impact of their performances have been overstated. “Rfield inflation” refers to the overvaluation of the consequence of fielding proficiency in the metrics...

I really like OPS. Proposed by John Thorn and Pete Palmer in 1984, it’s still the best indicator of batter run productivity that anyone has devised. At the risk of poisoning this blog with a lethal dose of theory, what follows are some reflections on how I conceptualize OPS and what I regard as the optimal way to construct it. Plus some measurements (phew!). 1. I like OPS because it is an explanatory measure of a hitter’s propensity to generate runes. Not all batting metrics, even good ones, are explanatory. Consider weighted on-base average (wOBA), the offensive component of WAR. wOBA consists of a set of correlations, updated every season, between runs and positive batting events. It would be circular to say that a metric derived from runs...

I’m interested in pitching evaluation metrics (who isn’t?!). Recently, I’ve been trying to understand what drove differences in pitcher proficiency throughout most of the twentieth century. We know that strikeouts are pretty much everything now, but that wasn’t so then. What sorts of factors most influenced pitching proficiency in the 1950s, say, and what is their relative power today? The obvious metric to focus on is “fielding-independent pitching” or FIP.  As an index comprising nothing more than the propensity of a pitcher to strike batters out, walk them, hit them with a pitch, and allow home runs, it’s not surprising that the power of FIP to explain differences in runs allowed has soared over the last three decades or so, as both strikeout...

Argh, I’m just stymied! I’ve been sucked into the BABIP—batting average for balls in play—rabbit hole. At any period in big league history, variation in BABIP and oBABIP (opponent batting average for balls hit in play)—contribute a substantial amount to runs and runs allowed. So naturally, one wants to try to explain them. Voros McCracken is famous for the thesis that pitchers have no impact on BABIP. If a hitter makes contact with the ball, nothing a pitcher has done is going to affect it, making outcomes a mix of chance and fielding quality. Well, for sure, variance in BABIP has historically been substantially influenced by fielding proficiency, as measured by rfield (runs saved by fielding). And I think most would accept now that either pitching...

No, wOBA is not a delicious type of sushi. It is a hitting-production metric that is supposed to be better than OPS and that figures in the calculation of WAR. I thought this post was going to invovle some kind of hyper-theoretical explanation of why, despite being a less successful empirical predictor of runs scored, OPS has theoretical virtues that make me prefer it to wOBA. But I don’t think there’s any need for that. Because as far as I can tell, wOBA isn’t superior to OPS as a predictive measure after all. wOBA stands for “weighted on-base average.” It was devised in the classic work The Book: Playing the Percentages in Baseball by Tango, Lichtman, and Dolphin (TLD), who, as I said, proposed it as a superior alternative to the much...