Baseball stats get even more specific

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Dayn Perry

Dayn Perry is a frequent contributor to His second book, "Reggie Jackson: The Life and Thunderous Career of Baseball's Mr. October," is available from HarperCollins Publishers. Read more of his work at the NotGraphs blog.

The statistical revolution came to baseball long ago, and these days it's as much a part of the game as cowhide, sunflower seeds and functionally illiterate Bill Plaschke columns. And despite much fretting to the contrary, the statistical revolution is nothing to fear, loathe or run from.

Statistics enhance baseball. Any baseball argument is informed by the numbers (even if you're using the wrong ones), and any understanding of this great game is made better and deeper by an understanding of the numbers.

So, with those dearly held principles in mind, let's take a walking tour of some of the more illuminating stats that the revolution has produced.

General concepts

BABIP (Batting Average on Balls in Play)

A conceptual knowledge of BABIP is essential to, among other things, projecting the performances of pitchers. Broadly speaking, a pitcher exerts the most control over whether a batter walks, makes contact, hits the ball in or out of the park and hits the ball on the ground or in the air. What becomes of a fair batted ball that isn't a home run, however, is largely a function of luck and defense.

Most often, a pitcher's BABIP will fall somewhere between .290 and .300. If his BABIP deviates wildly from this (and his career norms don't justify such deviation), then you can probably expect him to return to the .290-.300 range the next season.

By extension, when forecasting pitcher performance, it's best to look at his strikeout rate, walk rate, home run rate and groundball-to-fly ball ratio, then make separate estimations of the defense that'll be supporting him. A traditional pitching measure like ERA, of course, misses such vital nuances.

Replacement Level

When it comes to grasping modern statistical analysis in baseball, there's no getting around the idea of "replacement level." Replacement level is, for many useful measures, the baseline to which all players are compared. The name says it all — replacement.

Imagine that a team under tight budget and talent constraints loses a regular contributor to injury or surprise retirement or some other unforeseen phenomenon. To replace him, they'd turn to a prospect who's in need of further seasoning. Or they'd sign a scrap-heap free agent. Or they'd pick up someone off the waiver wire. Or they'd trade for a B-lister who'd require little in return.

All of that is the essence of the replacement player — what you could summon up on short notice and with few resources. The replacement player's level of performance varies from year to year, but it's always measurably worse than the league average. That's the case whether it's a replacement-level position player or pitcher.

The concept is important because it's not the hypothetical average performer to which players should be compared; it's the contingency plan — the replacement level — against which they should be measured.



Think of this as a souped-up version of that old standard, ERA.

ERA+ is simply ERA adjusted for the effects of the pitcher's home park and the league environment. That is, ERA+, unlike plain old ERA, accounts for the fact that pitching in, say, Dodger Stadium circa 1968 is ludicrously easier than pitching in Coors Field circa 2000.

Also, ERA+ is scaled to 100, which means that an ERA+ of 100 equals a league-average ERA after you adjust for park effects. Anything more than 100 is that many percentage points better than the league average (again, adjusted for the pitcher's home yard), and anything less than 100 is that many percentage points worse than the league average.

For example, Mariano Rivera is the career leader in ERA+ (minimum 1,000 innings) with a mark of 202, which means his career ERA is, on a park-adjusted basis, 102% better than the league average (wow). On the downside, Brad Lidge in 2009 posted an ERA+ of 59, which means his ERA was 41% worse than the league mean after correcting for his home park.


Here's where BABIP comes into play for the pitcher. FIP stands for "Fielding-Independent Pitching," and, as the name suggests, it attempts to decouple pitching and defense. It takes into account strikeouts, unintentional walks, hit batsmen and home runs allowed.

Also, FIP yields a number that looks like ERA, so it's in a statistical language the everyday fan can understand. It's useful in that it allows you to evaluate a pitcher in a vacuum, without the good fortune or misfortune of his defensive help getting in the way.



You've probably encountered OPS, which is shorthand for on-base percentage plus slugging percentage. As quick-and-dirty measures go, OPS is a good one, but OPS+ constitutes an improvement.

Like ERA+, OPS+ takes its foundational metric (OPS in this instance), adjusts it based on park and league conditions and scales the final result to 100. Also like ERA+, OPS+ is a useful tool when you want to eyeball production and compare across years and even eras.

For comparison's sake … the top career OPS+ is Babe Ruth, 207. Albert Pujols' OPS+ in 2009 was 188.

VORP   (Value Over Replacement Player)

Simply put, VORP tells you how many more runs a hitter produces relative to a replacement-level hitter. This means "runs" in the theoretical sense — i.e., how he contributes to the scoring of runs with his homers, doubles, singles, stolen bases, walks, etc.

VORP also compares hitters to their positional peers. For instance, shortstop is a more demanding position than third base, which is a more demanding position than right field. And so on. When comparing players across positions, you must take into account positional scarcity. In the circumscribed universe of Major League Baseball, it's easy to find a first baseman who can hit. It's manifestly difficult to find a catcher who can hit. VORP reflects this fact.


(Ultimate Zone Rating)

The problem with fielding errors (and, by extension, fielding percentage) is that they make little account for range. That is, they reward or penalize fielders for making (or not making) the routine plays, but they don't consider the batted balls that were never reached in the first place. In other words, you can't make an error on a ball you never got to, but the ball you never got to matters greatly.

To cite an extreme hypothetical, you field a soft grounder straight at you and so does 1985 Ozzie Smith. Then 1985 Ozzie Smith ranges deep in the hole after a sharp bounder, splays his arms out, dives as far as he's able, snags the ball in the last fraction of webbing and nicks the runner at first. You … barely even lean in the direction of the ball as it zips past you for a base hit. According to traditional fielding measures, you and 1985 Ozzie Smith are equally adept glove men.

On top of that deficiency is the fact that the scoring of errors is a highly subjective process, and it's also one as prone to homerism and "superstar treatment" as anything an NBA ref could come up with. And that brings us to UZR.

UZR makes note of errors, and it also, by dividing the entire field up into 64 different fielding "zones," evaluates a fielder's range. It does all this by calculating what percentage of balls hit into a fielder's zone are converted into outs and then making a host of contextual adjustments (e.g., park, ball speed, pitcher tendencies, etc.). Then that figure is compared with the league average for the position.

You need at least three years' worth of UZR data to make sensible valuations of fielders, but even with those limitations UZR is substantially better than the numbers usually bandied about in discussions of defense.

DER (Defensive Efficiency Rating)

DER is a wonderfully simple statistic (wonderfully simple in conception, anyway) that gives you a nifty snapshot of team defense. Simply put, it's the percentage of balls in play (i.e., fair balls that aren't home runs) a team's defense turns into outs. Home parks and other conditions can create some noise in the numbers, but it's still measurably better than judging teams based on error totals or fielding percentage.

Clutch indicators

(Win Probability Added)

This handy little widget tells you how a hitter or pitcher changes his team's chances with any given play. In other words, it's what a clutch statistic should be. Unlike flawed stats like game-winning RBI or saves, WPA accurately gauges how crucial a situation is and then determines how the player changes the complexion of the game with his performance at that given moment. It's expressed as a percentage. In the case of a positive figure, the player increased his team's chances of winning by that much. In the case of a negative number, he harmed his team's chances by that much.

For instance, when Bucky Dent homered for the Yankees in the top of the seventh in the one-game playoff with Boston in 1978, he increased their chances of winning by 46 percent. Thus, his WPA on that one swing was 46 percent.

Total player value

WAR (Wins Above Replacement)

Here we have a stat that provides a complete picture of player value. For hitters, WAR for the most part takes into account on-base percentage and a modified version of slugging percentage, with OBP weighted more heavily in the sausage-making process. As well, WAR uses UZR to evaluate the defensive contributions (or lack thereof) of those same hitters. The output, then, is an expression of what a player contributes, in wins, over and above the aforementioned replacement level, to his team.

WAR also works for pitchers. In their instances, the WAR calculus includes FIP, the replacement level and home and league contexts.

Last season, Ben Zobrist (!) led all position players with a WAR of 8.6, and Zack Greinke led all pitchers with a WAR of 9.4.

So, viva la revolucion and all that.

More Stories From Dayn Perry

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