Better Know A Stat - OPS+

Inspired by Stephen Colbert and his Better know a congressman series, TBLA is launching our new "Better Know A Stat" series and today's debut is the baseball reference stat OPS+. OPS+ is a great stat to start with as we use it just about every day, and it incorporates several stats that everyone should know. OB%, Slug%, and OPS. From The Baseball Page Website

OPS+ is OPS adjusted for the park and the league in which the player played, but not for fielding position. An OPS+ of 100 is defined to be the league average. An OPS+ of 150 or more is excellent, and 125 very good, while an OPS+ of 75 or below is poor.

A common misconception is that OPS+ closely matches the ratio of a player’s OPS to that of the league. In fact, due to the additive nature of the two components in OPS+, a player with an OBP and SLG both 50% better than league average in those metrics will have an OPS+ of 200 (twice the league average OPS+) while still having an OPS that is only 50% better than the average OPS of the league.

Many of you understand the definition above but for those that don't let us take a look at each of the statistics being used in the formula, which is basically:

OPS+ = (OBP / lgOBP + SLG / lgSLG - 1) * 100

More information about OPS+ can be found at Baseball-Reference.com, as well as more information about how their park and league factors are calculated.

On Base Percentage

OB% is measured by the sum of hits (H), base on balls (BB), and HBP (hit by pitch)  divided by the sum of times at bat (AB), (BB), sacrifice flies (SF), and HBP. The formula looks like this (H + BB + HBP) / (AB + BB + SF + HBP). If you have been here anytime at all you know that we usually use OB% instead of batting average when discussing the offensive potential of a player.  Each person has loyalties to certain statistics, some have discounted the batting average as obsolete but it is hard for some of us to give up that ghost, however OB% factors in every time that a hitter reaches base safely, not just the time the batter gets a hit and is much more indicative of a the offensive value then batting average. Using Matt Kemp in our example:

(180+52 + 3) / (606+52+6+3) = .352

.350 is good not great but when combined with Kemp's power you have a valuable player. Jamey Carroll and Russell Martin have good OB% but a weak slug% with little speed to go with it, making them much less valuable from an offensive standpoint.

Slugging Percentage

The 2nd part of the OPS is the slug%  which takes the total bases (singles (+1), doubles (+2), triples (+3), home runs (+4) ) divided by at bats. The forumula for slug% would be (Total Bases ) / (AB). Again using Matt Kemp as an example Matt had 122 singles, 25 doubles, 7 triples, and 26 home runs.

((122*1) + (25*2) + (7*3) + (26*4)) / 606  = .490

.490 is great for a center fielder. Only Tori Hunter had a higher slug% then Matt Kemp in 2009 for centerfielders.

On-Base Plus Slugging (OPS)

Adding OB% with Slug% gets you OPS. This statistic is credited to Bill James,  It is designed to merge a player's OBP, which measures how often he gets on base, and his Slugging Percentage (which measures ability to hit for average and power).  Until more advanced metrics came into play this is the stat that many used and still use when trying to determine the offensive value of a player. It has some good things and bad things. Stolen bases are completely ignored and it weights the OB% the same as Slug%. Also it does not normalize for era's and ballpark effects. For example Wes Parker had an OPS in 1970 of only .850 which at first glance is a good year for a first baseman but not really a great year. If you were to sort LA Dodger first baseman by OPS his .850 would be the 10th best offensive season. However when you use a normalized stat like OPS+ his season is actually tied for 3rd best. It was one hell of a season but the numbers are masked behind the tough hitting environment of Dodger Stadium.

That is why we love to use OPS+, it uses OPS but then normalizes the numbers for era and ballpark effects allowing you to compare what someone did in 1970 with what someone did in 2009.  OPS+ still has the same problem of weighting OB% and Slug% equally and more complex metrics have become available to address this but for a quick and dirty way to compare players across leagues and era's, it makes for a great metric.

Below are the 17 greatest Los Angeles Dodger seasons according to OPS+.

                                                                              
Player OPS+ TB Year Age AB HR RBI BB BA OBP SLG OPS Pos
Mike Piazza 185 355 1997 28 556 40 124 69 .362 .431 .638 1.070 *2/D
Pedro Guerrero 181 281 1985 29 487 33 87 83 .320 .422 .577 .999 *7538/9
Gary Sheffield 176 322 2000 31 501 43 109 101 .325 .438 .643 1.081 *7/D
Reggie Smith 167 281 1977 32 488 32 87 104 .307 .427 .576 1.003 *9/8
Mike Piazza 166 308 1996 27 547 36 105 81 .336 .422 .563 .985 *2
Gary Sheffield 164 300 2001 32 515 36 100 94 .311 .417 .583 1.000 *7/D9
Adrian Beltre 163 376 2004 25 598 48 121 53 .334 .388 .629 1.017 *5/6
Reggie Smith 161 250 1978 33 447 29 93 70 .295 .382 .559 .942 *9/8
Eddie Murray 158 290 1990 34 558 26 95 82 .330 .414 .520 .934 *3
Pedro Guerrero 156 308 1982 26 575 32 100 65 .304 .378 .536 .914 *985
Shawn Green 154 325 2002 29 582 42 114 93 .285 .385 .558 .944 *9/D
Shawn Green 154 370 2001 28 619 49 125 72 .297 .372 .598 .970 *9/83
Kal Daniels 154 239 1990 26 450 27 94 68 .296 .389 .531 .920 *7
Pedro Guerrero 154 294 1987 31 545 27 89 74 .338 .416 .539 .955 *73
Mike Piazza 152 307 1993 24 547 35 112 46 .318 .370 .561 .932 *2/3
Jimmy Wynn 151 266 1974 32 535 32 108 108 .271 .387 .497 .884 *8
Pedro Guerrero 150 310 1983 27 584 32 103 72 .298 .373 .531 .904 *5/3

Provided by Baseball-Reference.com: View Play Index Tool Used
Generated 12/30/2009.

The purpose of this series is not for our regular commentators who are already well versed in modern statistics but for those of who have found our site, hang around but don't quite know what we are talking about. This series would be a good time to ask questions and we will do our best to answer them.

Also I'm no expert so if I have made any mistakes or misrepresentations, please let me know so I can fix them.

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