EXPLANATION OF MANY SABERMETRIC STATS USED IN VARIOUS PLACES ON THE BOARD
Originally, with discussion at:
philliesphans.com/phorum/vie ... hp?t=16967
Q: What are considered traditional baseball stats?
A: Traditional baseball stats usually consist of counts of things (like RBI, AB's, IP's, etc.) or simple ratios (BA, ERA, HR-rate, etc.). Some of the most common are:
Stats that attempt to measure offensive performance: AVG, Runs, RBI's, Hits, Walks, Strikeouts, etc. Some of these are pretty good (AVG, and Walk Rate for example) but the counting stats like RBI and, to a lesser extent, Runs tend to be overvalued by the casual fan (and some baseball organizations). They receive a lot of airtime but are team-dependent to a large extent (for example, if a trained Iguana hit behind three guys with .400 OBP's he could get 100 RBI's).
Stats that attempt to measure pitching performance: Wins, Losses, ERA, Walks, Strikeouts, Saves, Holds, etc. ERA is a very good traditional stat (except for relievers that pitch a lot of partial innings), but Wins, Losses, Saves, and Holds all suffer from external influences.
Stats that attempt to measure fielding performance: Putouts, Assists, Errors, FPCT, etc.
Traditional stats are often worthwhile and germane to an argument, but they rarely provide the best evidence for any interesting argument.
Q: Why do many posters cite modern stats instead of traditional stats?
A: Modern baseball stats aren't really all that modern. They trace back to Branch Rickey (progressive Cardinals' GM in the 20's and 30's, Dodgers GM of the 40's, who I think invented OBP (on-base percentage)and isolated power, at least conceptually). Bill James is considered to be the father of most of the modern baseball stats, and he coined the term sabermetrics to describe the modern, statistical measurement of baseball performance.
So-called modern or sabermetric stats attempt to measure more complicated things, often things that directly impact fundamental questions like 'which of these players is better?' or 'which of these teams is likely to win this year?' They often accomplish this by combining several traditional stats mathematically and analyzing the effectiveness of the stats by complicated statistical methods. These stats (if posters understand them and agree about their accuracy) frequently provide better evidence on interesting questions than traditional stats.
Q: What are some of the more commonly cited modern offensive stats?
A: Here are a few:
OPS-this is the modern stat you'll see cited most frequently (not a Bill James stat). It is derived from adding on-base-percentage, OBP (a very good traditional stat that some argue is modern) and slugging-percentage, SLG. It's a quick way to get a reasonable measure of a player's overall offensive contribution without doing any complex math. It's become pretty universal, now available on ESPN's stat pages and baseball-reference and many others. A decent OPS for a corner OF or 1B is .800, a good one is .900, and a great one is 1.000 or more. Players in other positions have different levels of good or great depending on how challenging their defensive position is (this brings up the concept of the defensive spectrum, a James invention). Shortstops and catchers get the most leeway, followed by 2B, 3B, and CF. Jim Thome's 2003 OPS was .958, and David Bell?s was .579 (lowest in baseball for his number of AB's)
AVG/OBP/SLG-some people avoid using OPS and give batting stats this way. A very good offensive player has a .300 BA, a .400 OBP, and a .500 SLG as a corner OF or 1B (again, some slack given to harder defensive positions).
Runs Created-a Bill James creation that combines offensive stats to measure overall offensive contribution. It can be approximated by multiplying OBP by SLG by AB's. (OPS is a quick and dirty attempt to approximate this) There now exist very complex formulas for getting the exact answers for players (one of the most popular of these is the linear weights methods authored by Pete Palmer, which attempts to combine stats linearly with proper weighting coefficients). Regardless, Runs Created (RC) correlates very, very well with team runs and has a huge pile of evidentiary support. The best offensive players in a league in a given year create about 110-130+ runs, and most regulars create about 60-90. Jim Thome created 125 runs in 2003, while Jimmy Rollins created 76 (good for a SS).
RC's enable a baseball fan to get at least an approximate idea of a player's effect on winning, by using the next entry.
Pythagorean Win-Loss estimates-team winning percentages correlate very closely to team run totals in the following manner: (runs squared)/(runs squared) + (runs allowed squared)] is approximately equal to winning percentage. In modern baseball, that means a player must create or prevent about 9-10 runs to win an additional game.
Equivalent Average (EqA)-another overall measure of offensive performance intended to read like batting average. An average player is .260, good is .280, great is .300, etc. Clay Davenport (Baseball Prospectus) is the inventor (and posts the numbers on the net for free). Jim Thome's EQA for 2003 was .321, Pat Burrell's was .253 (bad for a LF, but not as horrible as some might think), and David Bell's was .216.
Park factors-adjustments for the relative tendency for parks to favor hitters or pitchers. The most important of many adjustments intended to refine offensive and defensive measurements. Baseball-reference and most other modern statistics sites often list park-adjusted and league adjusted figures. The Vet was pretty much a neutral park for most of its history, but has tended to be a pitchers' park in recent years. Coors is a great hitters' park (as pretty much everyone in the world knows) and Shea Stadium is a great pitchers' park. CBP seems to be a good HR park, and favors offense at least slightly (doubles and triples are depressed, at least partially offsetting the HR increase) as of the end of the 2005 season.
Replacement level (or replacement level player) (*from dsc25)- a player who is assumed to be freely available to any team when a fill-in player is needed. Different analysts have different methods of determining the exact parameters of this hypothetical replacement level player, but they all have the same basic concept: the level of production from freely available talent. It's important to consider how many runs a good player produces above that level, not above zero, for many reasons. RARP (Runs above replacement position) adjusts RC's for park, position, and replacement level, and is again available on Clay Davenport's page at Baseball Prospectus.
Stolen Bases-analysts focus on stolen base percentage rather than total number of bases. Runners must steal at least 2 out of 3 bases to add to their offensive value, otherwise the caught-stealings offset the SB's. Analysts recognize a subtle side benefit of SB attempts and other small-ball techniques is that they tend to even out run production from game to game by exchanging big innings for multiple one-run innings.
Rules of thumb: Modern statistical analysts use the many rules of thumb for measuring offensive performance. Here are a few: a batter ideally should walk at least 1 time for every 2 K's, should walk at least 1 time for every 10 AB's, should post at least 70-100 OBP points through walks and HBP's. (Walks are very important to sabermetricians) OBP is somewhere between 40 and 70 percent more important than SLG. Batter's strikeouts don't strongly correlate positively or negatively with runs created, and therefore are usually ignored.
Q: What about situational stats?-I hear them mentioned on broadcasts pretty often.
A: Managers and players use batter-pitcher match-up stats pretty often, and broadcasters often take situational stats to a ridiculous extent (by using arcane situations with very small sample sizes). Lots of statistics are now available on the internet for specific situations. Modern analysts find some of them significant, and some not so. Modern analysts strongly believe in the platoon differential (so lefty/righty situational stats are valued, since they seem to remain somewhat consistent from year to year). Analysts also value home/road splits, and sometimes day/night splits, and monthly splits. Almost all modern analysts completely discount so-called clutch stats like BA/RISP or late-innings-close. These stats are wildly divergent from year-to-year for players and teams, and are considered the product of small sample sizes and luck rather than ability.
Many people in the stat community are watching AVG and OPS split by COUNT fairly closely these days, especially on first pitch and two strike counts. Allegedly, Joe Kerrigan is a big fan of splitting batters' performance by count in order to adjust pitching approach.
Q: What about pitching stats?
A: There's not as much room for improvement in pitching stats, since ERA is already pretty good. Here are a few interesting ideas:
WHIP-(walks plus hits per inning pitched) this stat is seen frequently and is not accorded very high value in the sabermetric community, in part, because of its connection with fantasy baseball (it was one of the original eight categories in Rotisserie League Baseball, I think). It makes a good companion to ERA, which, especially for relievers, can fluctuate fairly dramatically due to lucky or unlucky breaks. Great pitchers have WHIP?s below 1.200, good pitchers between about 1.200 and 1.300, average 1.300-1.400; worse than 1.400 is pretty mediocre. Millwood's WHIP was the best among starters on the 2003 Phils team at 1.224 (11th in the NL), with Padilla and Wolf also among the league leaders at 1.240 and 1.245.
BAA or OBA-(batting average against or opponent's batting average)-a good stat, easy to interpret. Millwood, .232; Padilla, .230; and Wolf .219 were the Phils 2003 numbers.
OPSA-(OPS against) a better stat than BAA but harder to find (although it is available on ESPN). Examples from the 2003 Phils: Millwood, .691; Wolf, .713; Padilla, .726. Anything under about .740 is pretty good for an NL pitcher.
K/BB and K/9-rather than just count strikeouts, statisticians prefer to compare them to walks and to innings pitched. A good pitcher has a K/BB ratio above 2/1 and a K/9 IP ratio of at least 5 (James did a famous study where he compared pitchers who were equally successful in ERA and Wins but who diverged on K/9 rates and found that pitchers with K/9 rates below about 4.5 almost never had subsequent success.) Minor league followers use both K/BB and K/9 extensively to evaluate prospects. Top prospects should have K/9 of 9 or over in the minor leagues. Brett Myers' minor league K rates were low for a top prospect, and that is why many stat-oriented Phils' Phans are still skeptical about him in 2003 (but hopeful, seeing his K-rate improved dramatically).
The next two stats are 'improvements' for ERA's
Component ERA-a recent Bill James stats that uses the same general principle of RC (above) to estimate how many runs a pitcher 'should' have given up in the innings he pitched. This is a slightly better predictor of pitcher's subsequent performance than pure ERA.
DIPS ERA ($ERA, sometimes Indicated ERA)-perhaps the most controversial modern baseball stat, DIPS ERA is the brainchild of Voros McCracken (inventor of defense independent pitching statistics, thus DIPS), based upon the counterintuitive but statistically well-supported hypothesis that pitchers have little to no control on what happens to batted balls in play (other than HR's). DIPS ERA is calculated solely from the three 'true' pitching outcomes (BB, K, and HR allowed), with adjustments for quality of defense and park effects mathematically recombined with the true outcomes to produce a stat that mirrors ERA. DIPS ERA is a much better predictor of pitchers' subsequent performance than simple ERA. Millwood's DIPS ERA in 2003 was 3.71, Padilla's was 4.19, and Wolf's was 4.36. Cormier's was 3.12.
PRAA (pitcher runs above average), PRAR (pitcher runs above replacement), Runs Prevented, ERSAA (earned runs saved above average) etc.-these and other stats try to measure how many runs a pitcher saves versus average or replacement. Park adjustments and defensive adjustments are employed in many of these stats. ERSAA for 2003 Phillies pitchers were 24 for Cormier, 16 for Padilla, 13 for Adams, 8 for Millwood, and 2 for Wolf.
ARP (adjusted runs prevented)-used for relievers, an interesting stat derived from play-by-play accounts of the games which calculates runs prevented by employing data tables for expected runs (how many runs SHOULD score from an inherited bases loaded, no outs situation, for example, versus how many runs did score). Data tables are park and team adjusted, but NOT adjusted for lineup position, which would require an immense amount of data. Cormier's ARP was 30.2, Mesa's was -19.8, and Adams was 10.1.
Leverage Index-a tangotiger (well known internet sabermetrician-see links below) idea for comparing the contributions of relief pitchers, this one also derived from play-by-play accounts and focusing on relief pitcher's increased value due to how the pitcher is used in game situations. All game situations are weighted by leverage, average being 1, the highest (leading by one run, runners on second and third, one out in the ninth) being 10. Ratings come from comparisons of win expectation grids. Closers have the highest leverage indices in general, approaching 2 (meaning each inning the closer pitches is worth 2 'normal' innings). From 1999-2002 the highest leverage index belonged to Troy Percival at 1.87, Jose Mesa was at 1.43, and Tim Worrell was at 1.03.
Two other interesting stats that are mentioned occasionally: Quality Starts (QS's) and game score. A quality start is when a pitcher goes 6 or more innings with an ERA of 4.5 or under-this gives a quick and dirty idea of how often a starter keeps his team in the game. Game scores are computed from a table of rules (adding points for good things, subtracting for bad), with 90-100 point games being just about perfect, and an average start being around 50. Additionally, a useful rule of thumb for adjusting ERA is that a pitcher should be held responsible for about half of the unearned runs he gives up.
Q: What about fielding stats? Aren't they pretty meaningless?
A: There are no fielding stats that describe fielding skill broadly and show as much year-to-year correlation as the best offensive stats, but some modern fielding stats are pretty good. Even the old classic Fielding Percentage (FPCT or PCT) gives a decent idea of what it's intended to measure, how sure-handed and accurate-throwing a fielder is, and correlates well from season to season and with wins. Here are some of the modern stats:
Range Factor (RF)-a simple count of the number of plays made per game (a Bill James stat). This was the first attempt historically to get at the difference between a high-percentage fielder and one who got to a lot of balls. The argument for its significance is that since almost all fielding percentages are quite high, the best and worst percentage fielders are separated by 10 or 15 plays per season, but the difference in total chances can be as high as 100 plays or so in the same season. RF is subject to many external influences, and thus is more important historically than as a current analysis metric.
Zone Rating-a new counting stat, in which multiple scorers at each ballpark assign all batted balls to zones and count the number caught in each zone by each fielder. Fielders are then assigned percentage ratings based on the number of balls converted into outs in each zone with respect to number of balls that could reasonably be fielded (according to very specific criteria). ZR's are pretty good defensive stats, but have several weaknesses-they omit line drives and pop ups for IF-s, contain no adjustment for DP pivot ability, do not consider outfielders' arms, and are not applicable historically. Judgments are still too subjective (which balls 'should' be fielded?) and zones are not optimally shaped (twenty six pie shaped wedges).
UZR (ultimate zone rating) and UZR Runs-an improved zone rating obtained by using more and better shaped zones, categorizing errors, and adjusting for the run values of outs and unplayed balls. Still not historically available, and still flawed with respect to IF fly balls, outfielder throwing, catching thrown balls, and pivot ability. It's still probably the best widely accepted and available fielding metric intended to measure range, certainly the best yet constructed from the STATS, INC. play-by-play data-its year-to-year correlation for fielders is about what BA is for hitters (good, but not as good as OPS and the various RC's). Mitchel Lichtman, the inventor, (and the other folks at baseballprimer.com) are still in the process of tweaking the stat to improve correlation, but improvements at this point are small.
Defensive Win Shares (DWS's)-a new Bill James stat customized by position, a subset of Win Shares (below). Defensive Win Shares measures fielding on an arbitrary 4-3-2-1 weighting of four varying factors for each position, and uses creative, team-wide and league wide methods to get at proxy measurements for several hard to quantify categories (How good is a 1B at catching bad throws? How does the OF range affect IF assists?, etc.). A disadvantage is DWS's are not controlled for playing time, so they must be adjusted for part-time players like Marlon Byrd in 2003.
Probably the best way to employ fielding stats is to look at all of them for a particular player, and compare that player to the other players in the league. I'll do it here for 2 Phils (mostly in 2002, since 2003 numbers are not available to me in many cases):
Jimmy Rollins
Fielding Pct. .980 (T1/15)
Range Factor 4.58 (8/15)
Zone Rating .861 (4/15)
UZR .724 (13/15) (2003)
DWS's 6.49 (6/15)
Bobby Abreu
Fielding Pct. .981 (7/10)
Range Factor 1.92 (10/10)
Zone Rating .929 (1/10)!
UZR .755 (source unsure) (5/8) (2000-2003 weighted)
DWS's 2.17 (9/16)
Q: Are there any modern team-level stats (other than simply computing the ones above for a whole team)?
A: Team level stats don't get quite as much attention-offensively, team runs is a great summary stat, and ERA or runs against is a great summary defensive stat. At the team level, one tends to look at deviations-in other words, does the team score more or less runs than it should (via runs created) or win more or less games than it should (via Pythagorean projections)? The Phils have been on the bad end of these stats lately, while the Braves have been on the good end. One team stat that gets some play is
DER (defensive efficiency record or rating or ratio)-this is just the (sometimes park adjusted) percentage of balls in play that are converted into outs by the defense. It is considered a very good measure of how good a defensive team is, much better than total errors. The Phils' unadjusted DER for 2003 was .7160 (meaning 71.6% of balls hit into the field of play against them were converted into outs), 5th in the league for the second consecutive year, above the NL average of .7101.
Q: Are there any all-encompassing stats that give a good idea of how effective any player is, taking into consideration offense, fielding, and pitching?
A: Probably the most frequently cited 'overall' stat is Bill James' Win Shares (WS).
Each win share represents 1/3 of a team win, and is obtained from evaluating offensive, defensive, and pitching contributions with various modern stats. The Phils were led in WS's last year by Jim Thome with 30 and Bobby Abreu with 28. League leaders were Albert Pujols with 41, Barry Bonds with 39, and Gary Sheffield with 35. Eric Gagne was the league's leading pitcher with 25. Win shares are controversial outside the sabermetric community because of their complexity, and inside the community because of the seemingly arbitrary nature of some of James's choices (such as excluding loss shares and the choice of zero-level).
Q: What links can I use to find these stats, and the methods for calculating them?
A: For the more mainstream stats, espn is pretty good -- sports.espn.go.com/mlb/statistics
Here are baseballprospectus's articles (best sabermetric site):
baseballprospectus.com/current/
Lots of info is at baseballprimer (but you must search through the articles):
baseballthinkfactory.org/
Traditional stats (and some modern ones) for all players historically at baseball-reference:
baseball-reference.com/
Win shares at:
baseballgraphs.com/ --for 2003
baseballtruth.com/bbt_winshares.htm --for 2002
Other interesting sites:
baseball1.com/c-sabr.html --Sabermetric Articles
geocities.com/tmasc/ --tangotiger on baseball
diamond-mind.com/weblog/index.htm --diamondmind baseball
retrosheet.org/ --best historical day-by-day info
mb2.theinsiders.com/fbaseballfrm8 --a pure sabr board-pretty deep stuff
bluemanc.demon.co.uk/basebal ... tracts.htm --baseball contracts (not sure this is up-to-date anymore, but contracts are now on usatoday)
sports-wired.com/players/default.asp --stats with minor league numbers
baseballamerica.com/today/Stats/index.html --absolute must for minor league fans
hardballtimes.com --home of some of the best baseball writing anywhere (especailly Aaron Gleeman's stuff)