Baseball Prospectus Glossary
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Refers to a pitcher's wins. In context of a team rather than an individual pitcher, refers to team wins.
"First order wins." Pythagenport expected wins, based on RS and RA.
"Second order wins." Pythagenport wins, based on RPA and RPA Against.
"Third order wins." Pythagenport wins, based on AEQR and AEQRA.
Wins Above Replacement Player is Prospectus' attempt at capturing a player' total value. This means considering playing time, position, batting, baserunning, and defense for batters, and role, innings pitched, and quality of performance for pitchers.
Perhaps no sabermetric theory is more abstract than that of the replacement-level player. Essentially, replacement-level players are of a caliber so low that they are always available in the minor leagues because the players are well below major-league average. Prospectus' definition of replacement level contends that a team full of such players would win a little over 50 games. This is a notable increase in replacement level from previous editions of Wins Above Replacement Player.
Here is an example of the Wins Above Replacement Player spectrum based on the 2011 season:
Excellent - Jose Bautista 10.3
Great - Hunter Pence 5.2
Average -Gaby Sanchez 2.0
Poor - Adam Lind 0.5
Horrendous - Adam Dunn -1.7
WARP components can be found in this article, which also describes 2015 changes to FRAA: http://www.baseballprospectus.com/article.php?articleid=27944
Wins Above Replacement Player, level 1. The number of wins this player contributed, above what a replacement level hitter, fielder, and pitcher would have done, with adjustments only for within the season. It should be noted that a team which is at replacement level in all three of batting, pitching, and fielding will be an extraordinarily bad team, on the order of 20-25 wins in a 162-game season.
WARP is also listed on a player's PECOTA card. The PECOTA WARP listing is designed to correspond to WARP-1, not WARP-2 or WARP-3.
Wins Above Replacement Player, with difficulty added into the mix. One of the factors that goes into league difficulty is whether or not the league uses a DH, which is why recent AL players tend to get a larger boost than their NL counterparts.
WARP2, expanded to 162 games to compensate for shortened seasons. Initially, I was just going to use (162/season length) as the multiplier, but this seemed to overexpand the very short seasons of the 19th century. I settled on using (162/scheduled games) ** (2/3). So Ross Barnes' 6.2 wins in 1873, a 55 game season, only gets extended to 12.8 WARP, instead of a straight-line adjustment of 18.3.
For most hitters, at least, it is just that simple. Pitchers are treated differently, as we not only look at season length, but the typical number of innings thrown by a top starting pitcher that year (defined by the average IP of the top five in IP). We find it hard to argue that pitchers throwing 300 or more innings a year are suffering some sort of discrimination in the standings due to having shortened seasons. This why Walter Johnson has almost no adjustment between WARP2 and WARP3, while his contemporaries Cobb, Speaker, and Collins all gain around 7 or 8 wins.
The percentage of times a team wins one of the two Wild Cards in the simulated seasons.
The percentage of times a team wins one of the two Wild Cards in the simulated seasons.
Walks plus hits allowed per inning pitched.
Whole innings -- complete innings started and finished by the pitcher (no fractional innings are counted)
Wild pitches.
The odds that a team will win the World Series, given its Adj. Playoff Pct and Expected Win Pct.
In order to figure the WS Win Pct, we use the odds ratio to figure out a team's expected win percentage in various playoff rounds, and then use the binomial probability mass function to find the odds of winning a five or seven game series as appropriate.
Expected wins added over an average pitcher. WX uses win expectancy calculations to assess how relievers have changed the outcome of games. Win expectancy looks at the inning, score, and runners on base when the reliever entered the game, and determines the probability of the team winning the game from that point with an average pitcher. Then it looks at how the reliever actually did, and how that changes the probability of winning. The difference between how the reliever improved the chances of winning and how an average pitcher would is his WX.
Expected wins added over an average pitcher, adjusted for level of opposing hitters faced. WXL factors in the MLVr of the actual batters faced by the relievers. Then, like WX, WXL uses win expectancy calculations to assess how relievers have changed the outcome of games.
Expected wins added over a replacement level pitcher. WXR uses win expectancy calculations to assess how relievers have changed the outcome of games, similar to WX. However, instead of comparing the pitcher's performance to an average pitcher, he is compared to a replacement level pitcher to determine WXR.
Expected wins added over a replacement level pitcher, adjusted for level of opposing hitters. WXRL combines the individual adjustments for replacement level (WXR) and quality of the opposing lineup (WXL) to the basic WX calculation.
Walks allowed per 9 innings pitched
The Weighted Mean forecast incorporates all of the player's potential outcomes into a single average, weighted baed on projected playing time. In almost all cases, poor performances are associated with a reduced number of plate appearances. For that reason, they don't hurt a player's team quite as much as good performances help it; the weighting is designed to compensate for this effect (see also Jeremy Giambi Effect).
EXCEPTION: a player's projected PLAYING TIME (and therefore, his counting statistics that are incumbent on his playing time) is taken based on the median of his comparables' performance, rather than the weighted mean. This is designed to mitigate the influence of catastrophic injuries, which are better represented by Attrition Rate.
This exception does NOT affect a player's WARP and VORP forecast, which are calculated per the weighted mean method, treating players who dropped out of the database as having zero WARP/VORP.
A correction made to raw runs when converting them to a standard league to preserve their win value. Define an average team from season games played, league runs per game (9 innings or 27 outs, depending on whether you are using pitcher or batter data), and appropriate adjustments (park, team hitting/pitching, difficulty). "Team" is the effect of replacing one player on the average team with the player we are analyzing. Calculate the pythagorean exponent from (average + team) / games as your RPG entry; calculate winning percentage using the modified pythagorean formula. Now, go backwards, solve for "team" runs, given the winning percentage, an average team that scores 4.5 per game, and a pythagorean exponent of 2.00.
Winning percentage (wins / total decisions)
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