| Batter | OBP | SLG | pLI | WPA |
|---|---|---|---|---|
| David Wright | 0.373 | 0.506 | 0.93 | 1.22 |
| Damion Easley | 0.337 | 0.453 | 0.93 | 0.84 |
| Jose Reyes | 0.387 | 0.439 | 1.03 | 0.83 |
| Carlos Delgado | 0.305 | 0.435 | 0.97 | 0.71 |
| Ramon Castro | 0.349 | 0.538 | 0.84 | 0.29 |
| Ruben Gotay | 0.377 | 0.514 | 1.13 | 0.14 |
| Julio Franco | 0.328 | 0.260 | 1.17 | 0.03 |
| Joseph Michael Smith | 0.000 | 0.000 | 0.18 | 0.00 |
| Dave Williams | 0.000 | 0.000 | 0.34 | -0.01 |
| Sandy Alomar Jr. | 0.250 | 0.500 | 0.22 | -0.01 |
| Chan Ho Park | 0.000 | 0.000 | 0.84 | -0.02 |
| Shawn Green | 0.325 | 0.428 | 0.94 | -0.04 |
| Lastings Milledge | 0.000 | 0.000 | 0.46 | -0.06 |
| Jason Vargas | 0.000 | 0.000 | 1.37 | -0.09 |
| Ricky Ledee | 0.310 | 0.389 | 1.11 | -0.10 |
| Aaron Sele | 0.000 | 0.000 | 1.29 | -0.11 |
| Jose Valentin | 0.297 | 0.388 | 0.97 | -0.18 |
| David Newhan | 0.306 | 0.291 | 0.98 | -0.23 |
| Tom Glavine | 0.333 | 0.323 | 1.04 | -0.24 |
| Mike Pelfrey | 0.083 | 0.083 | 1.07 | -0.25 |
| Jorge Sosa | 0.190 | 0.105 | 0.71 | -0.26 |
| Carlos Beltran | 0.340 | 0.477 | 0.92 | -0.35 |
| Oliver Perez | 0.250 | 0.250 | 0.94 | -0.38 |
| Orlando Hernandez | 0.192 | 0.269 | 0.92 | -0.38 |
| Endy Chavez | 0.336 | 0.407 | 0.99 | -0.41 |
| Ben Johnson | 0.233 | 0.222 | 1.15 | -0.54 |
| John Maine | 0.194 | 0.097 | 0.73 | -0.54 |
| Carlos Gomez | 0.303 | 0.333 | 0.77 | -0.57 |
| Moises Alou | 0.374 | 0.445 | 1.02 | -0.75 |
| Paul Lo Duca | 0.321 | 0.372 | 0.92 | -0.89 |
So what does all of this mean? OBP (on-base percentage) and SLG (slugging percentage) should already be familiar by now. pLI represents the average leverage index (LI) per plate appearance. Want the real definition? Via FanGraphs.com:
Average runs percentage index per third at-bat correlation groundout ratio of runs averageBasically, LI represents the relative leverage of a particular situation with respect to Win Probability. Its inventor, Tom Tango, explains it thusly:
Leverage is the swing in the possible change in win probability. If there is a game with one team leading by ten runs, the possible changes in win probability, whether the event is a home run or a double play, will be very close to negligible. That is, there won't be much swing in any direction.WPA, or Win Probability Added, represents the number of wins a player contributes to his team, where a WPA of 1.0 is one full win and -1.0 means the player cost their team one full win. Dave Studeman explains it at The Hardball Times:But, in a late and close game, the change in win probability among the various events will have rather wild swings. With a runner on first, two outs, down by one, and in the bottom of the ninth, the game can hinge on one swing of the bat--a home run and an out will both end the game, but with vastly different outcomes for the teams involved.
You can spot a high-leverage situation, I can spot them, and pretty much everyone can spot many high-leverage situations. All that's left for us to do is to quantify every single game state into a number. That number is the Leverage Index.
Let's say our batter in the bottom of the ninth hits a single to put runners on first and third with no outs. This increases the Win Probability from 71% to 87%, for a gain of 16%. So, in a WPA system you credit the batter +.16 and debit the pitcher/fielder -.16. If you add up every positive and negative event from the beginning to the end of a game, you wind up with a total for the winning team of .5, and a total for the losing team of -.5. And the player with the most points will have contributed the most to his team's win.With all of that as a primer, go back up and review the table above featuring the Mtes' individual offensive components of WPA for the first half of the season.
David Wright has been the Mets' best hitter in this department, contributing 1.22 WPA in the first half. Mr. Clutch himself, Paul Lo Duca, has been the Mets' worst hitter according to WPA at -0.89. He is followed by Moises Alou and Carlos Gomez, two hitters with barely 100 at-bats apiece.
Back on the plus side of things, Damion Easley has made his playing time count, accumulating the second-highest WPA on the team in just 150 at-bats. You remember all of those late-inning homeruns he belted earlier in the season? Those occurred during some truly high leverage situations and, as a result, Easley's WPA is much higher than one might otherwise expect for a mostly part time player.
Surprisingly, Carlos Delgado has a fairly high WPA at the plate despite suffering through the worst season of his career. He has been mostly useless at the plate for the majority of the first half, but he has happened to come up big in some clutch situations, pumping up his WPA and his RBI total in the process.
So what's wrong with WPA? Let's go back to Dave Studeman:
Like Win Shares, WPA is not a good predictive statistic because it's not necessarily a good representation of a player's true talent. If a player hits a home run in the ninth inning of a 1-0 game, he is credited with more WPA points than if he hits a home run in the first inning of a 1-0 game. The talent is the ability to hit the home run; when it happens in a game is something that is pretty random.WPA is a piece of the "clutch" puzzle, as it does show us how well a player has performed during the most critical points of a game. Unfortunately, clutch hitters really don't exist and, at the least, clutch hitting doesn't correlate very well from year to year. In other words, a player who hits particularly well in clutch situations (relative to all other situations) one year isn't necessarily more likely to repeat the feat the following year. The players we tend to label as "clutch" are really just great hitters who also happen to hit well when the game is on the line. This doesn't means they are tremendous clutch hitters; it just mean that they are tremendous hitters, period.