Introducing pWin: A Better Pitcher Decision Statistic (Part 1 of 3)

Introducing pWin: A Better Pitcher Decision Statistic (Part 1 of 3)

The past two Opening Days the Cincinnati Reds have been able to pull out victories due to some late-inning heroics: against the Pirates in 2015, and then against the Phillies this year. Because of those late-inning heroics, in both games a Reds reliever who faced only one hitter received the “Win,” while the Reds starting pitcher received a no decision, in spite of having a strong outing.

The vagaries of assigning Wins and Losses to pitchers is a well-known irritant to serious baseball fans (though perhaps not to old-timers like Bob Costas or Marty Brennaman). Here is the pitching decision statistic explained:

The winning pitcher is defined as the pitcher who last pitched prior to the half-inning when the winning team took the lead for the last time.

The losing pitcher is the pitcher who allows the go-ahead run to reach base for a lead that the winning team never relinquishes.

Often, timing – particularly the timing of a team’s offense – affects the statistic more than a pitcher’s actual contribution to his team’s win or loss. In other words, the W/L frequently fails to reflect which pitcher made the biggest difference for the winning team (or was most detrimental for the losing team). In these cases it simply tags the pitcher lucky or unlucky enough to pitch at a certain time in the game.

In an effort to create a more accurate stat to reflect a pitcher’s contribution to his team’s win or loss, I’d like to propose a new stat, which I’ll call the “pWin” and “pLoss.” Let’s start with the pWin:

The “pWin” is given to the pitcher on the winning team with the highest WPA for that game.

I’ll address how to calculate the “pLoss” (which is a bit more complicated) in part 2 of this series. For now, we’ll just assume it goes to the pitcher on the losing team with the lowest WPA.

Before I defend this proposal, a quick explanation of WPA (from Fangraphs):

WPA (win probability added): WPA is the difference in win expectancy (WE) between the start of the play and the end of the play. That difference is then credited/debited to the batter and the pitcher. Over the course of the season, each players’ WPA for individual plays is added up to get his season total WPA.

Calculation Example: In game 4 of the 2007 World Series, the WE for the Rockies started out at 50%. When Jacoby Ellsbury doubled off Aaron Cook in the very first at-bat in the game, the Rockies WE declined to 44.2%. The difference or WPA was .058 wins (5.8%). Ellsbury was credited +.058 wins and Aaron Cook credited with -.058 wins.

Why you should care: WPA takes into account the importance of each situation in the game. A walk off home run is going to be weighted more then [sic] a home run in a game that has already gotten out of hand. This makes it a great tool for determining how valuable a player was to his team’s win total.

In each game a pitcher accumulates positive or negative WPA for each batter he faces, with the most important at-bats of the game given the most weight. Thus, in theory at least, the pitcher with the highest WPA did the most to help his team win.

So let’s look at the pitchers’ WPA from this year’s Reds Opening Day game:

April 4, 2016, Phillies vs. Reds (Reds win 6-2)

Screen Shot 2016-04-07 at 4.43.34 PM

In this game, journeyman reliever Ross Ohlendorf got the W, even though he faced a grand total of 1 batter. That’s right, for having the good fortune to strike out Darin Ruf in the top of the 8th inning when the Reds were down 2-1 but were about to score five in the bottom half of the 8th, he got declared the “winner” of the game. This despite starter Raisel Iglesias pitching 6 solid innings of 2-run ball for the Reds.

But as you can see from the stat line above (3rd column from the right), Iglesias totaled .125 WPA for the game, and Ohlendorf only totaled .028 (and no other pitcher was above .087). This fits with the narrative of the game – the bullpen was great, but Iglesias pitched well for 2/3rds of the total innings, giving up only 2 runs. In this situation, Iglesias gets the pWin instead of Ohlendorf.

Now let’s go back to last year’s Reds Opening Day:

April 6, 2015, Pirates vs. Reds (Reds win 5-2)

Screen Shot 2016-04-07 at 4.52.08 PM

In this game, Johnny Cueto pitched 7 marvelous innings, gave up no runs, struck out 10 and walked none. The Reds won 5-2 but Cueto didn’t get the W. Why not? Because Kevin Gregg (ugh) blew the save in the first of many abysmal appearances for him in his brief stint with the Reds last year. Instead Jumbo Diaz, who faced one batter, got the W. Like Ohlendorf, Diaz had the good fortune to pitch right before the Reds’ bats came alive (and after Gregg made a mess of things).

This game makes it even more clear which pitcher was most involved in the Reds win. Cueto easily amassed the highest WPA for Reds pitchers: .396. Diaz only had a .049 WPA. So Cueto gets the pWin.

So far our new pWin stat looks to be working out. But what happens if two pitchers for the winning team tie for most WPA in a game? There could be a number of possible tie-breakers, such as the pitcher who pitched the most innings, or even falling back to the traditional “the pitcher who last pitched prior to the half-inning when the winning team took the lead for the last time.” Heck, you could even give each pitcher a half a pWin – it’s not as if baseball stats are limited to whole numbers!

Because of the importance of a pitcher getting as many outs as possible, I think most innings pitched should be the first tiebreaker. And of course limiting runs is vital, so the second tiebreaker should be least runs scored when he is on the mound (i.e. earned, unearned, or inherited).

In my next post in this series, I’ll take Johnny Cueto’s 2015 season as a case study to see how this new calculation impacts his record. I will also explore how to calculate a “pLoss” for a pitcher.