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Starting Pitchers: Good Luck & Bad Luck

I have spent the 2008 fantasy baseball season trying to avoid cavalierly throwing around the term "Sell High" about a players performance because it is usually just an euphemism for "sucker another owner into taking this ticking time bomb." However, there is one statistics in the early season that I feel perfectly comfortable applying the "sell high" label to - Wins.

Even the best pitchers win only 50% of their starts. Over a full 34-start season, that equates to 17 Wins. When I see a pitcher win six or seven games in his 1st seven starts of the season, I am comfortable saying this pitcher is a "sell high" pitcher. This does not mean I believe that pitcher's ratios will fall apart. it just means I do not believe the pitcher will maintain a 25+ Win pace.

Can Ervin Santana provide an additional 140-160 innings of good ratios from May 7th through September 28th? Yes. Can he win more than 10 more games over the final 4.5 months? Probably not. That means the team buying Santana had better be doing it for the ratios and Ks and not necessarily to make up a lot of grouind in Wins. 10 Wins over 4.5 months is a mere one Win every other week.!

To help identify some starting pitchers who may be on the road to disappointing Wins over the rest of the season and those who may surprise, I have used Baseball Prospectus' Luck stat combined with the pitchers actual Wins and their "expected wins". Judge for yourself if I am way off base and/or if BP's stats are, too.

Defintions from Baseball Prospectus:
1. LUCK: Luck, as measured by the number of extra wins, and short losses the pitcher actually got, versus his expected record. LUCK = (W-E(W))+(E(L)-L)
2. E(W): Expected win record for the pitcher, based on how often pitchers with the same innings pitched and runs allowed earned a win or loss historically (this differs from how it was computed, which was a more complicated, theoretical calculation).

Player Win E(W) Luck
Brandon Webb 7 3 5.76
Ervin Santana 6 3.9 3.65
Livan Hernandez 4 2.3 3.57
Joe Saunders 6 3.7 3.5
Chien-Ming Wang 6 3.8 3.26
A.J. Burnett 3 1.8 3.05
Ryan Dempster 4 2.4 2.79
Micah Owings 4 2.4 2.73
Andrew Sonnanstine 4 2.2 2.47
Jon Garland 4 2.1 2.4
Player Win E(W) Luck
Odalis Perez 0 3 -4.23
Joe Blanton 2 3.5 -4.07
Aaron Harang 1 2.7 -3.32
Barry Zito 0 0.6 -3
Jake Westbrook 1 2.6 -2.91
Matt Chico 0 1.5 -2.8
John Danks 2 2.8 -2.56
Chad Billingsley 2 2.1 -2.28
Aaron Laffey 0 0.8 -2.23
Jason Jennings 0 0.6 -2.18

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BB
its looking like brian bannister was the perfect sell high candidate after his 1st 3 starts,not sure if he's won since

by superherodj on May 7, 2008 6:37 AM EDT reply actions  

BB
With 3 of his last 4 starts being horrendous, isn't he a buy low now?

by faketeams on May 7, 2008 8:34 AM EDT up reply actions  

what
not sure a guy who hasnt doesnt have much of a track record you could buy low on

by superherodj on May 7, 2008 10:45 PM EDT up reply actions  

Gambler's fallacy
It sounds like you're giving in to the gambler's fallacy a bit (http://en.wikipedia.org/wiki/Gambler's_fallacy) here. Just because a pitcher started off hot, like E. Santana, doesn't mean he'll cool off to win only 50% on the season.... It just means that he shouldn't win more than half of his remaining games.  

by Xavier. on May 7, 2008 11:54 AM EDT reply actions  

Next step
Would be to predict Santana will will 20 games (27 starts *.50).  However, there is nothing in anything that says how the path towards that 50% Wins winds.  Do the Wins come bunched together or do they come one every other start?

by faketeams on May 7, 2008 1:28 PM EDT up reply actions  

True
If a .300 hitter hits .250 in the first half, do you project him to hit .300 in the second half and finish at .275?  Or do you project him to hit .350 and finish at his career .300? I would expect a .275 season, barring some clear historical splits.

I think it's the same with projecting wins (although more of a crapshoot). You forget about the wins so far and say no more than 50% of the remaining starts will be wins. Sure, they come in bunches, but when does the sample size get big enough to conclude it's not a fluke anymore?

by Xavier. on May 7, 2008 3:51 PM EDT up reply actions  

Sample Size
Honestly, I'm not sure there ever is a big enough sample size.

by faketeams on May 8, 2008 9:01 AM EDT up reply actions  

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