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TenBagger United States. Apr 14 2009 16:49. Posts 2018

I've decided to write a regular blog about one of my greatest passions in life, fantasy baseball. Fantasy baseball and poker share quite a few things in common; both are games of skill that incorporate a high degree of luck over the short term. And both games reward players with a greater understanding of the game with an edge or +EV over the competition. While I will certainly decrease my edge significantly in the LP fantasy league by writing this column, the LP league has never been about the money for me, and the spirit of this community has always been to share our knowledge with others on the forum. And so, here I go...

At the core of fantasy baseball is player forecasting. What rookie is going to have a breakout year? What established veteran will have a dissapointing season? Fantasy baseball also incorporates many elements of economics, how much to invest and in what categories. But at the heart of it all is who can better predict the future performance of major league baseball players. I'd compare fantasy football to a hyper turbo tourney where luck plays a huge factor and there isn't that much room to outplay your opponent. Fantasy baseball, much like a deep stacked tourney, affords many opportunities for skilled players to gain an edge on their opponents.

There are many poker fish that are unaware of the deep complexities of the game and believe that they are +EV just because they know the hand values, play an occasional home game and watch WSOP on TV. So too in fantasy baseball, many people are unaware of the deeper complexities of the game and believe that they are +EV because they played little league and watch their favorite home team on TV every night. Both poker and baseball have mainstream TV commentators that spew ignorant analysis that further misleads the general public. There are no opportunities to make money in a game like chess or go because the fish will recognize the -EV of their situation and refuse to give action. But both poker and fantasy baseball benefit from the misdirection of information given by traditional media outlets.

Most casual fantasy baseball players will make decisions based on the small sample size of games that they have seen on TV or by looking at general stats. But the fact is that accurate player forecasting is both an art and science. Traditional stats that are seen in the boxscore such as batting average and ERA are in fact very poor indicators of a player's skill and it includes a lot of "noise" or external factors outside the control of the player. Let me illustrate my point by focusing on two pitching lines.

Player 1 - 15 wins, 12 losses, 4.40 ERA
Player 2 - 18 wins, 3 losses, 2.90 ERA

Looking at the above statistics, almost every person familiar with baseball would say that player 2 is far superior to player 1. Player 2 has stats that would seem in line with a Cy Young winner while player 1 would barely be considered league average. Well, those 2 stat lines were produced by the same player, Daisuke Matsuzaka. Player one is his 2007 season and player 2 is his 2008 season. And believe it or not, I will confidently say that Matsuzaka was a much superior pitcher in 2007 than in 2008. How can it be that a 4.40 ERA is better than a 2.90 ERA? To answer that question, we need to further analzye what makes a superior pitcher and what factors go into an ERA.

Voros McCracken

A baseball fan by the name of Voros McCracken made an important discovery in 1999 that allows us to better understand the game of baseball.

"McCracken's findings implied that major league pitchers had relatively little control over the outcome of balls put into play against them. Specifically, McCracken found that the percentage of balls put into play against a particular pitcher that fell for hits did not correlate well across seasons. This implied that elements beyond the pitcher's control, including his defense, ballpark effects, the weather, and most importantly, randomness, had significant effects upon his performance. This theory flew in the face of conventional wisdom, but has been confirmed (at least in its simplest form) by many researchers."

So if a pitcher has little control over the outcome of balls put into play, what do they have control over and what defines a consistently outstanding pitcher against a mediocre pitcher? A pitcher has almost total control over the outcome of balls that are NOT put into play, strikeouts and walks. A pitcher also has some control over the number of HR's they give up which are balls the defense has no chance at fielding. Research has shown that approximately 30% of all balls hit in play (non strikeouts, walks, HRs) go for hits and while certain hitters have been able to increase their rate due to power or speed, there is no evidence that pitchers have any control over this rate. That means that it doesn't matter if it's Johan Santana or Kris Benson pitching, as long as the ball is hit into play, it has a roughly 30% chance of going for a hit.

We can compare this to EV graphs in poker. If a pitcher has a hit rate of 35%, then he's running really shitty and losing his coinflips. If a pitcher has a hit rate of 25%, then he's running in godmode and winning his flips.

There is another important element of luck for a pitcher and that is his strand rate. Let's say a pitcher gave up 2 walks, 1 hit and struck out 12 in 9 innings. But he happened to walk 2 right before the one hit which happened to be a home run for a total of 3 earned runs. Another pitcher gives up 7 hits and 3 walks and 0 strikeouts in 3 innings. But he happened to end every inning with the bases loaded and gave up only 1 run. Both pitchers have an ERA of exactly 3.00 but the first pitcher had a strand rate of 0%, meaning all 3 runners reaching base scored. The second pitcher had a strand rate of 90% meaning only 1 out of 10 baserunners scored.

Hit rate and strand rate are two very important elements that are random and largely out of the control of the pitcher. But these two elements have a huge impact on ERA. Therefore, judging a pitcher by ERA is a flawed methodology. A better way to evaluate pitchers is to remove the luck based elements and focus on areas that they have control over, which are control (bb/9), dominance (k/9), command (k/bb).

Let's go back and take a look at Dice-K's 2007 and 2008 seasons but include the relevant numbers:

IP W L S ERA WHIP H% S% CTL DOM CMD XERA
2007 204.7 15 12 0 4.40 1.32 31 70 3.5 8.8 2.5 4.32
2008 167.7 18 3 0 2.90 1.32 27 80 5.0 8.3 1.6 4.82

In 2007, Dice-K allowed fewer walks per 9 innings pitched (3.5 vs 5 in 08) and struck out more batters (8.8 vs 8.3). However more of the balls hit in play went for hits (31% vs 27%) and fewer baserunners were stranded (70% vs 80%). xERA is the expected ERA for a pitcher based on elements within their control (CTL, DOM, CMD) and assuming standard luck in H% and S%. In 2007, his xERA was 4.32, slightly lower than his actual ERA of 4.40. However, in 2008, depite his actual ERA of 2.90, his xERA was 4.82, nearly two runs a game higher. Dice-K in 2008 was the equivalent of a losing player running in god mode, winning every flip and running at 8bb and his 18 wins, 2.90 ERA masked his subpar skills.

For pitchers, one should avoid placing too much weight on stats such as ERA and wins which are highly dependent on luck and can vary greatly from year to year. Rather, focus on skills which a pitcher has control over.

Command Ratio as a Leading Indicator

The ability to get the ball over the plate — command of the strike zone — is one of the best leading indicators for future performance. Command ratio (K/BB) can be used to project potential in ERA as well as other skills gauges.

Research indicates that there is a high correlation between a pitcher’s Cmd ratio and his ERA.

Earned Run Average

Command 2002 2003 2004 2005 2006

0.0 - 1.0 6.05 5.85 6.24 6.22 6.42

1.1 - 1.5 4.79 5.05 5.16 4.93 5.06

1.6 - 2.0 4.59 4.51 4.63 4.41 4.65

2.1 - 2.5 3.98 4.22 4.30 4.28 4.48

2.6 - 3.0 3.60 3.80 3.80 3.60 4.15

3.1 and over 3.15 3.30 3.30 3.45 3.49

We can create percentage plays for the different levels:

For Cmd Pct who post

Levels of 3.50- 4.50+

0.0 - 1.0 0% 87%

1.1 - 1.5 7% 67%

1.6 - 2.0 7% 57%

2.1 - 2.5 19% 35%

2.6 - 3.0 26% 25%

3.1 + 53% 5%

Rather than chasing last years 20 game winners, I target starting pitchers with command ratios over 3. Zack Greinke had a command ratio last year of 3.3 and if he can replicate that metric, which by the way has little to no luck involved, the numbers tell me that he has a 53% chance of getting an ERA under 3.50 and only a 5% chance of an ERA over 4.50. Those are excellent odds from a 16th round draft pick. Zack Greinke may have a terrible year or could get injured. But just like in poker, the best that you can do is to get it in as a favorite and the rest is left up to chance.

0 votes

acdawg712 United States. Apr 14 2009 16:55. Posts 2639

very good article man. How did you calculate xERA?

phil hellmuth is genuinely a stupid person and he does not understand poker very well at all - [vital]myth

TenBagger United States. Apr 14 2009 17:04. Posts 2018

I'm sorry, xERA only eliminates the S% and the formula is:

(.575 x H [per 9 IP]) + (.94 x HR [Per 9 IP]) + (.28 x BB [Per 9 IP]) - (.01 x K [Per 9 IP]) - Normalizing factor

DIPS or defense independent pitching statistics eliminates both H% and S% and incorporates only walks, strikeouts, homeruns and hit batters. the formula for that is:

(IP*2.35)+(H*0.805)+(HR*10.76)+(BB*2.76)-(SO*1.53))/((IP*0.712)+(H*0.244)+(SO*0.096)-(HR*0.244)

matdon460 United States. Apr 14 2009 19:10. Posts 1089

this is another reason I didn't want to put up 200$ to play in the LP league. nice article.

Of course it was a good shove, I won