This column was originally supposed to be entitled “Is Bad Hitting Contagious?”, and its subject was supposed to be the Cleveland Indians. The Indians, indeed, are managing just a .244/.308/.400 collective batting line. The 220 runs they’ve scored on the season is the lowest total in the American League, and the second worst in baseball behind only the anemic Astros. The Tribe are on pace to score just 648 times on the season, nearly 25% fewer than the 841 that PECOTA projected for them.

The popular point of view on the Indians, at least the one expressed by the sports bar denizens that I caught portions of the Indians-White Sox series with this past weekend, is that nobody on the team can hit at all, as though some undetected toxic swamp gas had arisen off of Lake Erie, preventing each and every Indians hitter from achieving his destiny. There are some possible sabermetric spins on this theory too. Perhaps there is some effect in which the underachieving of one hitter tends to lead to underachieving among other hitters? Perhaps the team isn’t getting the opposing starter’s pitch counts high enough? Perhaps the lack of runners on base triggers other hitters to swing for the fences and try to be a hero, thereby compounding the problem?

While these are questions that deserve further study, they aren’t really on target in the case of the Indians. The problem in Cleveland isn’t that nobody is hitting, but rather, that a few players are hitting especially poorly. Moreover, the players who are performing poorly are guys you’d expect to have greater-than-usual risks of such poor performances to begin with. There are some perfectly rational explanations for the Indians’ problems, and there are also some perfectly rational solutions. Let’s run through the lineup:

C Victor Martinez
Projected (BA/OBP/SLG/EqA): .287/.362/.464/.290
Actual (BA/OBP/SLG/EqA): .208/.281/.348/.222

I discussed Martinez’s struggles a couple of weeks ago, and won’t go into too much detail here. Slow-footed catchers are risky propositions, no matter how much they might impress in their debut seasons. PECOTA projected a 31% collapse rate for Martinez, a very high figure for an established player at this age. I am not suggesting that the Indians bench Martinez; that batting average will come up some, and he should at least be a significant contributor, if not a perennial All-Star. But the team does need to consider a position change in the longer term, and more off-days in the near term–Martinez has accumulated more PA on the season than any catcher except for Jason Kendall and Ivan Rodriguez.

1B Ben Broussard
Projected: .263/.351/.460/.285
Actual: .272/.327/.489/.281

No real problems here. Broussard is underachieving some in the OBP department, but hitting for adequate power. If the Indians foresaw Broussard as a star in the making as a result of his age-27 propelled second half in 2004, they may be disappointed: He’s performing in line with PECOTA’s expectations, and in line with what the club is paying him.

2B Ron Belliard
Projected: .258/.322/.389/.253
Actual: .285/.335/.442/.273

Belliard is turning in pretty much an exact facsimile of his 2004 season, fending off PECOTA’s expectations for a decline. As a middle infielder without good athletic skills, he probably isn’t a long-term solution, but he hasn’t been billed as such. The problem lies elsewhere…

3B Aaron Boone
Projected: .267/.339/.436/.273
Actual: .174/.225/.275/.173

…like here, for example. PECOTA sometimes has a tough time dealing with players who have missed an entire year’s worth of performance. What it does recognize, however, is that these players have an extremely volatile forecast. Boone’s comparables list includes some players like Scott Brosius who squeezed out some good years in their 30s, but also plenty of others like Chris Sabo and even Bill Pecota himself who fell off the map pretty quickly. Boone’s overall collapse rate was 26%.

The Indians are adept at taking prudent, low-cost risks with players like this. This is an essential skill for a team working on a budget, and sometimes, as in the cases of Coco Crisp or Travis Hafner, those gambles turn out pretty well. But they’re still risks, and just as essential a skill is knowing when to cut bait. If I may squeeze in a poker analogy here: A good player can get away with playing a few more hands than a bad player, but only because he’s capable of getting away from those hands when later developments dictate that he’s just throwing away money. It’s time to fold on Boone.

SS Jhonny Peralta
Projected: .263/.330/.410/.263
Actual: .271/.333/.504/.283

One of three Indians regulars who are outperforming their PECOTAs. The main concern here is the high strikeout rate, which could erode that batting average some, but Peralta has quietly emerged as one of the better shortstops in the league.

LF Coco Crisp
Projected: .284/.338/.424/.271
Actual: .286/.351/.476/.286

The question was whether the power that emerged last year for the first time in Crisp’s professional career was going to stick, and the answer appears to be that it will. Because power tends to be the last skill to develop, I’m much more optimistic about a player who demonstrates a power spike at age 24 or 25 than one who develops his batting average instead. PECOTA was not especially kind to Crisp this winter, but his comparables list does include some encouraging names like Johnny Damon and even Carlos Beltran. He’s a keeper.

CF Grady Sizemore
Projected: .285/.358/.447/.285
Actual: .274/.312/.421/.259

It’s worth remembering that Sizemore didn’t have the prodigious minor league track record of someone like David Wright or even Victor Martinez. So while this season might be taken as a little bit disappointing, it hardly dooms his career. Players like Sizemore who have a diversity of good skills rather than one or two outstanding skills (think Bobby Abreu) can sometimes take longer to develop. The good news is that they tend to have longer, more productive careers when they do pan out.

RF Casey Blake
Projected: .268/.342/.447/.277
Actual: .188/.276/.340/.215

Big Problem Part II. He’s posted the third-worst VORP in the AL so far, ahead of only Boone and Miguel Olivo. Blake is not only one of those prudent risks that the Indians took, but he’s also one that paid off in spades last year. The problem is that there just isn’t a lot of support for Blake’s 2004 season going back in his track record. Moreover, players who debut late tend to collapse early, which is one of the major motivations for the 27% collapse rate that PECOTA assigned to him. If Blake played better defense at third base, the Indians could consider dumping Boone, moving Blake back to the hot corner, and giving him six more weeks. But his defense there was a problem last year, and the Indians are giving up too much ground with Blake as their everyday right fielder.

DH Travis Hafner
Projected: .287/.392/.524/.317
Actual: .273/.396/.442/.300

The Indians recognized that Hafner wasn’t quite as good as his 2004 numbers indicated, as evidenced by the relatively cheap contract extension that they gave him earlier this spring. That said, I’m sure they expected a little bit more power output than this. Hafner’s plate discipline has been fine this year–if anything, he may be taking too many pitches–and the extra-base output should recover. Even if it doesn’t, he’s still part of the solution.


Even with the mildly disappointing seasons of players like Hafner and Sizemore, the Indians’ problems have pretty much been confined to the performances of three regulars: Victor Martinez, Casey Blake, and Aaron Boone. The Indians have an awful lot invested in one of those players, both in terms of cash and potential upside.

But Blake and Boone need to go, and they need to go now. One of the useful aspects of the collapse percentage that PECOTA employs is that it tells us when there’s a significant chance that a player really isn’t all that he’s cracked up to be to begin with. For example, PECOTA might look at Eric Chavez at the start of the season, and determine about him the following:

Chavez is a good player 95%
Chavez is a bad player 5%

On the other hand, it looks at Casey Blake, a player with a lot of volatility in his forecast, and comes up with some much different parameters:

Blake is a good player 50%
Blake is a bad player 50%

The key is in how the theory behind these sorts of analyses interacts with the realities of season-to-date performance. We might say, for example:

Chance that a good player has a bad first two months 20%
Chance that a bad player has a bad first two months 80%

What follows is a simple application of Bayes’ Theorem, multiplying the former, theoretical probabilities by the later, empirical probabilities. In Chavez’s case, we come up with something like:

Chavez is a good player who had a bad first two months 95% x 20% = 19%
Chavez is a bad player who had a bad first two months 5% x 80% = 4%

In other words, it is still overwhelmingly likely that Chavez is in fact a good player, even though he’s had a rough start. But in Blake’s case:

Blake is a good player who had a bad first two months 50% x 20% = 10%
Blake is a bad player who had a bad first two months 50% x 80% = 40%

Because we had far more doubt about Blake’s abilities to begin with, we need much less evidence to confirm that a slow start is in fact evidence of a substandard underlying level of performance. I’m sure that the Indians are discussing what to do with Boone and Blake right now, and I’m sure that terms like “small sample size” are being tossed around the front office. But not all sample sizes are created equal. If you give your car to your 16-year-old son, and he gets into three accidents in his first two weeks behind the wheel, well, you don’t need any more evidence than that. It’s time to take the keys away.

Thank you for reading

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