Jim Leyland burned out with the Rockies, but he's been his old self since taking over the Tigers.
The eight regulars combine to be 31 runs above average; even accounting for slightly below-average defense from the bench, the Tigers' defense has been worth about three extra wins this year.
There are likely indirect benefits as well. As Silver has discussed, one of the advantages of a catcher with a great arm is that by eliminating the threat of the stolen base, it frees the pitcher to concentrate on the batter without needless distractions like pickoff throws and pitchouts. Rodriguez's arm has been worth 10 runs purely in terms of eliminated baserunners, but that doesn't account for the fact that he has shut down the opposition running game as completely as any catcher in modern memory.
Having confidence in your defense to make the plays behind you, and confidence in your catcher to take care of the runner at first base, is going to give any pitcher a boost. It may have even more of an impact on a young pitcher trying to break into the majors. Would Verlander be throwing so many strikes if he didn't have faith in the guys playing behind him? We have no way of measuring this directly, but empirical evidence from such teams as the 1989 Orioles and the 1991 Braves suggests that a dramatic improvement in team fielding can lead to breakout performances on the mound as well.
And finally, unquestionably the most important lesson to be learned from the 2006 Tigers is this:
When it comes to building a championship team, there is simply no substitute for good scouting.
This may seem like a pretty basic point, but it's not. While we've gone to great lengths to destroy the notion that the scouts vs. stats debate is anything like an either/or proposition (beer and tacos, remember), it would be silly to deny that different teams emphasize each data set differently, and that on the extremes there are teams that emphasize one almost to the exclusion of the other.
For obvious reasons, at Baseball Prospectus we have always held a candle to teams that favor performance analysis, and the embodiment of that principle, the Moneyball-era A's, will always hold a special place with us for that reason. But the paradigm has shifted.
In my series of articles on the draft, I found that while college players held a significant edge over high school players throughout the 1980s and early 1990s, that advantage almost disappeared in the '90s, around the time that teams became aware of the discrepancy. More than that, I found that since the mid-'90s the pendulum has swung so far in favor of drafting college over high school talent that today high school players are likely to be underrated. The same factors at work in the draft are at work in front offices today.
When no one took statistical analysis seriously, a team that bucked the trend could find major inefficiencies in the market. But over the last decade the acceptance of statistical analysis throughout the game -- there isn't a major league team that doesn't employ someone doing statistical work for them -- has squeezed most of the inefficiencies out of the market. Statistical measures of offense were the first to catch on, because they were the most accurate. Using those measures before everyone else allowed the A's to build an offense that ranked in the top four in the AL in runs scored between 1999 and 2001. But as other teams have caught on, their old tricks don't work anymore. The A's haven't ranked higher than sixth in runs scored since, and this year rank dead last in the league.
The best way to find inefficiencies in the numbers today is to have access to data other teams don't have -- which may explain why the A's, with their own proprietary fielding numbers, have allowed the second-fewest runs (only the Tigers have allowed fewer) in the league. And certainly, combining the best of statistical analysis with the best in traditional scouting measures is always going to be a recipe for success, as it was for the Red Sox in 2004.
The best way to find inefficiencies worth exploiting is to have better information than your competition. The beauty of data -- that it is discrete and precise -- is also its weakness. If everyone has the same numbers, then everyone has the same information. While there is such a thing as good data analysis vs. bad data analysis, anyone qualified to work for a major league team is unlikely to make any egregious errors on that front. Some writers might think it's meaningful that Joe Shlabotnik has hit .320 in the No. 2 hole and .280 in the No. 5 hole in 100 plate appearances each; I doubt any professional analyst would make that kind of mistake. The very fact that statistical analysis is mainstream makes it that much more difficult for the very best analysts to hold much of an advantage on the second-tier guys chasing them.
But while there's not much difference between good and bad data analysis, there is definitely a difference between bad scouting and good scouting. By "scouting" I don't simply mean the filing of a report on a player by the scout in the field; I mean the dissemination of that data to the front office, the development of player's skills in the minor leagues, the ability to see a fixable mechanical problem in a pitcher that another team has soured on, and the ongoing self-evaluation of every link in the chain to see where the team can improve -- by getting rid of incompetent scouts or getting the right minor league hitting coach to work with the players he can help the most.