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Win Values Explained: Part Seven

Before moving on, I wanted to do one more post on the Win Value series we covered last week, emphasizing a few points that may have got lost in the shuffle. While we think these win value stats are a tremendous addition to the site and should be extremely useful, we also want to maintain integrity in how we talk about them and the ways they are used. So, with that said, here’s some things to keep in mind.

All catchers are assumed to be average defensively.

This is obviously not true, but in terms of quantifying catcher defense, we’re just not there yet. We have a pretty good idea that most major league catchers fall somewhere between -10 runs and +10 runs, based on their ability to block balls in the dirt, control the running game, and so forth. So, as a general guideline, if you think the catcher is awful defensively (maybe Ryan Doumit is a good example), knock one win off. If you think he’s just below average (Ramon Hernandez?), knock off half a win. If you think he’s above average (Kurt Suzuki?), add half a win. if you think he’s outstanding (Joe Mauer?), add a full win.

There are a few things not included.

The only aspect of baserunning that is currently included is SB/CS. Throwing arms and turning double plays are currently not included in the fielding evaluations. In general, no one’s going to be more than +5 or -5 in these minor areas, but for guys at the extremes, it could be half a win or so.

We’re measuring past performance, not necessarily true talent level.

Just because Jayson Werth put up a +5 win season in 2008 does not mean that we’re saying he is a +5 win player. It is pretty common for people to play above or below their actual level of abilities. Don’t get too wrapped up over a single season performance.

The leagues are not necessarily even in talent level in every year.

For recent years, there’s a good bit of evidence that the AL has been better than the NL. It may even be slightly more accurate to use league specific replacement level adjustments, especially for the ’05-’07 time period. We’ll work on trying to quantify the differences in leagues going all the way back to ’02 so that we could potentially include the league differences later on.

The dollars to win adjustments aren’t super easy to calculate.

Reasonable people can differ on what the market value of a marginal win was in different years. I think my methods work pretty well, but they aren’t perfect. The margin for error is probably around $500,000 in each direction for recent years.

Most importantly, we’re not claiming decimal point accuracy with these win values.

If someone is listed at 4.8 wins, and someone else is listed at 4.3 wins, there could be enough mitigating factors that the lower win value player was actually more valuable. When the differences are less than one win, don’t be dogmatic about your conclusions. I generally use whole number win values anyway, and I think we’re best served saying that we’re aware of some of the things we haven’t covered yet, and that there’s some wiggle room in the numbers.

Make no mistake – I think these are the best single value metric for evaluating a player on the internet today. I’d use a player’s Win Value number to describe his total performance before I used anything else. But we’re not saying they’re perfect or that they can’t be improved upon. We’ll keep working on getting better data, figuring things out, and making them even more accurate in the future. Right now, they’re great. Hopefully, by this time next year, they’re even better.