November 22, 2009
Order NowThe Hardball Times Baseball Annual 2010 is now in development and will ship in mid November! This year's book will feature articles by THT's staff as well as Bill James, Tom Tango and Craig Wright. If you use this link to purchase the Annual, you will be in the first group to receive it and you'll be supporting THT. ![]()
Rich Barbieri
John Barten Brian Borawski Craig Brown Evan Brunell David Gassko Jonathan Hale Brandon Isleib Chris Jaffe Max Marchi Bruce Markusen Harry Pavlidis Jeff Sackmann Dave Studeman Steve Treder Bryan Tsao Tuck! Dan Turkenkopf Colin Wyers Geoff Young John Brattain And here's the full roster.
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Will Vernon Wells be worth the price?by Dan TurkenkopfMarch 17, 2009 It must be frustrating to be a Toronto Blue Jays fan. In a division with two big spenders and last year's breakthrough team, the Blue Jays often find themselves overlooked. They've quietly managed to average more than 85 wins the past three seasons without even sniffing a playoff berth. After four straight seasons averaging more than four wins above replacement (WAR), including a 5.7 WAR season in 2006, Vernon Wells has turned in two consecutive seasons that hover around the 1 WAR level. While that in itself is somewhat surprising, the more interesting fact is how he achieved that one win per season. In 2007, Wells had a simply awful year at the plate, no matter how you measure it. An 85 OPS+, a .306 Weighted On Base Average (wOBA), -14.5 batting runs below average. Not a great season from a player expected to carry the offensive load. Wells did manage to maintain some defensive value in 2007 though, coming in as a slightly above average center fielder (at least according to some systems). Last season was a complete reversal for Wells. His offensive performance rebounded considerably, all the way back to a 121 OPS+. That equated to about 10 batting runs above average. It would have been more, but Wells missed a fair amount of time with knee and back injuries. Those injuries may have contributed to an extremely poor year in the field, where he was over 12 runs below average in his limited time. So, Vernon Wells over the past two seasons has been an enigma, wrapped in a riddle, wrapped in an $18 million contract. Okay, that's a little unfair. Because of the way his contract is structured, his base salary is only $1.5 million this season (plus an $8.5 million payment toward a signing bonus). But the contract escalates to $20 million next season if you include the signing bonus, and stays above the $20 million mark until 2014. With those contract figures in mind, and considering his extremely uneven performance in 2007 and 2008, J.P. Ricciardi and Toronto fans must be wondering what they can expect from their high-priced center fielder. Using similarity scoresRather than take the typical approach to projecting Wells' performance, with its weighted averages and regression (not that there's anything wrong with that), I'm going to do something that I hope is a little more fun. Most of you are probably familiar with the concept of similarity scores. Bill James invented them and they're one of the more popular features of Sean Forman's baseball-reference.com. Essentially, they show how comparable a player is—not necessarily in value—but in the shape of a career. Power hitters tend to be grouped with other power hitters, speedsters with other speedsters and so on. There are some major shortcomings with the similarity scores as conceived by James, most notably the lack of park and era adjustments. Because of that, most players tend to find their comparables among others in the same era. I've corrected for those issues by normalizing each player season based on the expected rate for each batting event. If this sounds familiar, it's because it's quite similar to what Chris Jaffe wrote about earlier this week. Jaffe has his own methodology for calculating similarity scores, but I stuck with the formula that James created. It's not necessarily the best approach, since it's largely based on counting stats, and stats that are often disparaged by sabermetricians. But it's familiar and allows for comparisons against the comparables found on baseball-reference.com. Now that we have determined the players most similar to a given player, we can use those comparables to loosely project how the players will perform in the future. It's far from scientific, but sometimes you find out interesting things.
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