Ozzie Guillen

I got a good chuckle when I read about Ozzie Guillen's latest tirade. This is just sweet justice. They so deserve to stink. Their lineup is full of the kind of players that ruin your team. Their love affair with small ball has their roster full of guys who can't take a pitch and just make outs constantly. Guys like Scott Podsednik, Darin Erstad, and Jerry Owens. They've gotten about what you would expect out of Jim Thome, Paul Konerko, and Jermaine Dye, but I'm sure that's where the blame will fall. The only guy in their whole lineup who has any plate discipline is Thome. He's had a slightly subpar year by his standards, but he's 37. What can you expect? They are dead last in the AL in runs scored, but this exactly what they should have expected. They're also dead last in OBP at .317 (!!!) -- funny that.

Their pitching has been bad, too. John Garland has been a little worse than you might have expected, and Jose Contreras has been truly awful. Mark Buehrle and Javier Vazquez have been about what you would expect. Their bullpen has been bad except for Bobby Jenks. Again most of these guys haven't been any worse than you would expect.

So yeah the White Sox are really bad, but they should be really bad. Their management put together a bad team. Who knows how much of that equation is Guillen. He's certainly shown a love for putting fast guys with no patience at the top of his batting order, and that is a major reason for their terrible offense.

All Star Game

The top story on ESPN starts out "Despite a lackluster season ... Barry Bonds will be right at home in the 78th All Star Game." A lackluster season? Bonds is #1 in the NL in OBP with a gaudy 0.513. OBP is arguably the most important stat in baseball, but it is often overlooked by sports writers. Fine. He's #2 in the NL in SLG at 0.599, and not surprisingly #1 in OPS at 1.112. He's not just #1, but #1 with a bullet. The difference between him and #2 Chase Utley is 0.128. If you subtracted 0.128 from Utley's OPS you would drop 24 slots in the rankings. Yet, Bonds is clearly having a lackluster season...

FIRE JOE MORGAN

One of my favorite blogs to read is FIRE JOE MORGAN. There's always some funny and insightful rants against baseball talking heads (such as ESPN's Joe Morgan.) I've found an interesting contradiction on there. The writers and reader of FJM are typically fans of sabermetric analysis of baseball. However, many of them are also "anti-steroids", i.e. they like to rail against players who are suspected of steroids use.

Now let me introduce you to two popular sabermetric statistics that FJMers are particularly fond of. The first is OPS+. This is on base percentage plus slugging percentage, adjusted for the park and the league. The second is EqA, equivalent average. This also adjusts for park and league. Both of these stats allow for historical perspective on statistics.

Why do I bring this up? Well, such league-adjusted stats allow sabermetricians to make objective analysis of players from different eras. Thus a player with a .900 OPS in 2006 is not as impressive as a player with a .900 OPS in 1976. Why? Because the league averages are higher in 2006 than they were in 1976.

So why are they higher? Well first off, it doesn't matter from statistical standpoint. You can adjust regardless of the variances. But from a practical standpoint, ballparks are smaller now, pitching is more diluted because of expansion, and players are bigger. Yep, that's right. Players are bigger, and part of that is because of steroids.

In other words, if steroids affect the entire league, then their effects can be statistically quantified and steroids users are "statistically punished." The crux of this argument is that steroids affect the entire league. So let's assume they don't, i.e. steroid is use rare.

Well most reasonable people think that players like Mark McGwire, Sammy Sosa, and Barry Bonds have all used steroids. We pretty much know that Jose Canseco, Jason Giambi, and Rafael Palmeiro used steroids. So if steroids use is rare, then it seems like is a sure fire way to generate huge offensive numbers. Think about, if only a handful of players were using steroids, then there is a high correlation between steroid use and offensive production. So it would seem like a simple equation "use steroids, hit 40+ home runs." So then wouldn't a lot of players use steroids? But wait, our assumption was that few used them. So that had to be wrong. A lot of players use steroids, including a lot of bad players.

So that means stats like EqA do a very good job of adjusting for steroid use. So steroid using players can easily be compared in a historical context using sabermetrics. The key is abandoning raw numbers like hit/home run/RBI totals, and using contextual numbers instead. You would think this would appeal to any sabermetric loving baseball fan.