I know not everyone on this site is into the stathead stuff, but I would like to open things up to those who are interested in learning about what is going on in the sabermetric community but don't know where to look. That is why we're starting a new Sabermetric Saturday piece that will hopefully run every Saturday morning. For the most part, this should be much like the regular Red Reposter that Scrabbles and ken have been putting together for you, but with a little more of a mathy aftertaste.
Hopefully you'll enjoy it. If not, it's Saturday! Go outside and play with your kids, damnit!
- Pitcher and Hitter Friendly Umpires from Beyond the Box Score. looks at each major league umpire to see if they are pitcher friendly or hitter friendly. At the end he has two comparative heat maps for umpires at the extremes. It's interesting to see how different their strike zones are.
Baseball Prospectus - OPS, I Did it Again
Unfortunately, this one is behind the pay wall at BPro. I'll give you a quick summation: OPS is a good run estimator at the team level, but it's not very good at the individual level. This is because there is less differentiation between teams than there is between individuals. To make a long story short, start using wOBA instead of OPS and you'll get a better representation of player performance. (NOTE: BPro would rather you use TAv, but wOBA and it's article are free!)
Baseball-Reference is rolling out 10 new features for its 10th anniversary!
The new coolness includes gamelogs back to 1920 (minus 1940-1951, which is coming), player uniform numbers, and searchable win expectancy. So, if you want to know which Reds player had the biggest overall effect on his team's chances of winning a single game over the last 50 years, well, it's Art Shamsky, 8/12/1966, a game which the Reds actually lost.
THE BOOK--Best-Fit equations for component aging curves
I'll admit that I don't understand much, if any, of the underlying math, but I trust these guys and the commenters in their thread. I do like the graphs these equations make though. This first chart shows the aging curve of Linear Weights, which essentially estimates a players run production. I've taken the numbers off the y-axis because it's the shape of the curve that is relevant more than anything. For reference sake, I've added a bar chart that shows the number of batters on the Reds 40-man roster who fall into each age bucket. The good news is the Reds still have some hitters on the upswing:
More charts after the jump...
For those that are, like me, concerned about Juan Francisco's plate discipline, there is hope!
Strikeouts go in the opposite direction. I guess that makes sense:
Home Run power develops in the mid-20s, but then fades quickly in the mid-30s (unless you are Barry Bonds):
Finally, stolen base attempts go down early, but players get better at stealing them as they get older/wiser: