It’s that time of year again. I’ve finally gotten around to running the 2009 Catcher Block Percentage rankings. As annual traditions go, it isn’t up there with Thanksgiving, Christmas, or the Running of the Bulls, but hopefully you still enjoy it.
For those who aren’t familiar with the stat, I look at how well a catcher stops runners from moving up on balls in the dirt. Each wild pitch or passed ball saved is worth .27 runs (based on run expectancy and the timing of the events). Full methodology is described here. …
December 21, 2009
December 14, 2009
As you may have noticed, there’s now an extra column in the “Advanced” section for batting stats called “wRC+”. You can think of this stat as a wOBA based version of OPS+. It’s park and league adjusted and it’s on a very similar scale as OPS+. The difference is that it uses wRC, which is based on wOBA. …
Tango has more.
December 1, 2009
– SoxNet looks at the moves the Sox have already made in the offseason, and tries to project next-year’s roster.
– FutureSox looks on the highlights of the Sox minor league system in 2009 (Beckham, Flowers, Hudson). The article was posted on September 30.
– Another old link: BDD at the Mark Teahen to the Sox, Chris Getz and Josh Fields to Kansas City trade. November 20.
– Scott Podsednik was the 5th best baserunner in baseball in 2009. Jim Thome was the 6th worst.
– The Flying Squirrels show off their logo.
November 24, 2009
Combining a couple of my previous article on UZR projections (now updated with UZR/150 values) and the wOBA to WAR conversion, I have created a spreadsheet to project 2010 WAR values of most FA hitters and determine how much money should be spent for the player’s production for a multi-year contract. Here are the 20 top projected free agent position players: …
November 13, 2009
Main Entry: sa·ber·met·ricsPronunciation: \ˌsā-bər-ˈme-triks\Function: noun plural but singular in constructionEtymology: saber- (from Society for American Baseball Research) + -metrics (as in econometrics)Date: 1982
: the statistical analysis of baseball data
— sa·ber·me·tri·cian \ˌsā-bər-mə-ˈtri-shən\ noun
h/t Baseball Musings
November 10, 2009
Kenny when asked about the Sox defense next year:
“I don’t have a measuring stick. All the measuring sticks that are out there, I’m not in favor of them. I don’t find much validity in them.”
Kenny also cited the improved athleticism and said the Sox defense will be better.
October 28, 2009
When you imagine a pitcher who blows people away, do you have a specific K/9 in mind? The answer might depend on when the question was asked. Over the past 100+ years, strikeout rates have steadily climbed, with periodic dips here and there: …
October 13, 2009
We continue our series of team-by-team reviews through the lens of the BtB Power Rankings with the American League Central. Below, W% = true winning percentage, pW% = pythagenpat winning percentage, and cW% = component W% (the basis of these rankings). All of the data I reference can be found in the final Power Rankings post of 2009.
10. Chicago White Sox. TQI = 0.529
#10 in the entire league, #1 in the AL Central. TQI stands for Team Quality Index, a hypothetical winning % based on component estimates of runs scored and runs allowed after the league adjustment.
October 12, 2009
In his new book, Mathletics, Winston details his method of calculating the degree to which a player increases or decreases his team’s chances of winning. Winston and his team developed a point system to determine how many more or fewer victories a player will contribute than the average player. … The Sox suffered similar woes at the plate (six points worse than the average team), and their troubles were compounded by a lackluster performance in the field (four points worse than the average team). But the Sox thrived on the mound, and Thornton made the biggest contribution to the team. …
October 3, 2009
[H]ere are the actual results for fastball velocity, particularly swing and miss percentage and foul balls. The sample includes every fastball that was swung at during the 2008 season, broken down into velocities of 85 mph and up. This yielded a sample of 38108 events. There were a number of interesting trends, particularly the correlation coefficients of fastball velocity relating to swing&miss percentage, and foul ball percentage. To me, the foul ball percentage was the most interesting, but I’ll let you decide. …
September 14, 2009
Fastballs are thrown a lot. One reason is that they’re thrown for strikes more often than any other pitch, leading to fewer walks. So why throw a non-fastball? Because curve balls, sliders, and off-speed pitches generate more whiffs and aren’t hit as hard. This data backs up the assumption that fastball should be thrown when balls are nearly as hurtful as a hard-hit ball, while other pitches are more useful when giving up a hard-hit ball is a big loss compared to simply wasting a pitch. The cutter, however, comes with the best of both worlds. It’s thrown in the zone as often as pure fastballs, but generates more whiffs (although not as many as the other three pitches), and isn’t hit as hard. It appears, then, that it’s a jack of all trades pitch, able to be pumped over the plate repeatedly without strong repercussions. …
BTW, here’s Tango’s thread.
What do you do? Have the pitcher execute a sac bunt? Read on!
September 10, 2009
Attached is the current fruit of a long-term project I’ve been working on. Namely, a large reference of minor-league-to-major league translations (zMLE or ZiPS MLE). We get back into the late 70s here as going back to then, there’s always some source that has the statistics required. Once we get earlier, there are some years that have BB and SO data, generally the most important missing data, but it’s extremely spotty and sometimes, not even whole years are filled. Some day, I’ll have these going back for as long as there was minor league baseball as SABR’s database project proceeds.So, what value do these have? For me, two things stand out as the most important. First, having these either reminds us or introduces us to fine players that never got a shot in the majors. We live in a time when Japan is a real alternative option for Ken Phelpsers like Greg LaRocca to have lucrative careers playing baseball and when increased understanding of the usefulness of minor league statistics in the mainstream has resulted in fewer guys getting completely overlooked.
Second, more information helps us increase our knowledge of how players age and develop. For systems that look at comparable players, it’s quite useful to have more 18-21 year-olds that aren’t stars to help us crack, from a statistics standpoint, who will develop and who will not. …