Looking at updating a projection in-season. Beware of math.
Fearless Leader’s entry today on how to improve graphs has inspired some conversation at BtB and Tango’s blog. For the most part I agree with everything Dave says – I do think that having the WAR values on the y-axis is helpful, which is about my only reservation with his advice. But. His graphs were […]
Let’s try a little thought experiment. Let’s say that tomorrow morning Bud Selig declares that he’s exercising the “best intrests of baseball” clause to have Albert Pujols‘ contract nullified, making him a free agent immediately. How many teams offer him a job? And how much money do they offer him? Yeah, I know – that […]
In my last article, I looked at how players regress to the mean, and how players on the borderline between the minors and majors might not have a readily identifiable mean to regress to. But what if we add in AA players? It seems that adding AA players does not give us a trimodal distribution; […]
A closer look at how regression to the mean affects players at the extremes.
Regression to the mean: good for groups, but it can’t tell the future. A graphical analysis.
CBS News had a reporter team at the Pitch F/X Summit in San Francisco, and here’s their report. It’s all stuff from the game afterward, not any of the presentations (the PowerPoint slides of which are available, though). As a sort of counterpoint, Bruce Bochy mentioned “paralysis by analysis.” Where I take issue with that […]
Does it help us predict future performance?
Why we should be spending less time arguing about BABIP, and more time looking at how to convert DIPS theory into runs.
A preview of shape of things to come.
I’ve been playing with the Hit F/X data from Sportsvision for a little while now, and I think I finally have something worth sharing with the class. If you check out the first THT Annual, you’ll find an article from Robert Dudek about the importance of hang time in how easy it is to field […]
Ultimate Zone Rating is now everyone’s favorite defensive stat on the Internet. But how reliable is it? Let’s define reliable as year to year persistance. It’s not the only definition, but it’ll do. We’ll measure it using weighted correlation coefficient. And for good measure, we’ll take a look at how to use it to regress […]
Why some arguments don’t need to be had.
We have a lot of smart readers here at THT, and a lot of you are simply budding THT writers in waiting. I got my start writing for the blog Statistically Speaking. A lot of our current THT writers worked for (and still write for) Beyond the Boxscore. Both of those sites are currently recruiting […]
One of the miracles of the Internet is that so much is preserved for posterity that otherwise would just get washed away. Here’s an oldie but goodie from Ron Shandler, talking about the way he adjusts his projections: As an example, let’s look at Pujols. After hitting 37, 34, 43, and 46 HRs, his baseline […]
Comparing FIP, xFIP and tRA.
Retroera SZR now covers the outfield, as well. These are park-adjusted based upon one year of data, unregressed. This is not ideal, of course, but will be addressed (hopefully) in the next update. I calculate the average rating in each park by season, weighting the home team’s performance so that it does not take up […]
Or deal with the draft. You choose.
TusconRoyal breaks down DL time by team, position and more. This is seriously one of the coolest things I’ve seen in a long time.
The funny thing about the improbable is that it’s not impossible.