Notice: Trying to get property 'display_name' of non-object in /var/www/html/wp-content/plugins/wordpress-seo/src/generators/schema/article.php on line 52
keyboard_arrow_uptop

After Neftali Feliz threw three strong innings on Wednesday, Jeff Passan made a convincing argument that Feliz belongs as a starter. It's good stuff from Jeff as always, with interesting quotes sprinkled throughout from Rangers pitching coach Mike Maddux and others.

Harry Pavlidis took a quick look at the PITCHf/x data from Feliz's new pitch: the cutter/slider.

Max Marchi added a second part to his series on measuring curveball command. Max investigated how Roy Halladay's curveball aim points differed by count. Max's series is developing some important building blocks for measuring command using PITCHf/x data.

Jeff Sullivan ran across some copies of old scouting reports on Greg Maddux from 1984, when Maddux was in high school. It's interesting to see what the scouts thought his strengths and weaknesses were at that time and where they thought he needed to improve.

Dave Allen looked at how pitch height and speed affected groundball rate for the knuckleballs of Tim Wakefield and R.A. Dickey. I love reading about knuckleballs (doesn't everyone?), and I'm a big fan of Dickey (snicker), so I eat up this kind of stuff. There are some interesting comments, too. Particularly pay attention to garik16 (Josh Smolow), who's done a good bit of research into the knuckleball in general and Dickey in particular.

Jonathan Hale had some interesting comments about my recent strike zone article. Jonathan's thoughts on why the umpire zone changes with ball-strike count made a lot of sense to me. His proposal about expectation bias is one that I particularly want to think about. He also argued, fairly persuasively in my mind, that replacing human umps with robot strike callers would be bad for the game.

Steve Sommer investigated Tim Lincecum's change in approach as his fastball speed has dropped the last few years. Steve did good work here and made some interesting observations, but I can't help feeling that this is still somewhat of uncharted territory. I really wish I knew much more specifically why and how some pitchers are able to adjust and others are not.

Lucas Apostoleris did a profile of Justin Masterson. The profile is very well done, and I particularly was intrigued by the final graph in the article, where Lucas looked at Masterson's pitch speeds by count. It was a very clever idea of Lucas to look at that, but I don't know quite what to make of it. It's not so much that Masterson bears down when he's in trouble. Instead, he cranks it up a notch when he smells blood in the water. This made me want to look at speed by count for other pitchers to see what kind of patterns they have.

I'll close with two older links, the first to a post from David Coleman at Crawfish Boxes that's actually a year old. I just happened to read it recently and was thoroughly impressed. David was responding to John Sickels' post about his growing disillusionment with sabermetrics. David gave a great argument for the place of sabermetrics in understanding the game, and there is a high-quality discussion in the comments to his post.

The second is on a similar topic, a thread from Baseball Fever. The quality of the discussion overall is not up to that in the Crawfish Boxes post, but I particularly appreciated the post by Matt Souders urging a more scientific approach to sabermetrics. Why don't more sabermetricians want to know why?

Thank you for reading

This is a free article. If you enjoyed it, consider subscribing to Baseball Prospectus. Subscriptions support ongoing public baseball research and analysis in an increasingly proprietary environment.

Subscribe now
You need to be logged in to comment. Login or Subscribe
edanddom
3/13
Thanks Mike - great links. Loved the Masterson profile. There was some talk about incorporating Pitch F/X data into PECOTA... simply showing this level of analysis on each player card would be a great half-step toward that goal of integration.