It’s not obvious or dramatic but it looks like the bottom of the called strike zone has moved down a bit matching what David Golebiewski found when looking at this after the 2011 season.  Look at 2008 and 2009, the center of the bottom dashed line falls in the sky blue range indicating something like a 35% chance of a strike call.  By 2011 and 2012, it’s in the green, suggesting roughly a 50% chance of a strike call.

There’s another little bit of trickiness based on how I collected the data above.  Hoping to get a less hazy look at the bottom and top of the strike zone, I limited the data to pitches on which the mlbam stringer had entered an “sz_bot” and “sz_top” (indicated the bottom and top of the strikezone) that were within 0.1 feet of the average values over the five year span.  This would throw out the tall/upright and short/crouching batters.  But maybe all we’re seeing in the images above are changes in how the stringers enter the bottom of the strike zone?  Brian Mills looked at this issue as well as the issue of systematic bias in strike zone designations.  He suggests that there were a changes in how sz_bot and sz_top were assigned some time in 2007.  I left 2007 out of this analysis completely.  To check for moving strike zone designations, I looked at batters who stepped up to the plate in all five years (339 of them) and looked at the average bottom and top that had been assigned to each batter in each year and then the average of those averages for each year.

It looks like something a little funny happened in  2010 where for the same group of hitters the average sz_bot snuck up by about an inch but there doesn’t appear to be a trend in designated strike zone size.

So, has the bottom of the strike zone moved down?  And how much difference could this make?

You can find them here.

Why did we wait until two days before the start of the season for this update?!?!

Well, Dan plays in a high stakes fantasy league that drafted last night and he didn’t want his secret sauce to get out to the public before the big draft.  Anyway, the table below shows ERAs, BABIPs and WHIPs both before and after this adjustment.  Ted Lilly gains the most from this adjustment but Marco Estrada’s jump might matter more to fantasy players;  Dan won Estrada in last night’s auction but had to pay $11, so he wasn’t the only one interested.

[Note: After making this update, we also shifted Ted Lilly towards more of a bullpen role which brings his ERA down to 3.80]

As Tango recently pointed out, Steamer was looking a a little pessimistic this year. Really, we were just a little behind the times. The good thing about basing our regression levels on pitch data is that if pitchers start throwing harder (and they have), Steamer adjusts accordingly. The bad news is that if they throw harder AND they strikeout even more batters than would be expected by this increase (they’ve done this too) we have a somewhat more complicated adjustment to make.

Our projections now attempt to take into account the league wide changes in strikeout and walk rates. The big thing you’ll notice is that ERA projections are down a bit. We’ve also added an adjustment based on the research done by Bill Petti and Jeff Zimmerman who found, among other things, that relievers’ strikeout rates drop off more steeply with age than starters’ strikeout rates do.

8 days till baseball… one major update to come.

I didn’t make adjustments for conference difficulty, teams’ opponents or anything else.  I also didn’t include the 8 teams from “round 1″.  In short, I put little time or thought into these and absolutely zero basketball expertise… but they might still be better than nothing.  Here you go:

*Hiroyuki Nakajima, Kyuji Fujikawa and Hyun-Jin Ryu have been added.

*Pitcher ERAs now take into account our team defense projections.  This will help the pitchers on the Angels among others and hurt the pitchers on the Blue Jays and Rockies.  (Note: the team defense projections differ between Razzball and Fangraphs since the projected playing time differs.)  Thanks to the guys behind them, Jered Weaver’s ERA falls from 4.10 to 3.99 while R.A. Dickey’s moves in the opposite direction, from 3.98 to 4.07.

*Thanks to the work of Clint Hulsey who compiled fastball velocities based on scouting reports on his I R Fast blog, Minor League fastball velocities have been added for 489 minor league pitchers.  Bruce Rondon gets a major boost in his strikeout rate and his ERA falls all the way from 5.34 to 4.08.  Gerrit Cole goes from 4.47 to 4.17.

We’ll keep updating playing time bit by bit and should have one last significant update that will come immediately before the season starts (we might even get to see Jered Weaver’s ERA fall once again).  During the season, our projections will be updated on Razzball and Fangraphs.  If you have a draft coming up, you can get discounted Rotochamp software through the ad on our Downloads page and send some money back our way in the process.

Well, I did some checking and, um, he’s right.

More specifically, Steamer was adjusting down the rate at which hitters get singles too aggressively when forming Major League Equivalencies (using what should be the adjustment factor for *all hits* rather than the adjustment factor for singles). Anyway, after making some adjustments, I checked our year to year MLE BABIPs for batters who moved up a level, batters who repeated a level and batters who made the jump the majors and can now feel comfortable standing behind our projections.

Players whose projections were based largely on minor league stats, of course, see the most benefit. Profar jumps up from .232/.301/.370 to .247/.315/.386. Bryce Harper’s move is less drastic, from .257/.329/.450 to .263/.335/.457. Both projections are still notably pessimistic compared to the other forecasters on Fangraphs (ZiPS, Oliver, James and the Fans), and this is always cause to be wary, but the gap has narrowed somewhat.

One last note, our adjusted system will still, to some extent, under-project players who go from the minors to a full MLB season. Historically, players who had more than 300 MLB PA following a season with 300 minor league PA’s over performed their Steamer BABIP MLEs. I’m okay with that. A Jurickson Profar who gets close to a full season’s worth of PA is more likely to be a Profar who has exceeded expectations than one who has fallen short.  This gets tricky though and it’s something we’ll need to revisit in the future with a little more data on hand.

And here is a plot showing the difference between the two images above.  The areas where extra velocity helps the most are dark blue.

These are the run expectancy changes due to 90 and 95 mph pitches (thrown by a right-handed pitcher to a right-handed batter) by location (as seen from the catcher’s point of view).  If you’re a pitcher, blue areas are good and red areas bad.  I was expecting to see that hard-throwers have disproportionately more success (more blue) up in the zone but, just based on these graphs, it seems like the advantage of an extra 5 miles per hour is spread fairly evenly across locations.

Note: kwERA = 5.4-12*(K-BB)/PA