Home Plate Umpire's Effect of on Game Events
With the start of the baseball season around the corner, it time to get the stats predictions for the most cherished people on the field, the umpires. More specifically, I wanted to examine the men behind the plate and how they effect the scoring of the games they call. The main portion of the data I used was from the website: The Logical Approach. It contains all the data on umpires since 2000, the year they were combined from being separate AL and NL groups to one MLB group. The following data was used: K/BB, BB/9, Base runners/IP, ERA and Total Runs/Game.
Procedure: To get to the final numbers, I calculated the total of all game scores for each umpire, added these up for all the seasons and averaged them to get the all time average values. Then I used this average and the yearly averages to create yearly "umpire factors" for each year to normalize the stats. I took the umpires that umped in all the nine years I had data for and determined the point when they had regressed to 50% (r-value) of there final value. Using these r-values, I predicted what the umpire's 2009 numbers. I have made the sheet available for all at Google Docs that includes all the umpires assigned to crews in 2009 (including the crew in which they are assigned) and also any umpire that umped at all in the majors in 2008. http://spreadsheets.google.com/ccc?key=pYilmL4DSNmkgSYzN_o80ZA.
Here is a chart of the averages off all the years data, the high and low values of the predicted values and the number of games where the umpire regresses to 50% of their actual value:
| |
K/BB | BB/9 | Base Runner/inning | ERA | Total RPG |
| Average Values for All Umpires | 2.01 | 3.16 | 1.40 | 4.59 | 9.55 |
| Highest Predicted Value | 2.85 | 3.53 | 1.47 | 4.91 | 10.33 |
| Lowest Predicted Value | 1.67 | 2.55 | 1.29 | 4.11 | 8.70 |
| Number of games to get to 50% regression | 35 | 97 | 133 | 97 | 194 |
To get a general idea which umpires are pro-pitcher or pro-hitter, I ranked each umpire in the 5 categories and then added these 5 figure together (not the most scientific method, but will work for general analysis). Here are the top 10 umpires for being pitcher and hitter friendly:
| |
Hitter Friendly | |
| Rank | Name | Crew |
| 1 | Derryl Cousins | O |
| 2 | Paul Schrieber | H |
| 3 | Jerry Crawford | M |
| 4 | Mike Reilly | Q |
| 5 | Gerry Davis | L |
| 6 | Jerry Layne | K |
| 7 | CB Bucknor | L |
| 8 | Gary Cederstrom | D |
| 9 | Greg Gibson | N |
| 10 | Tim McClelland | N |
| |
Pitcher Friendly | |
| Rank | Name | Crew |
| 1 | Doug Eddings | J |
| 2 | John Hirschbeck | A |
| 3 | Brian Gorman | L |
| 4 | Phil Cuzzi | M |
| 5 | Bob Davidson | C |
| 6 | Bill Miller | O |
| 7 | Brian O'Nora | D |
| 8 | Ron Kulpa | B |
| 9 | Jim Wolf | D |
| 10 | Dan Iassogna | G |
Finally, I used these numbers to see how they would effect a single pitcher. Using the ERA numbers, I looked at the Royal's Gil Meche in 2008. I added how much the each home plate umpire's ERA differed from the average ERA. He had an extra 2 runs scored against him because of umpire differences over the season. Taking these differences into account, his ERA drops from 3.98 to 3.90.
Improvements – I wanted to get this data able available before the start of the season, but feel it is far from complete. I plan on adding these two improvements for future analysis:
-
Incorporate Pitch F/X. I currently don't have all the data downloaded, but hope to have it soon. I plan on implementing something like Jonathan Hale did in this article for the Hardball Times. I would like to see how well the data correlates from umpires actual strike zone to the game stats.
-
Use Retrosheet data and Park Factors. With Retrosheet I would be able to go back further in time and be able to get any stat need (please suggest any additions that would be helpful to the research). Some umpires only work certain areas of the country, so their numbers might be skewed do to the parks they work in.
Conclusion: With a range of +/- 1.6 R/G for all the umpires, teams and pitchers will need to adjust for the umpire behind the plate. Hopefully I give a people a better understand of which umpires have what tendencies. Finally, I plan on expanding the research to have more and better data, including the data from Pitch F/X. As also I open to comments and suggestions.
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Pretty sweet, although I'll need another pass later.
Are you worried at all that some umpires called more games in hitter friendly ballparks or with a set of bad starters on the mound? Or does the huge amount of data make that only a small issue?
Beyond the Boxscore // Calling BJ Upton lazy is lazy.
Yes and no
Sample Size — By regressing the values, the ones that are at extremes have proven that they belong there
Ballparks — I believe it could be a problem and as I stated in #2 of improvements, I will look at it in the future
by Jeff Zimmerman on Mar 27, 2009 11:04 AM EDT up reply actions
Umpire usage
Great work here. I’m just wondering how MLB assigns umpires. Do certain crews work primarily in certain areas (west coast, midwest, east coast, etc.)? Or do they try to spread every crew all over the country, umpiring teams in every division? If there is a practice (maybe with the most senior crews) of having them umpire more in a certain area or region, then that could skew results. But this is an excellent bit of work.
The immoderate moderator
by Scott McKinney on Mar 29, 2009 3:01 AM EDT up reply actions
They do work certain parts to an extent.
I hope to do one with about 4 times the data, but wanted to get out what I had before the season starts.
by Jeff Zimmerman on Mar 29, 2009 12:37 PM EDT up reply actions
Not sure if you've seen ...
this.. since it’s from this time last year.
My attempt at linking Pitch F/X with umps (in aggregate vs individuals).
I am a bit disappointed for only one reason
I was hoping to find that if I looked at these numbers hard enough, it would back up my claim that Angel Hernandez is the worst umpire out there, but I just can’t quantify that by these stats. I am looking forward to the day that is a proven fact.
* sarcasm might be involved in this comment
and....BEN SHEETS!!! **
**not that BEN SHEETS might be involved in this comment, just BEN SHEETS!!!
(BEN SHEETS might be involved in this comment)
Pitch F/X should give more information
I figure I will look into how consistent they are in strikes and ball — which might help you. Any thing else I should look for.
by Jeff Zimmerman on Mar 29, 2009 12:38 PM EDT up reply actions
I think Hernandez is horrible
and this data isn’t going to help you out, because of the reason that he’s horrible: He’s the most inconsistent umpire behind the plate.
It’s one thing to be fairly neutral all the time — it’s quite another to be pitcher friendly one time out and hitter friendly the next. I’d prefer to have a Derryl Cousins as a pitcher even though he’s a hitter’s umpire, simply because I at least know what to expect when I walk out there. With Hernandez, you have no idea whether he’s going to have a big zone or a small zone on any given night, so how can you prepare for that?
"I just wish that the late Harry Caray were still around so I could hear him mispronounce 'Kosuke Fukudome' every fukun' night" -- Dennis Miller
I am really close to seeing who is the most inconsistent.
Just working out a few kinks with Pitch F/X
by Jeff Zimmerman on Apr 10, 2009 12:54 PM EDT up reply actions
Jerry Crawford certainly affected one game I saw
Detroit-Oakland ALCS playoff game 1 Oct 10 2006. I had good seats on the 3rd base line and saw that NO pitch even a millimeter above the belt was ever called a strike. Too bad for us (Oakland) ZIto was our pitcher. His curve was working great but Crawford wouldn’t give him any strike calls.
According to one article I read later, Detroit knew about Crawford and Leyland told his normally free-swinging team to take pitches. Smart move. They waited on a fastball or changeup and raked.

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