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A New Way of Measuring Home Field Advantage

Publication Date: March 27, 2007

I've looked at the topic of home field advantage before (although I think it's been a few years) and came away somewhat dissatisfied with the results (there, there, it's all right; I'm generally dissatisfied with most of what I do -- that's why I keep working). This week I want to try out a new metric that I think cuts a little finer by utilizing a measure that takes game scores into account as well as wins and losses. The one downside to it is that the final measure doesn't translate into any easily-understood measure like runs or games, but it at least gives us an interesting ranking to talk about.

What I've done (and I'm going to be intentionally sketchy on the math this time, just because it's not that interesting) is to look at a modified version of a metric called Strength of Victory (SOV), which comes from the football world and which Paul Kislanko reminded me of recently. Very roughly speaking, SOV is the difference of the scores divided by the sum of the scores in a game, so that in almost every case the result is a good measure of how much a team dominates a game. The version I'm using runs from -1 (being shut out) through 0 (a tie, not that there's any such thing) to 1 (shutting the other team out).

The disadvantage of using just win-loss figures, besides the small number of home-road pairs that each team gets, is that really good or bad teams tend to win or lose consistently in both locations. If a team is 11-1 in conference at home and 10-2 on the road, that doesn't really tell you much about their home field advantage. On the other hand, if they won the home games by an average of 10-3 and the road games 7-5, that's useful information. Using the SOV takes that into account. Since it's a ratio, so that a 6-4 game counts the same as a 9-6 game, it also eliminates the park factor from consideration, since both teams' scores are affected to the park factor cancels out. The one weakness comes from the nature of 0, so a 2-0 shutout is considered the same as 12-0. We'll just have to live with that, since it doesn't come up often enough in college ball to really change things.

What I'm looking at, then, is the difference in the average home SOV and the average road SOV for each team for games against teams that they played both home and away in the last four years (the same data set used to construct the park factors). Here are the twenty-five teams who seem to do the best job of taking advantage of their home park:

  1 Oklahoma State            0.277
  2 Clemson                   0.276
  3 Fresno State              0.274
  4 Texas                     0.266
  5 Troy                      0.266
  6 Wright State              0.259
  7 Texas Tech                0.258
  8 Stetson                   0.256
  9 North Carolina-Asheville  0.249
 10 Norfolk State             0.243
 11 South Florida             0.242
 12 South Carolina            0.240
 13 IUPU-Fort Wayne           0.239
 14 Coppin State              0.233
 15 Texas-Pan American        0.233
 16 Mississippi Valley State  0.231
 17 Lafayette                 0.231
 18 Minnesota                 0.230
 19 Wisconsin-Milwaukee       0.230
 20 Old Dominion              0.222
 21 Yale                      0.220
 22 Baylor                    0.215
 23 Tulane                    0.214
 24 Delaware State            0.211
 25 Oral Roberts              0.210

The number is just the difference in the home average SOV and the road average SOV; don't pay too much attention to it. I'm ignoring a few teams here -- teams that haven't been in D1 for four years aren't included, since they don't have enough pairs to trust the results, and Hawaii-Hilo is ignored, since their schedule cause some major headaches in trying to evaluate park effects and related events like this.

Some of these teams get to take some major advantage of their advantage, so to speak -- the days when Texas never, ever left home are gone, but they still play at home an awful lot, for example. Others don't, really; Wright State, for example, doesn't have that many non-conference home games.

There are actually about thirty teams that appear to play better on the road, in absolute terms, than they do at home. Here's the bottom twenty-five:

263 St. Louis                 -0.008
264 Alabama A&M               -0.008
265 Alabama State             -0.009
266 Arizona                   -0.011
267 Murray State              -0.012
268 Lipscomb                  -0.013
269 Louisiana State           -0.019
270 Alcorn State              -0.019
271 Northeastern              -0.021
272 Western Kentucky          -0.025
273 Brown                     -0.041
274 Penn State                -0.053
275 Maryland                  -0.056
276 Fairleigh Dickinson       -0.058
277 Long Island               -0.074
278 Jackson State             -0.077
279 Maryland-Eastern Shore    -0.077
280 North Carolina-Charlotte  -0.093
281 Radford                   -0.098
282 St. Joseph's              -0.101
283 Vermont                   -0.109
284 Ohio                      -0.111
285 Maine                     -0.112
286 Holy Cross                -0.124
287 Princeton                 -0.126

The bottom of this list appears to be mostly northeastern, but I can't spot a weather reason for it, since almost all of the home-away pairs for these guys are conference games or series against reasonably close geographic neighbors. Arizona's presence is interesting; I'm not sure what the implications are of having a major conference team that plays slightly better on the road, but I could make up some interesting scenarios.

One thing that I don't notice, which sort of blows my closing, is any correlation between these numbers and the reputation of the programs for the quality of their facilities; most of the stadia generally regarded as best are not on the top list, and some of the ones on the bottom list are regarded as quite nice.

Tournament Watch

This means absolutely nothing, ignore it.

This is one generic layman's predictions for who gets in the tournament. I'm not going to bother picking a team from the one-bid conferences, since the conference tournament will just be a crapshoot, but if I only list one team from a conference, they'll get an at large bid if they don't get the automatic bid.

America East   WAC                   Minnesota             Stanford
A10            Florida State         Coastal Carolina      Arizona
Big East       Clemson               UC Irvine             South Carolina
CAA            North Carolina State  UC Riverside          Kentucky
Horizon        Maryland              Cal State Fullerton   Vanderbilt
Ivy            North Carolina        Long Beach State      Arkansas
MAAC           Virginia              East Carolina         Mississippi State
MAC            Miami, Florida        Rice                  Mississippi
MEAC           Stetson               Southern Mississippi  Louisiana State
Mid-Continent  Texas                 Memphis               Auburn
Mountain West  Oklahoma State        Wichita State         Florida
NEC            Missouri              Southern Illinois     College of Charleston
OVC            Oklahoma              Evansville            Louisiana-Lafayette
Patriot        Texas A&M             Oregon State          Troy
Southland      Baylor                Arizona State         Pepperdine
SWAC           Kansas State          Southern California   San Diego

Pitch Count Watch

Rather than keep returning to the subject of pitch counts and pitcher usage in general too often for my main theme, I'm just going to run a standard feature down here where I point out potential problems; feel free to stop reading above this if the subject doesn't interest you. This will just be a quick listing of questionable starts that have caught my eye -- the general threshold for listing is 120 actual pitches or 130 estimated, although short rest will also get a pitcher listed if I catch it. Don't blame me; I'm just the messenger.

Date   Team   Pitcher   Opponent   IP   H   R   ER   BB   SO   AB   BF   Pitches
3/03 Arkansas-Little Rock David Klumpp Creighton 8.1 10 2 0 1 8 33 38 123
3/16 Kentucky Chris Rusin Arkansas 6.0 8 7 7 4 7 25 33 123
3/16 Hartford Szymanski Oklahoma State 9.0 7 4 4 4 5 33 39 136(*)
3/16 Vanderbilt David Price Mississippi 10.0 4 2 2 2 14 31 37 142(*)
3/16 Mississippi State Aaron Weatherford Florida 6.1 9 8 4 4 6 28 33 122
3/16 North Dakota State Jake Laber Creighton 6.0 10 7 7 4 2 23 31 133
3/16 Savannah State Patrick Ballew Bethune-Cookman 8.0 10 4 1 3 2 31 37 125
3/16 Butler Jon Dages Wright State 8.0 10 4 4 2 6 32 36 130
3/17 Florida A&M Cirilo Manego Indiana 8.0 7 2 2 2 7 30 33 129
3/17 Louisiana State Jared Bradford South Carolina 8.1 6 3 3 2 6 29 32 132
3/17 New York Tech Joe Esposito Florida Gulf Coast 6.2 3 3 2 6 9 21 27 126
3/17 Savannah State Mark Sherrod Bethune-Cookman 7.1 5 1 1 5 5 23 30 131
3/17 Lamar Allen Harrington Texas-Arlington 9.0 7 1 1 1 8 32 34 123
3/17 Portland Ari Ronick Utah 5.2 6 5 5 4 3 22 28 123
3/17 Butler Bryan Bokowy Wright State 9.0 7 1 1 1 8 35 36 140
3/18 Prairie View A&M Matt Chase Texas Southern 8.0 11 3 2 2 8 32 35 126
3/18 Cleveland State Brandon Hewitt Missouri 7.1 7 5 5 4 3 29 33 124
3/18 Fordham Tom Davis Manhattan 8.2 3 1 1 5 10 29 34 134(*)
3/18 Northeastern Dabrowiecki George Mason 6.2 8 3 3 4 14 28 32 133(*)
3/18 Southern Mississippi David Clark Kent State 6.2 5 4 4 6 7 25 32 121
3/18 George Washington Derek Haese Marist 8.0 10 5 3 2 8 35 38 134(*)
3/18 Alabama State Z Hilburn Jackson State 9.0 5 2 1 3 9 32 36 132(*)
3/20 New Mexico Jarrad Watkins New Mexico State 6.0 5 4 3 4 2 19 26 121
3/20 William and Mary Tyler Truxell Norfolk State 6.2 12 4 3 2 6 31 34 123
3/21 Virginia Tech Evan Frederickson Longwood 7.0 2 0 0 6 10 23 29 130
3/23 Maryland Casey Baron Clemson 8.0 4 0 0 1 7 27 29 121
3/23 Tennessee James Adkins Georgia 8.0 6 3 2 5 10 29 34 134(*)
3/23 Nebraska Tony Watson Missouri 10.0 3 1 0 3 7 32 35 131
3/23 UC Davis Fox Loyola Marymount 7.0 5 2 2 3 2 25 29 128
3/23 Vanderbilt David Price Arkansas 6.0 6 5 4 4 8 24 30 125
3/23 Winthrop Alex Wilson Virginia Military 9.0 4 2 1 3 14 30 34 137(*)
3/23 College of Charleston Nick Chigges Western Carolina 8.0 9 5 3 5 9 33 38 131
3/23 Portland Ari Ronick Dallas Baptist 8.0 6 2 1 3 5 31 35 139
3/24 Wright State Holleran Cleveland State 8.1 13 7 6 2 7 36 41 140(*)
3/24 East Tennessee State Brandon Langston North Florida 9.0 5 0 0 1 8 33 34 123
3/24 Florida A&M Cirilo Manego Bethune-Cookman 5.1 11 12 7 3 6 28 33 121
3/24 Fordham Javier Martinez George Washington 10.0 5 3 2 8 3 31 42 150(*)
3/24 IUPU-Fort Wayne Cole Uebelhor Indiana 8.0 10 6 6 2 3 33 37 121
3/24 Alabama A&M Bernard McKinney Mississippi Valley State 7.0 11 10 7 7 2 28 37 132(*)
3/24 Arizona Brad Mills Northern Colorado 7.0 5 2 1 0 10 27 27 122
3/24 West Virginia Maxwell Seton Hall 9.0 7 5 5 6 2 31 41 140(*)
3/24 Marshall Brian Chrisman Tulane 9.0 5 4 0 6 7 35 41 150(*)
3/24 Wagner Joe Testa Virginia Commonwealth 7.0 9 4 2 0 8 28 28 121
3/24 Youngstown State Engle Butler 9.0 6 4 3 3 10 32 39 127
3/24 Akron Frank Turocy Ball State 7.1 9 7 7 3 2 30 33 134
3/24 Arizona Preston Guilmet Northern Colorado 9.0 3 0 0 1 11 30 33 124
3/25 Akron Steven Zemanek Ii Ball State 9.0 7 5 5 3 3 33 39 137
3/25 Brown Jeff Dietz Charleston Southern 8.0 8 2 1 4 5 31 36 126
3/25 East Tennessee State Caleb Glafenhein North Florida 9.0 11 4 4 1 3 36 40 125
3/25 Florida Atlantic Chris Salberg Louisiana-Lafayette 7.0 7 2 2 7 5 26 34 128
3/25 Stephen F. Austin State Erich Lehmann Lamar 9.0 10 3 3 1 6 35 38 125
3/25 New York Tech Joe Esposito Maine 7.0 5 4 2 6 8 25 33 125
3/25 Samford Chandler Tidwell Murray State 8.2 10 3 3 3 10 34 39 143(*)
3/25 North Carolina A&T John Primus Norfolk State 9.0 8 2 2 4 10 35 40 148(*)
3/25 Texas-Arlington Chris Taylor Texas State 7.0 6 4 4 3 5 25 30 125
3/25 Temple Tom Dolan Massachusetts 8.2 10 3 1 2 9 34 37 143
3/26 Cal Poly Thomas Eager Oregon State 6.2 6 6 6 5 6 22 31 121
3/27 Boston College T Ratliff Hartford 9.0 8 5 5 5 7 30 38 139(*)
3/27 Harvard Eric Eadington Florida Atlantic 6.0 9 1 0 2 7 25 27 135

The Klumpp count is a correction based on an actual pitch count.

(*) Pitch count is estimated. As always, I welcome actual pitch count corrections.

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