Shoeless has recently been having fun with Bunty McBunterson, and all that good stuff. I can’t wait to see how his career actually goes. Of course, people have been wondering how the bunt works in OOTP for some time, and for just as long no one has really known. The game doesn’t really tell you anything about it from a stats perspective other than counting successful sacrifices and printing results on the game log.
Real teams would know, of course.
They would have numbers, or, if they were old school they would have, if nothing else, the eye test and an old coach in the background who’s spitting tobacco and grumbling how this kid could really lay one down.
All we have in OOTP, though (other than the bunt and “bunt for hit” ratings), are SACs and game logs.
You know where this is going, right?
It struck me a while back that, since the game logs actually note when a player is “bunting for hit” that I could gather some data. And, of course, that’s what I’ve done. In particular, I’ve sorted out every “bunt for hit” attempt noted in the logs, and indicated their success or failure. Here’s the data, split by team/player:
Two Notes:
- This data is games through June 30
- BFH = Player’s Bunt For Hit rating (remember, it’s relative!)
| Team | Batter | BFH | ATT | 1B | Out | AVG |
|---|---|---|---|---|---|---|
| Atlantic City Gamblers | Bradley Sheen | 6 | 1 | 1 | 0.000 | |
| Boise Spuds | Ramón Miranda | 7 | 1 | 1 | 0.000 | |
| Ricardo Ruíz | 9 | 4 | 2 | 2 | 0.500 | |
| Brooklyn Robins | Ignacio Venegas | 6 | 2 | 2 | 0.000 | |
| Tim Torres | 8 | 1 | 1 | 1.000 | ||
| Calgary Pioneers | Tashfin Modupe | 5 | 1 | 1 | 0.000 | |
| California Crusaders | Jorge Lugo | 7 | 1 | 1 | 1.000 | |
| Mitch Dalrymple | 6 | 2 | 1 | 1 | 0.500 | |
| Charm City Jimmies | Tomás Guillén | 5 | 1 | 1 | 0.000 | |
| Chicago Black Sox | Joe Mills | 9 | 1 | 1 | 1.000 | |
| Luis González | 8 | 6 | 2 | 4 | 0.333 | |
| Tomás Durán | 8 | 14 | 6 | 8 | 0.429 | |
| Des Moines Kernels | Jorge Aranda | 9 | 1 | 1 | 0.000 | |
| Edmonton Jackrabbits | Robert Menzies | 8 | 6 | 1 | 5 | 0.167 |
| Wilson Villanuela | 8 | 2 | 1 | 1 | 0.500 | |
| Hawaii Tropics | Doeke Soethout | 5 | 2 | 2 | 1.000 | |
| Las Vegas Hustlers | Kinfu Lugono | 5 | 1 | 1 | 0.000 | |
| Tom Rudge | 5 | 1 | 1 | 1.000 | ||
| Long Beach Surfers | Ira Sánchez | 7 | 4 | 4 | 0.000 | |
| Louisville Sluggers | Théo Bourges | 6 | 1 | 1 | 1.000 | |
| Madison Wolves | Rodger O'Connor | 5 | 1 | 1 | 1.000 | |
| Montreal Blazers | Casimiro Mouriz | 8 | 10 | 5 | 5 | 0.500 |
| Phoenix Talons | Tommy Holman | 5 | 1 | 1 | 0.000 | |
| Portland Lumberjacks | Jaime Ramírez | 7 | 2 | 2 | 0.000 | |
| Jorge López | 7 | 5 | 5 | 0.000 | ||
| Rockville Pikemen | Manuel Rivera | 6 | 2 | 2 | 1.000 | |
| San Antonio Outlaws | Mennac Shakes | 8 | 11 | 5 | 6 | 0.455 |
| Twin Cities River Monsters | Juan Luis Manuel | 7 | 3 | 2 | 1 | 0.667 |
| Wichita Aviators | Hervé Billy | 5 | 1 | 1 | 0.000 | |
| Jorge Rincón | 7 | 9 | 4 | 5 | 0.444 | |
| Yellow Springs Nine | Ángel Ruíz | 8 | 2 | 2 | 0.000 | |
| 100 | 39 | 61 | 0.390 |
Lots of fun stuff here, right? (tip of the hat to Brooklyn’s I-Gas, who got me thinking about this one in the first place). Of note—across the league, bunt for hit has been successful 39 of 100 times, or good for a .390 clip. This seems high to me, but what do I know? I mean, there is a lot of game theory behind that number. Bunt at the right times, and you probably can hit that kind of rate. Or if infield shifts are in play, and a guy decides to bunt, it’s almost a concession, right? How OOTP does its magic here is a total mystery, and that’s before we get to the fact that a sample of 100 is WAY too low to make any concrete statements about, and before we note that the OOTP manager’s strategy setting on bunts probably influences this, too.
Still, there it is.
I got to wondering about the BFH ratings. Do guys with higher BFH ratings bunt more often, or are they more successful when they do?
Parsing the data above by BFH ratings gives you the following:
| BFH | ATT | 1B | Bunt-Out | AVG |
|---|---|---|---|---|
| 5 | 9 | 4 | 5 | 0.444 |
| 6 | 8 | 4 | 4 | 0.500 |
| 7 | 25 | 7 | 18 | 0.280 |
| 8 | 52 | 21 | 31 | 0.404 |
| 9 | 6 | 3 | 3 | 0.500 |
So, yes, guys with larger BFH ratings relative to others, bunt more often. In this league and at this sample there is a demarcation between 6 and 7. Also, in this very small sample size, the success rate between the 7-8-9 guys seems to jump about a hundred points each. My guess is that if I pull this data at the end of the year, those numbers would change, but that’s where they are now.
As far as the high success rates of “low” bunt skills (5 and 6), I’m at a loss. Could be random success that will fade with practice, could be bad bunters who succeed due to shifts, could be structural OOTP things. I don’t know. But in the end the fact that these are big batting average numbers makes one have to at least acknowledge something could be going on in the game code.
Of course, I should note that I also can’t say I know what those numbers should be.
Maybe it’s true that bunt game theory results in bunts falling for a high success rate?
You feel free to tell me.
