Integrity. Innovation. Impact.

Jeff Ohlmann

Jeff Ohlmann

Assistant Professor of Management Sciences


Ph.D. in Industrial & Operations Engineering, University of Michigan, 2003
M.S. in Industrial & Operations Engineering, University of Michigan, 2001
B.S. in Mathematics, University of Nebraska-Lincoln, 1998

It's the third round of your fantasy football league draft and the hot sleeper pick at wide receiver you didn't think anybody else knew about is suddenly drafted by the team picking right in front of you. Your stomach tightens and your palms sweat. Your strategy is shot and now you have 90 seconds to come up with a new one. So you rifle through the piles of player statistics, but suddenly it's just a bunch of numbers. You don't know what to do but the clock ticks on and with three seconds left, you panic and pick someone based on the fact that he plays for your favorite team.
You vow that next year, you'll have a new strategy, one that's nimble enough to survive little surprises like this. That's where Jeffrey Ohlmann's research might be able to help.
Ohlmann, assistant professor of management sciences, is one of the first people to study sports league drafts from a scholarly perspective.
His model tries to help fantasy drafters overcome the fundamental handicap of not knowing what players will be available to draft in future rounds.
"The basic premise of our model is that a team should select a particular player based on consideration of a player's estimated value, the availability and value of other players, and the team's need at each position," said Ohlmann.
The software Ohlmann is developing runs a computer algorithm to determine the best immediate pick based on what other players are likely to be taken over the rest of the draft. It takes into consideration three factors: estimates of player values at each position (quarterbacks, running backs, etc.); roster spots that still need to be filled; and estimates on the selection tendencies of other managers.
The software then advises players about which positions to draft first and which can wait for a later round.
Today, numerous teams in the NBA and the NFL employ "quant" experts to perform quantitative analysis to guide personnel decisions and in-game strategy. While Ohlmann and his colleagues demonstrate their model with a fantasy football league, he thinks a similar approach could be applied to building a real sports team.
However, he says a crucial step in developing a useful draft day tool that a professional sports team could use is determining the best way to measure a player's abilities. Ohlmann says this could be accomplished by combining quantitative methods with scouts' expertise.
"Quantitative analysis is not a crystal ball and will not be 100 percent accurate in identifying which players are going to be successful," said Ohlmann. "But it will help minimize the error that results when the front office personnel are 'fooled by their eyes' and let emotions affect their decisions."
Ohlmann says the underlying theme of his research has uses beyond fantasy sports drafts. The work is related to the more general problem of how an individual makes choices when those choices may be altered based on the choices other people make.
Ohlmann also has discovered that sports provides an excellent teaching tool for helping students understand quantitative methods.
"Many students are sports fans, and even if they aren't, they can relate to the examples," said Ohlmann.