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Operations Research and Fantasy Football

After a very successful year, my fantasy football teams are crashing and burning in the playoffs.  For those who do not know fantasy sports, fantasy football involves a group (8-12 people) drafting NFL players at the beginning of a season.  Each week, my team gets points based on the success (or lack thereof) of the players in their “real” games.  If my players get more points than my opponent’s, then I win.  After a regular season,  the best fantasy teams in the league then face off in the playoffs.  Some fantasy sports work a bit differently:  most fantasy baseball leagues collect statistics from the entire year and give points in the final year standings on the categories, without the head-to-head matchups.

One of my teams this year was the best I ever had.  I had the top three wide receivers in the league (Moss, Owens, and Edwards), the second best quarterback (Romo), a top running back (Addai), a great defense (Patriots), and a top kicker (Folk).  My tightend was not great, but that was the only weakness.   Over the regular season, I outscored the second best team in the league by an average of 30 points in a game (teams typically score 60-120 points in a game).  But, sure enough, the playoffs come around, my team goes cold, and I lose the first playoff round.   So now I am just struggling to get third place in the league.

I am not the best fantasy player around.  To be so would require much, much more time than my three-year-old son will allow me.  But I do try to use a bit of operations research thinking in my play.  Some (but not all) key decisions come in the initial draft.  Players are taken in turns in a serpentine fashion:  if there are 10 fantasy players, then the person with the first pick will next get the 20th pick;  the person with the 10th pick also gets the 11th pick).  Given the projected player values (which is the real key to the problem: data!), the “best pick” depends on what you expect others to do, and the relative value of the alternatives.  For instance, if you need a quarterback, and the best quarterback is worth, say, 280 points, with the next best being worth only 200 points (a huge difference), then you better pick that quarterback (unless you are absolutely sure that quarterback will be available when you pick next).  But if there are five quarterbacks in the 280 range, you can afford to wait, since it is more likely that one of them will still be available when you pick next.

Mike Fry, Andrew Lundberg (both of the University of Cincinnati) and Jeffrey Ohlmann (University of Iowa) analyzed this issue in depth in an article published in the new Journal of Quantitative Analysis in Sport.  Their work got a fair amount of press a few months ago, including a writeup in USA Today (sorry I missed it earlier:  New Zealand doesn’t cover football well!).  I just went through the article (while waiting for my son to wake up and enjoy Christmas), and it is terrific, going well beyond the obvious points.  I particularly liked the analysis of the value of each of the draft positions.  There is a view that drafting early is best, but the serpentine nature of the draft evens things out.  With the data they looked at, it is true that the first position is best, but the differences are quite slight, and the value is not monotonic in draft position.

At the end, though it comes down to player projections.  As the article quotes:

“If you value Ryan Leaf as the best quarterback, it’s going to tell you take him when it’s time to take a quarterback,” Ohlmann says. “If you give me bad projections, I’m going to give you some very bad advice.”

{ 1 } Comments

  1. Bob Hett | December 26, 2007 at 12:46 am | Permalink

    Boy, I’m having a really tough year myself. It really does sound like you had a great draft. It’s a shame your team went cold on you, but as you well know, sometimes the ball takes funny bounces.

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