Friday, July 15, 2016

Ultimate Frisbee

The concept of Fantasy Football + computer simulation + statistical analysis + a game accessible to all students = the Ultimate Frisbee Draft.

Back in my student teaching year, I went a bit off the rails with project design in my Stats class.  After a rough first semester of Stats that turned around with a successful Minute to Win It project, I decided to tie every content area into some project.  My favorite, and the longest-lasting one over seven semesters, is the Ultimate Frisbee Draft.

We lead off the unit by watching one of my favorite movies, Moneyball, as a class.  Even students who have already seen it get a chance to watch it from the perspective of better understanding sports analytics while newbies get introduced to the power of data analysis in the sports world.  This intro event sets up a class discussion around which statistics matter and how someone could use those to predict overall value in any industry.

From there, I introduce students to our sport, Ultimate Frisbee.  I very intentionally didn't choose baseball, football, or another common sport -- these have tons of existing analytical approaches already covering the web that students could simply adopt without deep thought.  In addition, I have a number of students who are not motivated by sports.  Ultimate Frisbee, however, is one of those rare activities that nerds (my robotics students LOVE Ultimate), chatters, and intense athletes can all find really engaging.  To get an intuitive sense of the game, we spend a day outside or in the gym playing short games during class.  I use the time after games to reflect on the last match and encourage students to track specific stats of their own during the next game.

Finally, we get to the data.  I wrote a computer simulation that plays games of Ultimate between virtual players and tracks all throws, catches, and drops, per player, during the game.  After each virtual player plays 30 games (a number large enough for analysis but small enough for lots of noise to creep into the data), I dump the data of all 98 players into a giant spreadsheet.  From here, teams of students start to dig into the overwhelming pile of numbers to figure out who they want to draft for the ultimate Ultimate team.

Once given the hook and a chance to explore, I introduce the statistical tools that will become their friends.  Depending on when I teach it, I like to start with a search for the stats that actually matter, using a few rounds of multiple regression with the most important team stat, winning, against nearly everything else.  Since there are only 30 games, picking a player based on their number of wins has far too much noise to be reliable.  However, if you find that something like short catch percentage or the number of successful long throws are highly correlated across all players, you can use those much larger numbers and sort by categories with less noise.

We also talk about tools for sorting individuals.  You could use the raw stat, a rank order, a percentile, or a z-score.  Each has their own benefits.  When students want to combine two stats into one "power stat", I usually recommend the use of the z-score since it makes both values unitless while retaining a the magnitude relative to the mean.  Since there is no obvious right way to do all of this, it leads to fantastic student questions and discussions.

Some groups of students take my recommended approach of finding key stats, getting z-scores, adding the totals, and sorting.  Others modify this to break players into categories / positions, choosing a strong thrower or two with a supporting cast of receivers.  Others put their money on defense, looking for players who effectively deny the Frisbee on the logic that it ends drives quickly and gives them a short field for offense.

On the practice draft day, student teams are assigned a random draft order.  From there, they have 30 seconds to pick an unchosen player when they are up.  I only do 2-4 rounds in the practice draft and then assign the remainder of the slots on their teams with equivalent players.  Once teams are selected, I run their teams back through the original simulator to have them square off against one another.  The simulator will actually play through a full game, simulating one throw at a time based on probabilities from the throwing player, their defender, the match-ups of the receivers, the selected receiver to get the pass, and whether or not the pass was caught based on ability, defense, and other factors.  Fortunately, computers are crazy fast, so this takes fractions of a second.  The simulator, looking old-school fancy with its command-line spewing of text, prints out the records of each team as they play every other team 21 separate times, each up to 15 touchdowns.  It then enters into a "tournament mode" where teams go into a bracket (based on their "regular season" rank) and face off in a single match.  The 21 games per competitor series gives useful feedback on which teams are statistically solid, while the playoffs is a chance for even the worst of underdogs to eek out an occasional win.  This is analogous to many real sports, and it leads to more interesting discussions that a lesson on the "Law of Large Numbers" could ever do.


All of this is just a practice round -- I do this to help students become familiar with the format.  However, it also has the nice side effect of motivating teams with awful strategies and analysis to pull things together.  I have seen a number of teams make a strong turn-around based on lessons learned in the practice round.  When students share out their strategies, I have them focus on process, not their "secret sauce", since they tend to get pretty competitive.

By the final game day, teams are ready with spreadsheets, have a process to cross out the selected players as they get drafted, and get pretty audibly upset when someone takes their star player right in front of them.  Coming in much more organized, the draft usually takes only 5-10 minutes for all 7 rounds to complete.  After running through the regular season, I hand out awards/candy to the top teams, but then save the ultimate treat for the playoffs.  I click through just one game at a time here, encouraging teams to cheer and show their pride before revealing their fate.  In the end, we all have a lot of fun, including many students who usually don't get into sports or anything that smells like fantasy football.

Altogether, I spend 6-7 days in a block class with this unit.  It is long, but it is always memorable for students, creates fantastic student questions, and often inspires interesting projects when I provide an open-ended opportunity later in the course.

See videos and spreadsheet links for students to reference / download.

How to get up and running with the simulation:

  • Download and install Python 2.7 for Windows or Mac.  This is the environment that runs that code.  It is a simple "click next" type of installer.  You may want to reboot at the end if things are not running properly in later steps.
  • After installation, download this zip file and unzip it somewhere on your computer.
  • Double click "draft.py" to run the drafting program -- this is where you will setup a class, name the teams, and input the results of the 7-round draft.  Whatever name you give your "period" will be the same name you use later when running the simulator.
  • Double click "simulator.py" to run the season + tournament simulator.  Whenever the screen pauses, just press enter to make the computer do the next thing.  This can be run as many times as you like using the same draft data.
  • Tweet at me, email me, or comment below if things don't work the way they should.  I would love to help you get this running!  Thanks to @stoodle for encouraging me to finally write this up after years of procrastinating!

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