What is DFS?

I didn't know what DFS was at this time last year. After much research, some fortuitous timing, and a little luck I now work at one of the biggest companies in this rapidly growing industry.

Daily Fantasy Sports (DFS) represents this weird microcosm of year-long fantasy sports and sports-betting, offering a vehicle for fans to leverage their (fantasy) sports knowledge against others for cash. Unlike the online poker boom of a decade ago DFS has seen huge support from the major professional support leagues. Leagues know that the more time fans and spectators spend thinking about and researching sports the more their own industries will grow and flourish. DFS enhances the way fans experience spectator sports, which is very much in line with the motivations of the individual leagues and sports entertainment industry as a whole.

I learned about the industry last fall when I saw a few ads for various sites while watching TV and while doing fantasy football research for a league with my buddies. I thought it was neat, partly because I had a ton of free time on my hands (I had just leftNorthBridge, my first post-college job) and partly because I love statistics and making unnecessary models for everything.

The concept behind DFS contests is very simple. Each week in the NFL, for example, real players are assigned DFS salaries based on their projected fantasy performance. As a contestant you effectively playing the role of GM or Head Coach. You are given a salary cap and your goal is to build a lineup (given certain roster requirements) of players that will score the most combined fantasy points in that week’s contests.

It’s a big optimization problem

On the surface DFS is a very simple optimization problem: maximizing fantasy point output under salary and roster position constraints. As such, if you have accurate fantasy point projections for each player, you can create a simple linear optimization model that will create the ideal lineup for you under the various constraints.

This is what I set out to do last fall, and it was quite fun. The point projection model was very simplistic – fantasy ‘expert’ opinions were aggregated (truth in the masses) and average projections were used for each player to determine a baseline level of expected fantasy output. These were then plugged into a linear optimization model in which player projections were matched up with player salaries from various DFS sites, and an optimal lineup was created. This optimal lineup represented the ideal combination of inexpensive value players and high-profile superstars that would be expected to maximize total fantasy point production. Awesome.

 

Player salary vs. projected rank with trend line.
Blue dots above the orange line represent players who are priced higher than their projected performance. Dots below the trend line represent under-priced players who are projected to out-perform their salary.

Unfortunately, when I entered these lineups into the big contests on a few different sites, I never seemed to win much of anything. This is where my simplistic modeling and projection from last year was sub-optimal – there’s a huge amount of game theory involved in DFS, and I wasn't thinking about that aspect in the slightest. More important than an optimization model is a coherent strategy with sound reasoning tailored to the specific contest you are entering. My next post will overview the different types of contests in the DFS world and how to approach them each strategically.