By: Dan Conway, director of the Loras College Center for Business Analytics
One of the great things about analytics is that one can leverage the innovations and discoveries in one discipline and apply them in another discipline in order to derive new insights and enable better decision-making. This repurposing of knowledge has worked well in many areas of business, including finance, operations, human resources, and marketing.
We see similar innovations from analytics and big data in sports, health care, and politics. Some of these innovations are exciting, inspiring, and transformational. Others are being used in politics.
It’s now time for the swag discipline to feel the analytics: Fantasy football.
Year after year, one player in my fantasy football league pummels me mercilessly in matchups, often in direct proportion to the smack talk I initiate before the games begin now that I think about it. This year, I am going to employ analytics to challenge my nemesis to see if my team can finally compete against Sister Margaret Mary Cosgrove, a retired accounting instructor at Loras College. I think this might be the year. From here, it looks like smooth sailing.
So, how can analytics be used in decisions a coach might face in fantasy football? The main decisions coaches face are (1) who to draft and (2) who to play each week, and (3) when to trade a player.
Looking for equivalents in business, a team can be thought as a financial portfolio. Players are assets and they have an expected value and a variance (good/bad days and really good/bad days), moving similarly in fantasy points weekly as stock prices might move. Bench players represent options that can be exercised in the event that a starter experiences unexpectedly poor performance or injury. Trading has a natural parallel.
In business, we also consider macro impacts such as a high interest rate environment (like playing the Carolina Panthers twice in a season is a difficult environment) or low interest rate environments (taking candy from the Cleveland Browns is a favorable environment).
How does one choose a portfolio? One might look at macro indicators like rates on risk-free assets, or one might look at the competitive landscape and look for the highest risk adjusted return. In fantasy football, running backs often have lower variance than receivers; so financial portfolio selection would suggest we acquire running backs ahead of receivers.
Who to play? If the goal is to win, and the other team appears superior, then the answer might not be to play the players with the highest expected returns, but rather play some with the highest variance. We see such strategies when a hockey coach pulls a goalie in the last minute, when a basketball team fouls opponents and shoots wild three-point shots, or when a football team throws a Hail Mary pass toward the end of a game in an act of desperation. If one fantasy team is expected to lose, then that team should play high variance players such as quarterback Phillip Rivers rather than steady performers such as Tom Brady.
If one views bench players as stock options, then the natural way to measure their value would be to use Black-Scholes option pricing models. Black–Scholes is a mathematical model of a financial market containing derivative investment instruments. These equations contain enough Greek symbols to make Zeus blush, but can be used to rank available players to serve as insurance, or risk mitigation instruments.
I shared my analytically-based game plan for fantasy football with my parents looking for support. My mother went and hid in the bathtub covering her head with the family Bible. My father cradled up under the workbench in the garage. I’m not sure they understand the concept of smooth sailing.
Game on, Sister Margaret!
Learn more about Loras College’s Executive MBA in Business Analytics program.