Game Theory, in its most basic form, is simply the study of mathematical models of strategic interaction among rational decision makers. In “Game Theory and Psychology,” Andrew M. Coleman and Eva M. Krockow describe Game Theory as “a branch of decision theory focusing on interactive decisions, applicable whenever the actions of two or more decision makers jointly determine an outcome that affects them all.” That’s a lot of Oxford lingo, so we’ll look at an extremely raw application: Rock, Paper, Scissors.
We all know the game, and we’ve been in situations before where we can begin to formulate an optimal strategy against an opponent if we see that they are not throwing each outcome (Rock, Paper, or Scissors) at an exact 33% clip. Discussing this idea further, what if we notice our opponent ALWAYS leads with Rock. Would it then make sense for us to let mathematical probabilities decide what we lead with, or would it be better to ALWAYS lead with Paper against this specific opponent? Using this same example, what if we pick up on the fact that our opponent never throws Paper, but utilizes Rock and Scissors equally at 50% each. How would you formulate a plan to beat this player? I’m not sure about you, but I would throw Rock 100% of the time, as the opponent literally can never beat us, only tie or lose.
Realize that these are extreme examples, but we can begin to understand Game Theory and its application in a game like Fantasy Football, where there are a set of commonly known rules (also referred to as “Common Knowledge,” which we will discuss further in the course), a known payout table (where we can clearly see the outcomes of our decisions vs. the other players, or field), and known strategies amongst the field (via the vast number of providers available and the strategies they develop). So what does Game Theory mean to me?
To illustrate this notion, we’ll look at a quick personal example. I was recently invited to compete in the DraftSharks Invitational, a super flex best ball tournament with 60 of the top analysts and high stakes players in the world. I drafted Stefon Diggs at WR22 in the fifth round, took two members buried on the 49ers RB depth chart late, and took Chase Daniel late. Why? The draft occurred prior to the NFL opt-out date, and I knew both Tevin Coleman (confirmed through his wife that his twin toddlers also carry this trait) and Smokey Brown have a blood cell anomaly disease called sickle cell trait. I also knew Matthew Stafford has a lot going on in his personal life, with a toddler at home and a wife battling a (benign) brain tumor. To me, these three players were at an increased risk of opting out this season, as people with sickle cell trait are considered “at extreme risk” with COVID, and Stafford has more than himself to think about when weighing the decision of whether to play or not. Drafting Diggs at WR22 would then have been at his floor, and Chase Daniel, Jerick McKinnon, JaMycal Hasty and Jeff Wilson would all have carried massive upside at their respective ADPs should one of the “at-risk” players have opted out. None of them ended up opting out, but the reasoning and thought process that led me to target those players specifically was entirely rooted in Game Theory.
In the paid area of this course, we will first further break down Game Theory, jump into the psychology associated with the theory itself, look at how we can leverage our knowledge of these theories in Single Entry and 3-Max, do the same for MME (Mass Multi-Entry) contests, discuss how to handle chalk, discuss how to leverage ownership projections to maximize our return, put it all together to develop a repeatable habit pattern, and finally discuss the process of self-evaluation (Monday morning quarterback) and how each slate can be analyzed to refine our process. But first, we have four more free lessons to go through in our effort to equip you to leverage game theory for bankroll boosting in GPPs!