The Psychology and the Pricing: A New Inquiry into Sports Betting Markets - Part 1
The prevailing wisdom often treats modern sports betting markets as a solved problem - a bastion of efficiency where prices (odds) are so sharp that finding a persistent edge is nearly impossible. This new research vertical is founded on a simple premise: this wisdom is incomplete. Efficiency is a myth when markets are comprised of human actors and built on simplified models. This project will be a formal inquiry into two primary "attack surfaces" where I believe this efficiency breaks down.
Pillar 1: The Psychology (The Irrational Public)
The first pillar of this research is grounded in behavioral economics. The betting public, which collectively shapes the market, is not the perfectly rational actor of classical economic theory. It is a crowd driven by powerful and predictable cognitive biases:
Narrative-Driven Betting: Overvaluing teams with compelling recent stories or star players.
Recency Bias: Overweighting the most recent game's performance while ignoring larger sample sizes.
Favorite-Longshot Bias: Systematically over-betting popular favorites and under-betting longshots.
These biases create sentiment-driven mispricings. The goal of this research stream is to systematically model these predictable irrationalities to identify value where the market price has been distorted by public emotion.
Pillar 2: The Pricing (The Assumption of Normality)
The second pillar is a direct, quantitative challenge to the models used to price odds. For reasons of tractability, many pricing models are built on a foundational assumption of normality - that the distribution of potential outcomes, like the point spread in a football game, follows a standard bell curve.
But what if the real world isn't so "normal"? Sporting events are frequently subject to "fat-tailed" distributions, where extreme outcomes occur more often than a normal distribution would predict. A model that correctly accounts for the true, often non-normal, distribution of outcomes can identify subtle but significant mispricings that standard models will always miss.
The Path Forward
These two pillars are deeply intertwined. The irrationality of the public creates the market distortions, and a more robust quantitative model is the tool we use to detect and exploit them. This project is another application of the MathematicalEV ethos: go back to first principles, question every assumption, and combine psychological and mathematical analysis to find the exploitable edge. Future posts in "The Lab" will document this investigation.