Recruitment Under Uncertainty
Collegiate recruitment is a decision problem under profound uncertainty. Will a prospect commit? How will they develop physically? What is the probability of injury? How will they interact with existing roster chemistry? Traditional recruitment relies on scout intuition — a valuable but inherently limited signal. Monte Carlo simulation supplements intuition with systematic probability modelling, generating thousands of potential scenarios to quantify the expected value and variance of each recruitment decision.
The Simulation Architecture
Our simulation engine models each prospect as a bundle of probabilistic attributes: athletic performance trajectory, academic eligibility risk, injury probability, position versatility, and commitment likelihood. For each recruitment class, the engine runs 10,000 simulated seasons, varying these attributes according to their probability distributions and measuring the resulting team performance across multiple metrics. The output is not a single prediction but a distribution of outcomes — enabling coaches to understand not just what might happen but how likely each scenario is.
Portfolio Theory for Scholarships
Scholarship allocation resembles portfolio construction in financial theory. Each scholarship investment carries expected return (contribution to team performance) and risk (variance in outcomes). Just as a diversified investment portfolio reduces risk through correlation management, a diversified recruitment class manages athletic risk by ensuring that the failure of any single prospect does not catastrophically impact team performance. Our models explicitly calculate the correlation structure of recruitment investments.
Validation and Accuracy
Over three seasons of deployment, the simulation engine's predicted team performance distributions have enclosed the actual season outcomes within the 80% confidence interval in 84% of cases — suggesting the model accurately captures the uncertainty structure of collegiate athletics. Areas of ongoing improvement include psychological factors, coaching interaction effects, and transfer portal dynamics.