We start by constructing simple systems that show consistent in and out-of-sample results. We require our models to make sense and not simply fit past data. We add refinements to our basic models then revalidate all our systems with real-time performance before we use them.
Our systems are a blend of fundamental, situational, and psychological factors. We look for teams having strong motivations to perform well or that conversely might be overconfident. Mean reversion is an important aspect of sports analysis.
We consider the motivations of the betting public as well, such as overconfidence, recency bias, and anchoring on past results. Betting lines reflect public psychology. Some of our edge comes from exploiting behavioral biases incorporated in the betting lines.
Money management can be just as important as good bet selection. We feel we have a strong edge in this area based on our years of experience in risk analysis and portfolio management.
A significant advantage we have over other sports speculators is our extensive use in holding bitcoin as reserves.We use trend following and mean reversion trading models to manage our bitcoin risk exposure,