The author is analyzing basketball performance using data from the past four seasons, considering factors such as team relationships, crowd bias, and player motivation. They use a graph model to represent these relationships, leveraging tools like Neo4j to store and query the data. The model takes into account historical data, team performance, and Pythagorean Expectation to predict win probabilities between teams. By applying this model to hypothetical matchups, the author demonstrates its potential for making accurate predictions.