Much of the foundation of our graph theory-based database algorithms was created with applications focused on U.S. professional sports, particularly Major League Baseball.
We have found many interesting analytical results based on measuring the connections made between MLB players when they have taken the field together as teammates. One of our more interesting results is the correlation between MLB player connections and on-field player performance. Our database algorithms allowed us to determine that the player measurement of "more MLB teammate connections to teammates" is positively correlated to the player metric "offensive on-field performance of a player" but NOT positively correlated to "DEFENSIVE on-field performance of a player". Send us an email and we'll tell you why we think this is so.
We also used our database algorithms to determine which MLB players most improved the performance (we used WAR values) of their teammates over a 5-year timespan. This should be of great interest to players, teams, and player agents, as it shows which players MULTIPLY their own value by increasing many other players' performance.