Returns to Inequality: Introduction and predictions

As a follow up to my data dump post on league-level and individual player inequality in sports, I want to go a level deeper in each league and see where inequality makes a difference on the field (or court, or ice). This series of posts will look at each league and run a simple regression of winning percentage against overall payroll and team Gini coefficient.

I expect there will be relatively low correlation between spending and winning in the harder-capped leagues (NHL and NFL) while the NBA and MLB should show some.

The real interesting point will be whether prominent current teams that are more unequal (stars and minimum-salary guys: the Miami Heat or New England Patriots) are successful as a rule or as an exception.

A few predictions before I get started:

NBA – My guess is the NBA will have the biggest returns to inequality as a proxy for teams having stars. With those stars they are not able to afford middling salaries for role players and drop quickly down to minimum salary or exception-level players.

NFL – I would think the returns to inequality are high here, but not exactly as a proxy for having stars. The NFL’s cap structure essentially forces teams to play rookies and younger, pre-contract extension, players heavily and supplement them with selected veterans. The catch is that nearly all teams have a big young player population so the difference between one that works out and one that doesn’t might not be visible in the salary distribution.

MLB – This is anyone’s guess. The returns to inequality – after controlling for the wide distribution in overall team salary – might be strong or they might not. I don’t have a good feel for it so this will be more of a fact finding mission.

NHL – I am guessing that returns to inequality are strong here too, with relatively high leverage of the individual players resembling the NBA more than the NFL or MLB.