To date, KPI Sports has been built upon not only a ranking system designed to be more precise than existing systems, but has also developed several other easy-to-use, logical statistical metrics intended to not only tell a more exact story, but also be simple enough for someone without an advanced degree in mathematics to understand.
KPI Rankings: The KPI formula is designed to assign a value to every game played during a season for each team. The formula assumes nothing and there are no preconceived notions or numbers assigned in the preseason. Each team’s value for each of their games is averaged over the course of a season for each team – meaning that every game played counts the same (unlike the weighted RPI). Values for the games adjust as more data is compiled.
Everything is based on the number 1. The worst loss possible is worth approximately -1.0, while the best win possible is worth approximately +1.0 (the best winning percentage a team can have is 1.000). The best loss may be worth -.01 while the worst win may be worth +.01. A hypothetical tie is worth 0.
The formula is applicable across many sports, specifically those where teams win and lose and there are scores (so basically, most everything).
The formula incorporates Opponent’s Winning Percentage, Opponent’s Strength of Schedule, the Game Result, Scoring Margin, Pace of Game, Location of Game (Home/Away/Neutral) and the Opponent’s KPI Ranking. The value for each game is divided by games played for the overall KPI Ranking.
The rankings can be made to include only a certain subset of games as well. Home KPI, KPI vs Top 100, November KPI, and any combination one can dream up are possible.
KPI Strength of Schedule: KPI Strength of Schedule factors not only the KPI of the opponent, but also the adjusted location of the matchup.
DIFFs: DIFFs are statistical differentials between how one team performs compared to what their opponents typically allow. Think of it as factoring in strength of schedule to numbers like rebound margin, scoring differential or how many times a team gets to the free throw line in basketball, or touchdown rates in football. DIFFs can be measured for any team stat kept for both a team and an opponent. For example, Duke led the country in the Offensive Points Per Possession DIFF last year — the difference between their offensive points per possession and their combined opponents’ defensive points per possession. Arizona led the country in the Defensive Points Per Possession DIFF.
EXP’s (pronounced EEE-EX-PEES): EXPs are the expected numbers based on a comparison of how one team and their opponent have performed to date. This algorithm can be used to anticipate the number of points, rebounds, touchdowns, base hits, goals, etc. that could occur in said game. The data becomes more accurate as more games are played and improve the sample size.
G-Score: The G-Score (short for Game Score) assigns a value to a matchup between two teams in order to rank the game based on the quality and competitive balance of the teams playing in it. The KPI of each team along with differentials between the two teams are factored.
Many other numbers and bits of data appear at KPI Sports, most with more easily understood applications. As data (and additional sports) continues to appear, more explanations may become necessary.