High school football computer rankings from all 50 states
Computer rankings are updated after each game night, as fresh results are factored into the data which drives the rankings. An explanation for our formula can be found below.
HIGH SCHOOL ON SI HIGH SCHOOL FOOTBALL COMPUTER RANKINGS
High School on SI has launched its own computer-based high school football ranking system. Our computer rankings have been created for the enjoyment of fans and are not official state rankings.
How are the rankings calculated?
High School on SI has created its own linear algebra-based ranking algorithm inspired by the Colley Bias-Free Ranking Method. Colley’s Method was created by Wes Colley, Ph.D., an astrophysicist at the University of Alabama at Huntsville. He devised his algorithm in order to help address the subjectivity and controversy regarding BCS college football selections in the 1990s and early 2000s, using a method that used no subjective variables.
The method he developed was one of a small handful used by the NCAA from 2001-2014 to rank football teams for bowl games and the national championship. To this day it is one of the most accurate and well-established linear algebraic rating systems in sports. And Colley’s Method achieves a high level of mathematical precision without incorporating what many call the most important variable in sports rating systems: margin of victory.
Colley’s Method base equation is derived from Laplace’s Rule of Succession, which boils down to the formula:
A team’s rating = (1 + number of wins) / (2 + number of games played).
In order to take strength of schedule into account, Colley replaces number of wins in the numerator with (wins – losses)/2 + sum of opponents’ ratings.
That leaves the final equation: (1 + ((number of wins – number of losses)/2) + sum of opponents’ ratings) / (2 + number of games played.)
High School on SI's ratings algorithm is built around the above equation, but deviates from Colley in that it also incorporates margin of victory. Our system applies additional adjustments to teams’ ratings based on just how much a team wins or loses by, and also includes an increased significance of teams’ strengths of schedules.
These adjustments amount to a unique algorithm that maintains proportionality to Laplace’s Rule of Succession but aims to address the primary challenges of ranking high school football. Our system was designed to address the high school field consisting of a larger number of teams, more talent disparity between the best and worst teams, and substantially more variation in strength of schedule than in NCAA Division 1 football.
Lastly, since this version of our ranking engine will not have any impact on official state rankings, the main drawbacks of factoring in margin of victory are not applicable.