Why can’t we just use the points scored over total points as a basis for predicting the expected outcomes? The answer to that simply is that the data would be wrong. Going by the diagram, if it is a tall and thin triangle, the team scored a lot more points compared to what they have given up, and if it is a short and long triangle, the team has given up many more points compared to what they actually have scored. Think of points scored as ( a), and points allowed as ( b) where ( c) is a function of the (a and b) linear equation and we just want to know what the relationship is between a^ 2 / c^ 2 (c^2 is a^2 + b^2) to get a percentage of wins multiplied by the total games. It basically figures out the distance between two points of a right triangle (c), or for what we are interested in, the expected value between the relationship of sides.
The Pythagorean theorem is a^ 2 + b^ 2 = c^ 2. Since then, the Pythagorean wins theorem has continued to be statistically significant. The 2011 edition of Football Outsiders Almanac states, “From 1988 through 2004, 11 of 16 Super Bowls were won by the team that led the NFL in Pythagorean wins, while only seven were won by the team with the most actual victories. This way we can have a better idea on what to expect for next season. This is why we can use a Pythagorean win total compilation to compare what was expected to happen based on points scored for all of the NFL teams, to what actually did happen in how these teams finished out their year. Using a function that takes a look at the total points scored as a data point with the total points allowed is, at many times, a better indicator of a team’s future success compared to their actual record. Due to these discrepancies, we need to formulate the data to find out what some of these teams were expected to do based on points scored compared to their actual win/loss results. Sometimes teams score many of their points during blowouts, and as luck will have it, those same teams might lose their close games. In that same year, the Chargers scored 337 points while only giving up 345 (almost 50/50) and only won only 5 games. In 2019 the Houston Texas scored 378 total points, yet gave up 399 to win 10 games. Is it possible for an NFL team to score more points than they give up and have a losing record? How about score less points than they allow and have a winning record? The answer to that is that it is very possible, and it happens every year. The method that we will be discussing today is the 2021 Pythagorean win total calculation as a method to help predict the 2022 football season results. If we find some scientific methods that will correlate well using a team’s past performances to their success in the future, it will help us become not only more knowledgeable, but it could also help us become more profitable. Wins and losses do not tell the whole story and they are also rarely a good indicator by itself for a team’s future success. Many of us NFL football analysts and sports bettors want to have good methods for prediction for next year’s football season in order to be more accurate. We can just go back to January 9th of this year to find an easy example of that for when the Jaguars beat the Colts. Let’s face it, there is a good amount of luck that happens within the football season the best teams do not always win against the worst teams. There is also a certain amount of randomness of “when” the points are scored that pertains to a team’s final win record. The shape of the football itself creates it’s own sort of randomness on circumstances such as situation like field position during punts and how the ball spins during field goals. Posted April 29, 2022, reposted July 23rd 2022Īs discussed from last year’s article, football is a game of inches, and by being off just one, could be the difference between a win and a loss in a league with limited games.
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