Speak With Data

Definitions: Pythagorean Expectation, Preseason = The previous year's Real Pythagorean Expectation, with a factor of regression to the mean based on the year-to-year correlation of  Real Pythagorean Expectation. Pythagorean Expectation, Real =  Pythagorean expectation of points , based upon goals scored and goals allowed so far this season. An exponent of 1.27, derived from analysis of previous NASL seasons, is used Pythagorean Expectation, Bayesian = The main power ranking. Using Bayes' Theorem, updates its value accounting for new information. Begins with the preseason ranking, then updates week to week after that.  Expected Final Points = Using the Bayesian Pythagorean Expectation, the number of points a team has already, and the possible points remaining, is found Why am I doing a power ranking for a Division II soccer league? Because it is the league Indy has a team in.

Last Monday, it was announced the United States, Canada, and Mexico would jointly bid for the 80 match, 48 team expanded 2026 World Cup. If the (heavily favored) bid wins over potential other bids from nations in South America, Oceania, or Africa, it would be the first three country joint bid, and first joint bid since 2002 in South Korea and Japan. (1) Unlike the 2002 World Cup, in which games were split evenly between the two hosts (2), the proposed 2026 bid would have 60 games in the US, and 10 each in Mexico and Canada, with no games beyond the quarter finals. Mexican fans were not pleased with its significantly less  futbol -obsessed neighbor getting a lion's share of the games in the sport's biggest event (3). While I understand the frustration of Mexican fans in the joint bid being a mainly American bid, it understates an interesting fact about the bid: the US didn't need a joint bid to host. Looking at the World Cups since the last time the US hosted in 1994 ,

Definitions: Pythagorean Expectation, Preseason = The previous year's Real Pythagorean Expectation, with a factor of regression to the mean based on the year-to-year correlation of  Real Pythagorean Expectation. Pythagorean Expectation, Real =  Pythagorean expectation of points , based upon goals scored and goals allowed so far this season. An exponent of 1.27, derived from analysis of previous NASL seasons, is used Pythagorean Expectation, Bayesian = The main power ranking. Using Bayes' Theorem, updates its value accounting for new information. Begins with the preseason ranking, then updates week to week after that.  Expected Final Points = Using the Bayesian Pythagorean Expectation, the number of points a team has already, and the possible points remaining, is found Why am I doing a power ranking for Division II soccer league? Because it is the league Indy has a team in.

Definitions: Pythagorean Expectation, Preseason = The previous year's Real Pythagorean Expectation, with a factor of regression to the mean based on the year-to-year correlation of  Real Pythagorean Expectation. Pythagorean Expectation, Real =  Pythagorean expectation of points , based upon goals scored and goals allowed so far this season. An exponent of 1.27, derived from analysis of previous NASL seasons, is used Pythagorean Expectation, Bayesian = The main power ranking. Using Bayes' Theorem, updates its value accounting for new information. Begins with the preseason ranking, then updates week to week after that.  Expected Final Points = Using the Bayesian Pythagorean Expectation, the number of points a team has already, and the possible points remaining, is found Why am I doing a power ranking for Division II soccer league? Because it is the league Indy has a team in.

Definitions: Pythagorean Expectation, Preseason = The previous year's Real Pythagorean Expectation, with a factor of regression to the mean based on the year-to-year correlation of  Real Pythagorean Expectation. Pythagorean Expectation, Real = Pythagorean expectation of points , based upon goals scored and goals allowed so far this season. An exponent of 1.27, derived from analysis of previous NASL seasons, is used Pythagorean Expectation, Bayesian = The main power ranking. Using Bayes' Theorem, updates its value accounting for new information. Begins with the preseason ranking, then updates week to week after that.  Expected Final Points = Using the Bayesian Pythagorean Expectation, the number of points a team has already, and the possible points remaining, is found Why am I doing a power ranking for Division II soccer league? Because it is the league Indy has a team in.