Speak With Data

There has been significant discussion, given the uncertain status of Andrew Luck's shoulder injury, of the Colts possibly signing Colin Kaepernick, in addition to previous possible signings of the former 49er in Baltimore (after Joe Flacco suffered a back injury of unknown severity, leading to open discussion with the community and no signing of a quarterback who could serve long-term in place of Flacco) and Miami (after Ryan Tannehill re-injured his knee; the Dolphins have since signed Jay Cutler). Kaepernick's status as a free agent has been cemented by controversy regarding his social activism, seeing quarterbacks with much less-impressive resumes signed by teams (*cough* Mike Glennon *cough*) while Kaepernick remains on the sideline (or, rather on a sideline of a field that does not contain NFL players). There are significant issues raised by teams hesitations (as displayed by the Ravens) to sign a player based on their activism, and I do not believe a blog where the phrase...

In the later half of this Premier League season, there has been discussion of a shifting of power between the two North London clubs, historically dominate Arsenal and the long-mediocre Tottenham Hotspur (1). This discussion peaked after a poor performance by Arsenal in their April 30th meeting at White Hart Lane, with Tottenham winning 2-0. Tottenham as been riding high this season; currently in second place in the table, they have punched their ticket to the Champions League, and if first place Chelsea stumbles down the stretch, could win the Premier League. Arsenal, after a hot start, have struggled this season; dominated by their rival clubs at the top of the Premier League, embarrassed by Bayern Munich in the Champions League, and on the outside of the top four. Having sunken to as low as sixth, the Gunners are now 4 points behind Liverpool's fourth place and Champions League. Their only glimmer of success has been reaching the FA Cup Final; while an accomplishment, they had b...

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.

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.