Below is the Pythagorean table for the 2010-11 French Ligue 1 at just past the halfway mark of the season (matches played up to 15 January). The league Pythagorean exponent is 1.70.When I was taking a look at the goal distributions for each of the teams, I was half-expecting Rennes to be the big overachiever […]
Below is the Pythagorean table for the 2010-11 German 1. Bundesliga, for matches played up to 15 January 2011. The league Pythagorean exponent is 1.70. Dortmund are flying high at the top of the league, but the team of the first half of the season — and perhaps the biggest surprise in the major European […]
And now it's time to talk about the error-ridden Wikipedia page for the Championship. I use the results matrix to develop league tables from which I develop a Pythagorean table. I match up the league table against the table on the Wikipedia site to verify that all of the data line up correctly (sort of […]
Fulfilling a reader request…Below is the Pythagorean table for the 2010-11 English Football League Championship, as of matches played last Saturday (15 January 2011). As always, I used a league Pythagorean exponent of 1.70. The projections suggest that QPR should be opening up a substantial lead on their rivals, but they haven't. The rest of […]
Below is the Pythagorean table for the 2010-11 Spanish Primera División after 19 matches — exactly at the halfway point. As always, I use a league Pythagorean exponent of 1.70 in my calculations. Barcelona and Real Madrid have made the league an emphatic two-horse race, and that is reflected in the Pythagorean expectations. Espanyol was […]
Two years ago I started Soccermetrics in order to write about statistical problems in soccer in a more technical and uninhibited way. My initial post was one that I had written on my HexagonalBlog website as a way to answer some questions in my mind about the viability of an analytical approach to soccer. Now […]
I wasn't aware of this until Sarah Rudd alerted me to it on Twitter, but this year's MIT Sloan Sports Analytics Conference will have a Soccer Analytics session. (Hey, it's not like I'm checking the website everyday!) Last year's conference had an Emerging Analytics panel discussion which features representatives from soccer and American football, but […]
A quick look at my post archive has reminded me that this weekend marked the two-year anniversary of Soccermetrics. I wasn't able to write a post yesterday because I wasn't near a computer (and there was too much going on yesterday anyway), but I don't think anyone will kick up a fuss about me being […]
J. Apesteguia and I. Palacios-Huerta, “Psychological Pressure in Competitive Environments: Evidence from a Randomized Natural Experiment”, American Economic Review 100 (December 2010): 2548-2564.This economics paper focuses on the psychological issues involved in high-stakes competitive environments, using the penalty kick shootout as an illustration. The major finding of the paper is that there is a structural […]
Nathaniel Boyden and James Carey, "From One-and-Done to Seasoned Veterans: A Demographic Analysis of Individual Career Length in Major League Soccer", Journal of Quantitative Analysis in Sports, 6(4): Article 5, 2010.In this publication, the authors analyze data on over 1,000 Major League Soccer players in order to study the demographics of the league. The findings […]
