I’m a big cricket fan (to be honest, there are few sports that I’m not a fan of), and I’ve been fascinated by some of the visualizations that TV production teams use to communicate individual and team performance. One such visualization is the “wagon wheel” that is an overhead view of the paths of all […]
I’ve agreed to give a lightning talk at the December PyData Atlanta meetup next week. I will be talking about the use of the lifelines Python library to perform survival analysis, and I will be using my study of the MLS draft as an example. I have a hard five-minute limit, so don’t expect to […]
The MLS Front-Office Efficiency ratings always generate a lot of discussion for various reasons, from its methodology to its use of salary data from the MLS Players Union surveys. Much has been written about the accuracy of the salary data and the inability to fully account for outlays on the clubs’ (and MLS’) books. Steve […]
Lanzo un nuevo proyecto para coleccionar datos del fútbol — en este caso, todos los tiros de cabeza que ejecutan en la Primera División Argentina, de temporada 2016-17. Se encuentran los archivos en el repositorio ProjectData de GitHub.En la segunda mitad de 2016 Soccermetrics entró en un acuerdo con DataFactory para crear contenido analítico acerca del […]
A couple of weeks ago I placed a new data archive in Soccermetrics’ ProjectData repository on GitHub, but I haven’t found time to mention it until now. I’m looking to identify all headed shots in Argentina’s Primera División this season, and I’ll explain why.I’ve been working with data from DataFactory for Argentina’s Primera and the Copa Sudamericana […]
Jay Heumann, “An improvement to the baseball statistic ‘Pythagorean Wins’”, Journal of Sports Analytics, 2(1): 49-59, 2016. [PDF]Abstract: This paper introduces a new version to the commonly used “Pythagorean wins” statistic, which improves on the traditional method by means of mathematical adjustment. The new statistic is called the “pairwise” Pythagorean wins, and it is demonstrated, […]
The 2016 Major League Soccer regular season came to a close two weeks ago, so it’s time for a new edition of the Front-Office Efficiency table. As was the case last year, this table is displayed as an infographic on the Soccermetrics SlideShare page and as twenty individual panels on the Soccermetrics Twitter page.The efficiency metric […]
Presento abajo una tabla que contiene algunas medidas del rendimiento arbitral en los partidos de la Primera División de Argentina 2016-17. Algunos se fijan en la cantidades de tarjetas o penales cobrados; esta tabla muestra el descuento agregado, los intervalos entre interrupciones, y el tiempo efectivo de juego para dar una imagen del manejo del partido.Datos suministrados por […]
The following chart presents metrics that in their totality provide a picture of the referee’s management of matches worked in the 2016-17 Primera División Argentina.Data supplied by DataFactory.Here’s the key for the table columns, aside from the obvious. P1 and P2 refer to first and second periods, respectively. All time is in seconds.Added: Stoppage time added […]
Presento en esta entrada el tiempo efectivo de juego de los partidos del torneo de Primera División de la Argentina hasta la Fecha 8 (1 de noviembre de 2016). Los datos fueron suministrados por DataFactory.Debo aclarar que estas figuras son crudas y no ajustadas. Es que el DataFactory no anota todos los momentos que la pelota […]
