Later this week I will attend the 10th annual MIT Sloan Sports Analytics Conference. It’s amazing how this conference has grown from a Boston-area gathering in MIT Sloan conference rooms into a slick and highly-polished event that attracts experts and enthusiasts in sports analytics and sports business. It’s also amazing that this will be my sixth […]
There are two sport analytics conferences later this year that deserve attention.The first is the 8th European Conference on Sport Economics, organized by the European Sport Economics Association (ESEA) and hosted at the University of Groningen from 31 August to 2 September. The conference will have presentations on papers discussing — you guessed it — […]
Soccermetrics’ Marcotti repository has finally reached an important milestone. The transition of the schema from SQL scripts to Pythonic data models is complete, and a next-generation set of extraction, transformation, and loading (ETL) tools has been ported successfully from other projects. It’s not a final version, but I feel comfortable with setting a version number at this […]
For the last couple of months, I’ve been updating and modernizing the Marcotti data schemas that Soccermetrics uses to build its match databases. It’s good work, but databases need data to be placed in them, and hopefully in a systematic and reliable way.Over the years, I have written a lot of scripts and modules to […]
The 2016 MIT Sloan Sports Analytics Conference is coming soon, albeit a couple of weeks later than usual. And once again the soccer analytics community will be stepping away from their computers to have a drink and attach human faces to virtual identities. The drinkup location is in the same spot as in previous years: Thursday 10 […]
Tim Swartz, Adriano Arce, and Mohan Parameswaran, “Assessing Value of the Draft Positions in Major League Soccer’s SuperDraft”, The Sport Journal, 16(9): 2013. [PDF]In this paper, the authors create performance metrics based on minutes played and salary level of drafted Major League Soccer players in order to estimate the relative value of the SuperDraft positions. […]
Continuing from my previous post on club impacts on effective time in J-League Division 1 matches in 2015, I look at the same for clubs competing in the 2015 J2 season. The previous post contains background information and the modeling methodology, so I will present just the graph here.Here’s some summary data on effective playing time […]
I started off 2015 with an analysis of effective time in the J-League and which teams appeared to have a strong influence on it. To start off 2016 I do the same type of analysis but from a Bayesian perspective. My objective for 2016 is to take my analytics into more of a Bayesian direction — […]
UPDATE (21 January 2016): I added some additional content throughout the post, but especially in the caveats, what to learn and where to learn it, and breaking into sports analytics. I also added Dean Oliver’s tweet, which reminded me that you need to know your sport to do sports analytics.UPDATE #2 (9 November 2016): Added a […]
In this post, I present another way to visualize Front-Office Efficiency in Major League Soccer’s Designated Player era, which also gives me a reason to try out D3 functionality on WordPress.I start with a basic scatter plot of league points versus standard win cost for all MLS teams who played during the 2007-2015 regular seasons. […]
