Back in the late 1980s, as a college student, I would go to the NHL offices in downtown Montreal, and pick up their official end-of-season statistics package. This was something that was reserved for the media, but somehow I had the idea to ask, and they were kind enough to oblige. Since I was learning dBase, I then had to manually enter every piece of data in that package, probably some 20,000 discrete data values. Combining sports, numbers, and computers was a labour of love for me. Add in that in the 1980s, Pete Palmer and Bill James inspired the sabermetric revolution: my career path was set, as was that of thousands more.
SportsDataverse
Welcome to the SportsDataverse. We are an open-source sports data organization trying to make data and utilities more accessible for everyday users.
Data Everyday: Data Literacy Practices in a Division I College Sports Context
Inside Baseball: The Automated Ball-Strike System as an Object Lesson in Technological Rule Enforcement
Clearly-defined rules are often assumed to be straightforward to automate and evaluate. We challenge this assumption through an in-depth study of Major League Baseball's (MLB) seven-year experimentation with the Automated Ball-Strike System (ABS). ABS is envisioned to call balls and strikes accurately: a seemingly straightforward use of technology to objectively determine the distance between a pitch and the strike zone. Although the strike zone is an area clearly defined in the rulebook, it took MLB seven years to figure out how to automate calling balls and strikes with ABS, showing how even seemingly straightforward rules require a complex translation process to operationalize via technological systems. In this paper, we trace the design decisions that led to the current implementation of ABS. Our case study reveals that "distance" exists even between a clear rule and its technological implementation. Using analytic frameworks from Science and Technology Studies (STS), we show that such distance exists because (1) historically, the "ground truth" of the strike zone is contested: the rule in practice has always reflected a hybrid between the rulebook definition and umpires' enforcement decisions; and (2) the use of ABS is embedded in an existing eco-system, where the implementation of a technological enforcement system needs to balance multiple stakeholder values. This perspective challenges conventional evaluation paradigms that center on the distance between a formalized rule and its technological implementation, and instead calls for evaluating how such systems are experienced in practice. Addressing this question requires in-depth social science approaches, contributing to ongoing conversations in FAccT about the implementation and evaluation of sociotechnical systems.
The World Series Was Electric — So Was Bluesky - Bluesky
“How can you not be romantic about baseball?” — Moneyball 2011
Introducing DAVIES: A framework for Identifying Talent Across the Globe — American Soccer Analysis
In the world of sports, the search for an all-encompassing player evaluation metric is never-ending. Baseball was the first to develop its metric with Wins Above Replacement. Basketball followed suit with Player Efficiency Rating, and Hockey WAR has come into the fold within the past year. The US So
BlATBall - Interdimensional Baseball on AT Protocol
Smashrun - Stats for runners
Smashrun is a data visualization platform that helps runners track their training consistency, volume, and effort distribution. Sign up is quick and easy and it's free!
Living in Data: A Citizen's Guide to a Better Information Future (Paperback)
Jer Thorp’s analysis of the word “data” in 10,325 New York Times stories written between 1984 and 2018 shows a distinct trend: among the words most closely associated with “data,” we find not only its classic companions “information” and “digital,” but also a variety of new neighbors—from “scandal” and “misinformation” to “ethics,” “friends,” and “play.”To live in data in the twenty-first century
datasetpapers — a public research experiment
An experimental approach to versioned, forkable, machine-readable analyses. A prototype, not a product or service.
datasetpapers — a public research experiment
An experimental approach to versioned, forkable, machine-readable analyses. A prototype, not a product or service.
Danielle Robinson, PhD
Advancing the power of data to improve the social and economic lives of all people.
Dynamic Data Science
<p>Use our Common Online Data Analysis Platform (CODAP) to explore dynamic data science activities and gain fluency in data moves to examine large datasets.</p>
RUNALYZE - Data analysis for athletes
RUNALYZE is a manufacturer-independent analysis platform for endurance athletes, that helps athletes to train smarter.
#atdev friends, if you had an analytics database of all atproto records, what are some interesting things you'd like to know? - how many total posts? - how many chars have been typed across all posts? - how many live/dead PDSes out there? - how many "Jerry, no!"s? - something with the social graph?
