2021-10-01, 13:30–14:00, Salta
Basketball is spatial. Any event that occurs during a basketball game—a made shot, a missed shot, a rebound—has a corresponding spatial or spatio-temporal information embedded in it and, one can argue, that location oftentimes plays an important role in its occurrence or success.
If you think of the basketball court as a map, a parcel of the earth, or simply a Cartesian coordinate plane then every location on the court can be specified by a coordinate pair. If we consider one type of basketball event—a shot or field goal—every occurrence of this event on the court will have its own corresponding coordinates. Aside from coordinates, these field goals can also have attributes or marks—the name of the player, the name of the team, the opponent, the time left on the clock, whether the shot was made or not, whether it was defended—that provide other information about the field goal. If we take this collection of field goals, what we actually have is a collection of points in space that is, similar to any spatial point dataset, susceptible to spatial analysis. This is why it makes sense to analyze basketball from a spatial perspective.
In countries with advanced player tracking systems, they’ve been able to perform studies and research that challenge conventional wisdom and create a deeper understanding of the spatial aspects of the game.
For the past few years, I’ve been trying to do the same in the Philippines even though we do not have advanced player tracking systems and have a severe lack of readily available basketball-related spatial data.
This presentation will talk about how spatial concepts and open source technologies can be used to map and spatially characterize the game of basketball by providing examples of spatial analysis and visualization of field goals in the University Athletics Association of the Philippines (UAAP) Men’s Basketball Tournament.
The presentation will talk about how spatial concepts and open source technologies can be utilized to study and spatially characterize the game of basketball, specifically the act of shooting and scoring, using a case study of the University Athletics Association of the Philippines (UAAP).
It will discuss better methods and metrics for analyzing, visualizing, and describing the geography of field goals in the UAAP, compared to conventional statistics such as field goal percentage and common visualization techniques such as shot charts and shooting zones, by considering the set of field goals as a point process and subjecting it to spatial point process analysis .
This includes using Non-negative Matrix Factorization (NMF) for determining the spatial basis vectors of the field goal dataset and computing for metrics for performance evaluation that compare a player’s expected points scored based on the distribution of his field goals to the actual number of points that he scored. Different ways to spatially visualize shooting and scoring in basketball will also be presented.
Pintor, Ben Hur
University of the Philippines, PhilippinesTrack –
Use cases & applicationsTopic –
FOSS4G implementations in strategic application domains: land management, crisis/disaster response, smart cities, population mapping, climate change, ocean and marine monitoring, etc.Level –
1 - Principiants. No required specific knowledge is needed.Language of the Presentation –
Ben is a free and open stuff advocate based in the Philippines. He supports the open data & mapping communities in his country as an individual and through BNHR, his consultancy, and SmartCT, a tech non-profit he co-founded.
Learn more about him at https://bnhr.xyz