https://github.com/josedv82/epv_nba_dashboard
A conceptual dashboard to visualize Expected Possession Value (EPV) in the NBA.
https://github.com/josedv82/epv_nba_dashboard
nba nba-analytics nba-stats nba-visualization rstats shiny sparklines stock
Last synced: 6 months ago
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A conceptual dashboard to visualize Expected Possession Value (EPV) in the NBA.
- Host: GitHub
- URL: https://github.com/josedv82/epv_nba_dashboard
- Owner: josedv82
- License: mit
- Created: 2021-01-12T14:29:11.000Z (almost 5 years ago)
- Default Branch: main
- Last Pushed: 2021-05-18T21:58:17.000Z (over 4 years ago)
- Last Synced: 2025-03-25T17:17:44.504Z (7 months ago)
- Topics: nba, nba-analytics, nba-stats, nba-visualization, rstats, shiny, sparklines, stock
- Language: R
- Homepage: https://josedv.shinyapps.io/EPV_NBA_Dashboard/
- Size: 9.31 MB
- Stars: 12
- Watchers: 2
- Forks: 0
- Open Issues: 1
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# EPV Dashboard
A minimal app to visualize Expected Possession Value (EPV) in the NBA.***
Exploring an idea to visualize and interact with EPV in Basketball resembling a stock trading app. The dashboard provides information at a play by play level for a full game as well as the player total EPV added for that game. A dynamic play diagram alongside the EPV can be displayed for all available plays.
* Live App: [Link](https://josedv.shinyapps.io/EPV_NBA_Dashboard/)
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#### References
Cervone, D., D’Amour, A., Bornn, L., & Goldsberry, K. (2016). **A multiresolution stochastic process model for predicting basketball possession outcomes.** Journal of the American Statistical Association, 111(514), 585-599. [Link](https://arxiv.org/abs/1408.0777)
Cervone, D., D’Amour, A., Bornn, L., & Goldsberry, K. (2014). **POINTWISE: Predicting Points and Valuing Decisions in Real Time with NBA Optical Tracking Data.** Sloan Sport Analytics Conference. [Link](http://www.lukebornn.com/papers/cervone_ssac_2014.pdf)
#### Data
The EPV data was sourced from https://github.com/dcervone/EPVDemo
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#### Mobile Devices
This app is not intended to work on mobile devices and therefore some functionalities may not work on smaller screens.