An interactive R Shiny application for NBA Draft evaluation, rookie success prediction, player comparison, and front-office decision support.
👉 https://yfazp7-danny-thompson.shinyapps.io/basketball-analytics-hub/
👉 Live App: (Paste your Shiny URL here)
- Model rankings for the 2026 NBA Draft class
- Draft Value metric
- Success Score predictions
- Draft steals and reaches
- Historical NBA rookie success prediction
- Probability of NBA success
- Predictive modeling built in R
- Search any player in the draft class
- View:
- Success Score
- Model Rank
- Draft Value
- College statistics
- Physical profile
Compare two prospects side-by-side.
Includes:
- Model Preference
- Success Score
- Draft Value
- College production
- Head-to-head visual comparisons
Interactive rankings with filters for:
- Team
- Success Score
- Draft Value
Evaluate each NBA team's draft based on:
- Average Success Score
- Best draft pick
- Total Draft Value
- Team selections
Future module for evaluating NBA trade value using production, age, contracts, and team context.
- R
- Shiny
- dplyr
- ggplot2
- DT
- readxl
Basketball Analytics Hub/
│
├── app.R
├── global.R
├── server.R
├── ui.R
├── modules/
├── data/
├── www/
└── README.md
https://github.com/DannyTData/predicting-nba-career-success
https://github.com/DannyTData/2026-nba-draft-value-model
- Player photos
- Trade Value Model
- Salary analysis
- Draft simulator
- Free agency tools
- Team needs dashboard
- Interactive visualizations
Danny Thompson
Basketball Analytics | Predictive Modeling | Sports Data Science
Aspiring NBA/WNBA Basketball Operations & Analytics Professional




