Predictive analytics for daily fantasy basketball.

pip install -r requirements.txt

The python code is contained within the schneiderman module.

Any executable files (python or otherwise) are within bin/.

• scrape/ Various data scrapers.
• models/ Persistent storage for scraped and processed data.
• regresssion/ The linear modeling tools used on the gathered data to predict weekly scores.
• lineup/ Randomized algorithm used in generating lineups from predicted weekly scores.

• static Static data. Supports analysis, changes infrequently, fetched manually.
• data/ The user local data folder. Used for temporary storage of pipeline stage data. Ignored by git.
  • data/clean Output data from bin/clean.
  • data/scrape Output data from bin/scrape
  • data/games Output data from bin/load_games
  • data/train Output data from bin/train
  • data/predict Output data from bin/predict
  • data/lineup Output data from bin/lineups