Predictive analytics for daily fantasy basketball.
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README.md

schneiderman

Predictive analytics for daily fantasy basketball.

Installation

pip install -r requirements.txt

Project Structure

Executables

Code

The python code is contained within the schneiderman module.

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

schneiderman/:

  • 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.

Data

  • 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