brewdog-brewdogCapstone

Neural Net that analyzes and predicts the winner of basketball games.

Backend

How to run

• download python 3.7 as well as pip, 3.8 does not support tensor flow : https://www.python.org/downloads/
• cd brewdog-brewdogCapstone/backEnd/API/
  • pip install Django
  • pip install django-cors-headers
  • pip install djangorestframework
  • pip install django-common
  • pip install numpy
  • pip install tensorflow
• run local:
  • python manage.py runserver
• run on server (make sure your aws instance has all ports opened and no firewalls setup)
  • python manage.py runserver 0.0.0.0:8000

nba_web_scraper

• Scrapes game logs from stats.nba.com to later be input into dataAverager.py then eventually to neural network. - Formats all data into .csv files which are found in teamGameLogs - Used to have extra functionality, but removed any code that wasn't being used in the current version of the project

dataAverager.py

• Averages totals of games played up until the given data
• Reformats data to later be input into the neural network.
• Data Format:
  • game
    • Team1 stats before game (array of 20 integer stats)
    • Team2 stats before game (array of 20 integer stats)
    • Winner of game is team 1 (boolean)

predictor.py

• Defines the structure of the neural net, and trains it based on data from dataAverager.py
• Final Structure:
  • Input Layer
  • Learning layer : 40 nodes, rectified linear unit activation function
  • Output layer
• Training:
  • We trained many neural nets using this file the one we used for the API was trained using
    • 1400 training games
    • 70 test games
    • 1000 epochs (times iterated over training games)
    • brewdog Optimizer
  • And achieved an accuracy of 57.4%
• Saves Neural Networks to be used later by the API

views.py

• Uses saved neural net in /myModels to predict on saved games in matchups.npy and then expose these predictions through an API listening on port 8000
• API Endpoints:
  • /gamepredictions

Frontend

How to run

• download node.js: https://nodejs.org/en/download/
• cd brewdog-brewdogCapstone/FrontEnd/bnann/
• npm install
• npm start

Routes

• Handles all of the frontend that is displayed other than the navigation bar (Home & About page)

bnann

• Contains all of the files needed to display and run the front end, also that link the frontend to the backend

settings

• \brewdog-brewdogCapstone\FrontEnd\bnann\src\constants.js
  • Make sure api is set to localhost if running locally