A better implementation in Python with added features and a working API is now available on : Nba-Match-Predictor. The new version is still a project-in-progress
Version: 2
Author: Khai H Lai
Last Updated: 9/3/2019
Changelog:
- Added hashCode() and equals() to class Team.
- Added webscraping functionality using JSoup library
Language: Java
This simple program uses Monte Carlo simulation to:
- predict the result of an NBA match.
- output each team's probability of winning the matchup.
Has basic UI that allows users to type in the names of the teams they wish to simulate the match-up with.
The simulator uses library Jsoup to scrape data from Basketball Reference NBA 2019 Ranking and Team Rankings. It then uses Monte-Carlo simulation (with added random statistical variations applied on the procedure described on Basketball Distribution) to give the probability of each team winning the match-up.
- Make this program into a webapp that can be easily used and accessed by the public.
- Make this program into a browser extension that automatically fetch from that day's NBA schedule and output predictions.
- Goal for completion: December 20, 2019