In the 2018-2019 NBA Season, Two players of the Golden State Warriors, Draymond Green and Kevin Durant got into a heated argument at the end of Nov 13 2018. Draymond basically said the team did not need Kevin Durant (an Mvp and Nba Champion) to win a championship during the season. Unfortunately, Kevin Durant got injured during the final of the NBA championship and the Golden State Warriors lost the Championship. This lead me to ask the questions : "What is the effect of an expensive NBA player's injuries on a Team's record ?". This question can be used to understand the value of paying a high salary for a particular player and if it is justified. Also we can predict if a team will win or lose ratio if a player is injured.
- Scrape Sport Injuries data from 2010 - 2019 from Pro Sports Transactions
- Scrape Player informations data and Teams record data from Basketball Reference
- Calculate team record ratio when the valuable player is injured
- Build linear regression using current scraped data
- MVP: Number of Sport Injuries per season from 2010-2019 on high earning players.
- Goal: Get a score showing relationship between Sport player and Team's record.
- Date of Absence/ Injury
- Player
- Team
- Player's Total Earnings
- Player's Duration in the NBA in Years
- Average Earnings of Players
- Maximum earning
- Number of Team Wins during player's Injury per season
- Number of Team Loss during player's Injury per season
- Difference Between Win and Loss
- Player's name
- Player's team
- Player's current season earnings
- Number of Team Wins during player's Injury per season
- Number of Team Loss during player's Injury per season
- Difference Between Win and Loss
- Scraping the data may take longer than expected.
- In terms of using Regression I need to make sure that the way I represent the team's record lends itself to the model.