538-nba-prediction-methodology
đ° Summary (use your own words)
Explaining the methodology behind how 538 simulates their game prediction models.
âď¸ Notes
- First iteration relied on Elo ratings
- This worked well to keep track of the general strengths of teams over the years
- But it does not capture any player movements, injuries and resting quickly
- In 2015, 538 introduced a system called CARM-elo which extends the Elo framework to use their CARMELO player projections
- This improves the offseason affects to a teamâs projected strengths
- It still had trouble with super teams that went easy during the regular season and turns it on during the playoffs - it couldnât properly measure these teams
- In 2018, fully moved away from Elo and uses player rating system
- This system is based on RAPTOR metric
- Using a blend of basic box score stats, player tracking metrics, plus/minus stats to estimate a playerâs effect (per 100 possessions) on his teamâs offensive and defensive efficiency
- This metric forms a prior for each player and it gets updated as the season goes on
- Then teamâs strengths can be calculated based on the line-ups they have available during game day
- Make game predictions by combining the teamâs talent level weighted by expected minutes played, and multiplied by a regular season or playoff scalar adjustment and converted into expected points scored
- The expected winning percentage is calculated with Pythagorean expectation for regular season this has the form
- $$winning % = \frac{Projected Pts Scored^{14.3}}{Projected Pts Scored^{14.3}+Projected Pts Allowed^{14.3}}$$
- The season is then simulated with Monte Carlo and then the predictions are made