Well, has he? Silver purports to have constructed a brand-spanking new model christened CARMELO that predicts (with a confidence interval of 80%) an NBA player's WAR in the coming years. It's worth your time to follow that link over to FiveThirtyEight, and spend the next ten or so minutes perusing Silver's breakdown of his methodologies. The watered down, fast-pace (consumer friendly!) version:
- Start with a big pot. Heat to 350 degrees fahrenheit. Throw in the vitals: height, weight, draft position. Add in the seasoning: TS%, USG%, FTr, AST%, TO%, TRB%, BLK%, STL%, and a viscous mixture of BPM and RPM. Bring to a simmer.
- Pour that pudding of statistical and biographical information into a pan and bake for three hours. Once cooked, compare your resulting player information pie with historical players' information pies. The similarities and differences between these two are indexed as similarity scores. A positive similarity score is more similar than not (100 being perfectly matched), a 0 indicates an equilibrium of similarities and differences, and a negative score signifies more differences than similarities.
- Abandoning our pie analogy, and forging forward with actual pertinent information, the CARMELO algorithm collects the 10 most similar seasons for this hypothetical guinea pig player. From there, the algorithm dissects each of the 10 players' 7 seasons subsequent to the season tabulated in the similarity scores, and averages out all 10 players' WARs each year.
Each average is weighted, however, towards more similar players. For instance, a player with a similarity score of 60 will have double the effect on the WAR average than a player with a similarity score of 30.
- Finally, CARMELO spits out a pretty scatter plot, complete with a range of 80% of the probable WAR totals each of the next 7 years for the given player.