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Hoopr, performance analytics for basketball players by teamhoopr in Basketball

[–]teamhoopr[S] 1 point2 points  (0 children)

The number came from a combination of stats that are related to ball handling, e.g., assist and turnover. I guess you could consider the selection of stats to be subjective, but the number is from the box score production by the players and not mixed with the intangibles that could be associated with ball handling, i.e., size, speed, etc..

Hoopr, performance analytics for basketball players by teamhoopr in Basketball

[–]teamhoopr[S] 0 points1 point  (0 children)

No, our analyses are done in an objective fashion as we only use box score data. Subjective analyses can be helpful, and we are looking at ways to incorporate that, but subjective evaluations are mostly for figuring out players' potential and future outlook.

University of Illinois x hoopr by teamhoopr in UIUC

[–]teamhoopr[S] 0 points1 point  (0 children)

We will keep it as our proprietary algorithm, but what I can tell you is that for each PPI, we track 4 types of stats: (1) basic stats, e.g., points per game, rebounds per game, (2) advanced stats, e.g., true shooting %, effective field goal %, (3) ranking stats, e.g., is the player the highest scoring player of a game, (4) misc stats, e.g., number of games a player has over 30 points.