Advanced statistics (also known as analytics or APBRmetrics) in basketball refers to analyzing basketball statistics through objective evidence. APBRmetrics is a cousin to the study of baseball statistics, known as sabermetrics, and similarly takes its name from the acronym APBR, which stands for the Association for Professional Basketball Research. A second core tenet is that per-minute statistics are more useful for evaluating players than per-game statistics. From John Hollinger's Pro Basketball Forecast:
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| - Advanced statistics in basketball (en)
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| - Advanced statistics (also known as analytics or APBRmetrics) in basketball refers to analyzing basketball statistics through objective evidence. APBRmetrics is a cousin to the study of baseball statistics, known as sabermetrics, and similarly takes its name from the acronym APBR, which stands for the Association for Professional Basketball Research. A second core tenet is that per-minute statistics are more useful for evaluating players than per-game statistics. From John Hollinger's Pro Basketball Forecast: (en)
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| - Advanced statistics (also known as analytics or APBRmetrics) in basketball refers to analyzing basketball statistics through objective evidence. APBRmetrics is a cousin to the study of baseball statistics, known as sabermetrics, and similarly takes its name from the acronym APBR, which stands for the Association for Professional Basketball Research. A key tenet for many modern basketball analysts is that basketball is best evaluated at the level of possessions. During a single game, both teams have approximately the same number of possessions, because they alternate possession. (A team can have slightly more if it begins and ends a quarter or half with possession.) However, over the course of the season, teams play at very different paces, which can dramatically color their points scored and points allowed per game. Therefore, these analysts favor use of points scored per 100 possessions (offensive rating) and points allowed per 100 possessions (defensive rating). A second core tenet is that per-minute statistics are more useful for evaluating players than per-game statistics. From John Hollinger's Pro Basketball Forecast: It's a pretty simple concept, but one that has largely escaped most NBA front offices: The idea that what a player does on a per-minute basis is far more important than his per-game stats. The latter tend to be influenced more by playing time than by quality of play, yet remain the most common metric of player performance. A more complete explanation of possession-based analysis is available in "A Starting Point for Analyzing Basketball Statistics" in the Journal of Quantitative Analysis in Sports. (en)
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