The 2021-22 men’s basketball season marks the fourth season of the NCAA Evaluation Tool (NET) rankings, which replaced the RPI prior to the 2018-19 season as the primary sorting tool for evaluating teams. In May 2020, the NCAA announced there will be changes made to the NCAA Evaluation Tool to increase accuracy and simplify it by reducing a five-component metric to just two.
The remaining factors include the Team Value Index (TVI), which is a result-based feature that rewards teams for beating quality opponents, particularly away from home, as well as an adjusted net efficiency rating. The adjusted efficiency is a team’s net efficiency, adjusted for strength of opponent and location (home/away/neutral) across all games played. For example, a given efficiency value (net points per 100 possessions) against stronger opposition rates higher than the same efficiency against lesser opponents and having a certain efficiency on the road rates higher than the same efficiency at home.
We’re here to help you understand what’s valued in the NET rankings and how they’re used.
What did the RPI calculate? How is the NET different?
The Ratings Power Index (RPI) was made up of three components:
- A team’s winning percentage
- Average opponent’s winning percentage
- Average opponent’s opponent’s winning percentage
The NET includes more components than just winning percentage. It takes into account game results, strength of schedule, game location, scoring margin, net offensive and defensive efficiency, and the quality of wins and losses.
NOTHING BUT NET: Get to know the NET rankings — and what they mean for the NCAA tournament
It’s both a results-driven and predictive metric.
What are the NET Rankings?
Here’s EVERYTHING you need to know. Be on the lookout for the first release pic.twitter.com/kdZwDEjFPS
— NCAA March Madness (@marchmadness) November 26, 2018
How was the NET rankings system created?
The NET rankings system was improved in the summer of 2018 after consultation with the Division I Men’s Basketball Committee, the National Association of Basketball Coaches, top basketball analytics experts and Google Cloud Professional Services.
Late-season games from the 2017-18 season, including from the NCAA tournament, were originally used as test sets to develop a ranking model that used machine learning techniques. The model was used to predict the outcome of games in test sets and it was optimized until it was as accurate as possible.
That…
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