Where Do Mountain West Teams Fall Within The NET Ratings?

Where Do Mountain West Teams Fall Within The NET Ratings?

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Where Do Mountain West Teams Fall Within The NET Ratings?


Where Do Mountain West Teams Fall Within The NET Ratings?

What exactly are the NET ratings?

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A key tool for NCAA Tournament selection

In 2018 the NCAA Evaluation Tool (NET) was created by the Division I Men’s Basketball Committee, the National Association of Basketball Coaches, basketball analytics experts, and Google Cloud Professional Services to create a ranking system to provide more accurate seeding for the NCAA Tournament. The NET was essentially created to replace the Ratings Power Index (RPI). The NET Rankings aim to factor in factors that the RPI did not.

RPI was made up of the following components: winning percentage, average opponent’s winning percentage, and average winning percentage of the opponent’s opponents. The NET rankings consider game results, scoring margin, game locations, quality of wins and losses, and net efficiency. The components in the NET rankings are combined to form two “factors” that determine a team’s NET Ranking. The two factors of NET are Team Value Index and Adjusted Net Efficiency.

Team Value Index

The first factor in the NET is Team Value Index (TVI). TVI is based on game results, and takes into consideration the opponent, location, and winner of the game. TVI divides a team’s games into Quadrants to determine the quality of wins or losses. Quadrant 1 consists of games at home against teams ranked 1-30, games on a neutral court against teams ranked 1-50, and games on the road against teams ranked 1-75. The other quadrants follow a similar pattern:

  • Quadrant 1: Home 1-30, Neutral 1-50, Away 1-75
  • Quadrant 2: Home 31-75, Neutral 51-100, Away 76-135
  • Quadrant 3: Home 76-160, Neutral 101-200, Away 135-240
  • Quadrant 4: Home 161+, Neutral 201+, Away 241+

For a team’s resume, Q1 wins mean considerably more than a Q4 win, and Q4 losses hurt a team more than a Q1 loss does. Games can also move between quadrants as the season progresses, for example, say San Diego State were to play BYU at home and BYU is ranked in the top 20 that game would be considered Q1 at the time of the game, but if later in the season BYU drops out of the top 30 that game is moved down to Q2. Say Boise State plays and beats a team like Texas A&M on the road and at the time Texas A&M isn’t in the top 75 but then Texas A&M goes on to have a great season and finishes in the top 75 that win would become a Q1 win for Boise State.

Currently, the Mountain West has six teams in the top 60, and Utah State just on the outside at 65. This could mean a three-plus bid Mountain West or it may not, as these rankings are not set in stone for at-large berths for the NCAA Tournament.

Rather, these are a tool to use to create the full picture.

Adjusted Net Efficiency

The Efficiency metric in the NET focuses on taking scoring into account in the rankings. Net efficiency is essentially a team’s offensive efficiency minus defensive efficiency. Efficiency is calculated by total points/total possessions, so on offense, it would be offensive points scored divided by offensive possessions, and on defense, it would be opponent points divided by possessions. Say a team scores 90 points on 40 possessions that team’s offensive efficiency would be 2.25 per possession.

If the same team allows 70 points on 40 possessions to its opponent, the defensive efficiency would be 1.75 points per possession, and the team’s net efficiency would be 0.5. Now comes the adjusted part of the efficiency factor, and that is to compensate for the fact that teams play at different speeds and tempos. If Team A has a net efficiency of 0.5 points per possession, and that team averages 40 possessions per game that team has an Adjusted Net Efficiency of 20.

If Team B has a net efficiency of 0.4 points per possession but averages 55 possessions per game Team B would have an Adjusted Net Efficiency of 22 and would therefore be ranked higher then Team A in Adjusted Net Efficiency even though Team A has a higher Raw Net Efficiency. 

The NCAA doesn’t say what the exact algorithm is for using these two factors, but these two factors are used to rank teams and help the NCAA Selection committee determine seeding for the Tournament as well as what teams get an at large bid to the tournament.



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