(Updated with games through 3/11/2023)
Track your college basketball team’s quad 1 wins along with their record in the other three quads. The quadrant classification system breaks down a team’s schedule and results in four quadrants with the purpose of placing greater emphasis on games played on neutral courts and in true road environments. The “Quad Score” combines the quadrant records for a team into a single metric by dividing the accumulation of quad score points by the number of games played.
- Click column header to sort
- Hover over number to see list of teams
NCAA Team NET Quadrant Wins and Losses Tracker
(NET rankings from NCAA.com)
Any chance you could provide the link for this dataset?
Thank you for asking, Brian. Link added
Thank you!
Is the specific Quad win and losses based entirely on where the opponent was ranked at the time of the game? For instance, If North Carolina plays at Wake Forest and Wake is ranked in the top 75 that would be considered a Quad 1 game. However, is Wake Forest goes on a down spin and ends up ranked 90th, is the game NC at at Wake still considered a Quad 1 game or it is now considered a Quad 2 game?
Great question, David. The classification of past opponents is updated every day with their current NET ranks. So in your scenario, yes – the Wake Forest game is re-classified as a Quad 2 game.
It’s technically possible for North Carolina’s win over Virginia Tech (current NET: 42) to be reclassified as a Q1 win. There are a lot of factors at play, but VA Tech would probably need to win most of the rest of their games (except the one against UNC) – and win by double digits. Scoring margin matters.
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I don’t like this methodology as much as others because there are no metrics as far as “then” versus “now”. I mean if a team struggled a month ago but most of their quad one wins are more recent (they are on a roll “now”) then this method is not measuring that parameter.
If one team has four quad one wins and they were all before Christmas and another team has four quad one wins but all in the last month, then I’m saying the latter team is hotter, looking at then versus now history.
Thanks for the comment, Mike. I assume you’re referring to the Q Score. My intention is to aggregate Quadrant wins and losses into a single metric in a simple, straightforward way.
If you’re looking for a ranking methodology that is a better predictor for future performance, then I’m with you. A rating that weights more recent results a little more is preferred.
The Q Score could be considered a resume-related metric. The Selection Committee doesn’t consider how hot a team is, so at least the Q Score is relevant.
I’m curious. What other methodologies that consider recency do you like more?
I’m most interested in seeing the actual team-by-team breakdown of Quad wins. Am I missing something as far as more specific team breakdowns?
This page shows the number of wins and losses every team has in each Quadrant. If you’re viewing on a PC, you can hover over the number to see which teams make up that total. If you are looking for more details, the NCAA publishes Team Sheets. It’s a pdf document with a whole page dedicated to showing the details of a team. Click on the “NET Team Sheets” link: https://extra.ncaa.org/solutions/rpi/SitePages/Home.aspx
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