Abolish the Quadrant System (And Use Win Quality Instead)

Introducing a new resume metric that makes understanding wins and losses easier

Every year, the process for selecting teams to the NCAA tournament becomes slightly more numbers-based. This is primarily a good thing, as well-constructed metrics that are driven by data help the tournament selection rules become clearer and less subjective. Even this offseason, the NCAA has added two new metrics to the official team sheets used by the selection committee.

One commonly used resume sorting metric is problematic: the quadrant system. The premise of the quad system is simple: a team’s wins and losses are divided into four quadrants based on how difficult that game is deemed to be, using a combination of the opponent's NET ranking and whether the game took place at home, on the road, or at a neutral site.

On the surface, a team’s quadrant records provide a good summary of the types of wins and losses that a team has. For example, here are Louisville’s quadrant records as of Wednesday, January 29th, courtesy of WarrenNolan.com:

An experienced resume evaluator can immediately see that Louisville has performed pretty well in its toughest games (.500 in Q1) while handling all other easier games without a hitch (11-0 in the non-Q1 games). In fact, just five teams have more Quad 1 wins than Louisville: Auburn, Oregon, Iowa State, Kentucky, and Texas A&M.

The most glaring issue with the quadrant record system is the sensitivity of the quadrant cutoffs. A Quad 1 loss can turn to a Q2 loss overnight, just due to that opponent moving from the 75th to 76th in the NET without even playing a game. The cutoff points are arbitrary, picked to be nice numbers divisible by 5 so that they are easy to remember:

Furthermore, all wins within the same Quadrant are treated equally, which is incredibly unfair. A win on a neutral against Bradley counts as a Q1 win, just like a win on the road at Auburn would. These hard-set quadrants make sorting wins and losses into categories easy, but you lose so much valuable information in the process.

In summary, the quadrant system aims to explain how good a team’s wins and how bad a team’s losses are, but the execution is flawed. I’ve been told that the selection committee is much more nuanced in the way it evaluates these wins and losses, but for someone who is taking quadrant records at face value, it can be misleading.

Resume Quality at EvanMiya.com

To improve this, I have created a new resume metric at EvanMiya.com called Resume Quality, which divides your body of work into two numbers: Win Quality and Loss Quality. Similar in nature to Wins Above Bubble (BartTorvik.com), Resume Quality determines how difficult each game on a team’s schedule is based on how a team on the at-large cutline would fare in those games. The real value of this metric comes in splitting up wins and losses into several categories:

Win Quality: This measures how good your wins are based on the difficulty of those games. A team with a high win quality has won many tough games.

Loss Quality: This measures how bad your losses are based on the difficulty of those games. Having a loss quality close to zero (loss quality is negative) means that you don’t have many losses, and/or your losses came against good opponents. A lower loss quality often indicates that you have lost some games you should have won.

Resume Quality: This is the sum of Win Quality and Loss Quality. It’s also equal to your number of wins minus the expected number of wins that a bubble team (defined as a team good enough to get the last at-large bid) would have against your schedule.

The table below shows the top teams in Resume Quality, which can be found on the Team Resumes page at EvanMiya.com:

You can also hover over any team’s Win Quality or Loss Quality to see the value of their best wins and worst losses. For example, here are Auburn’s best wins, with their Win Quality values:

How It’s Calculated

The difficulty of each game is determined based on how likely an average bubble team (defined here as a team right on the tournament at-large cutline) would be to win against that opponent at that venue.

For example, Mississippi State lost at Auburn this season. According to the current team ratings at EvanMiya.com, the probability that an average bubble team would win at Auburn is just 14%. If Mississippi State loses, its loss quality decreases by 0.14. However, if It wins, its win quality increases by 0.86, which is equal to 1 minus 0.14.

Notable Resumes

It’s worth highlighting several teams that have interesting resume metrics based on this new system:

Louisville is ranked 17th in Resume Quality. As mentioned previously, the Cards are 5-5 in Quad 1, with only 5 teams having more Q1 wins. However, in terms of Win Quality, they rank 14th, with their best wins coming at Pittsburgh, at SMU, and at Florida State. All of those wins were on the road, but none of those opponents rank inside the top 35 at EvanMiya.com, which is why Louisville’s Win Quality ranking isn’t higher. The Cards are 26th in Loss Quality.

Memphis has a polarizing resume, clocking in at 15th in Resume Quality. There’s a big disparity between their wins and losses. They rank 8th in the country in Win Quality, with their best wins being at Clemson, on a neutral vs Michigan State and UConn, and at home against Ole Miss. However, they have taken some bad losses, including at home to Arkansas State and away to Temple, leading to a Loss Quality ranking of 32nd.

Resume Quality shows that Auburn has the best resume in the country by a mile. They are 1st in both Win Quality and Loss Quality, with their lone loss coming at Duke, which is only counted against them by 0.15. Their best wins are against Houston, Iowa State and Purdue on a neutral, and on the road against Texas and Georgia.

I believe that UC Irvine deserves an at-large bid if the bracket were constructed today. UC Irvine is 37th in Resume Quality, which would be good enough for a 10 seed. The Anteaters are 17-3, ranking 47th in Win Quality and 22nd in Loss Quality. Yes, they don’t have an eye-popping win on their schedule against a top-50 team, but they’ve won more games than a bubble team would be expected to win against their schedule. Only sporting three losses is very impressive.

How Is This Different Than Wins Above Bubble?

The premise of Resume Quality is very similar to Wins Above Bubble, partly because I think WAB is the best existing resume metric we have. There are a few notable differences, though:

• Separating the Resume Quality number into Win Quality + Loss Quality gives a much clearer picture of a team’s work than just using one number.

• Game difficulty calculations use team ratings at EvanMiya.com, not the NET or some other site like BartTorvik or KenPom.

• An “average bubble team” is defined slightly differently. For Resume Quality, I define an average bubble team as a team that would just get into the field as the last at-large team. Right now, this means that there are 45 teams with a Resume Quality above zero, almost identical to the actual number of teams that receive at-large bids on Selection Sunday. I don't know how WAB is calculated by the NCAA, but at BartTorvik.com, there are 53 teams with a WAB score above zero as of today, which is many more than will make the tournament an at-large. This discrepancy doesn't lead to big changes in the ordering of the teams according to Resume Quality or WAB. Still, I like the interpretation of Resume Quality better: If you have a Resume Quality above 0, you have a resume good enough to make the tournament.