BubbAnalysis: NC State

Welcome to the latest edition of BubbAnalysis, formerly known as Bubble Breakdown, formerly known as Bubble Banter.

Right now I want focus on NC State. In the latest bracketmatrix, NC State is an 11. Yet my algorithm currently projects them on the 9-line, and unlikely to fall out even with a loss. What gives?

It inescapably comes down to non-conference strength of schedule. Because they played so many of the worst teams in DI, their "NCSOS" is dead last—at least based on the primary measure of NCSOS highlighted on the NCAA's Nitty Gritty report and Team Sheets, which is simply opponent's winning percentage (i.e. RPI Factor 2). This primitive measure is not an input to the T-Ranketology algorithm. In fact, my algorithm gives no separate weight to strength of schedule as a standalone input (though it is certainly incorporated into the algorithms inputs).

Most bracket projectors, I gather, do separately consider SOS and especially the NCSOS, and I understand why they do. First, it's a number on the official documents. Second, there have been a few high profile cases where a bad NCSOS was specifically mentioned as a reason that a team was excluded. A couple of Seth Greenberg's Virginia Tech teams come to mind here.

I did not include SOS or NCSOS in the algorithm for a few reasons:

• In prior years, the committee used RPI, which was highly correlated to SOS because it was 75% composed of schedule metrics. Indeed, the current "SOS" numbers on the official NCAA documents are just what used to be called RPI Factor 2, which was 50% of the RPI formula. So it was possible to simply use RPI and get good enough results with the algorithm. For example, the 2010 Virginia Tech team that was snubbed supposedly because of its terrible NCSOS also had an RPI rank of 59—not a disqualifying rank, but definitely in the area where a team is not likely to be selected. (My current algorithm would have had them the last team in the field—close enough!)

• It's a very very noisy signal. There are many examples of teams with terrible schedules getting in, and getting good seeds. Just as an example, last year Michigan had a bad NCSOS and got a three-seed. And there are many examples of teams with very good schedule metrics who nonetheless were left out or down-seeded. So it's hard to figure out how to put this into an algorithm because in the vast majority of cases it clearly has no impact whatsoever (at least independent of its effect on RPI).

• Strength of schedule is accounted for in Kenpom, BPI, Sagarin, KPI, and SOR — the other metrics on the official docs. People seem to resist this, but it's clear that Kenpom has long had some effect on selection decisions, and that was formalized last year with its inclusion, along with those other metrics, on the team sheets, etc. Teams that play terrible schedules will typically be punished in those systems unless they actually perform very well against those opponents.

Now, with the NET this year things are up in the air. If we were still using RPI, there is zero doubt that NC State would be disqualified from consideration for an at-large. (Their RPI rank would be 100+, far beyond the realm of consideration, certainly in my algorithm.) And the reason their RPI would be so bad is because their NCSOS kills it. But their NET is in the low 30s, their power ratings are in the 30s, and they have 8 Q1+Q2 wins. Only one team with that profile has been left out since 2008: last year's USC team, which was widely considered an at-large shoo-in. (By the way, their NCSOS rank was a perfectly respectable 62.)

That leaves the question: will the Committee rely on RPI Factor 2 to downgrade NC State, despite having a profile that otherwise matches dozens of at-larges and just one snub? It might! And if it does, I'll probably tweak my algorithm to incorporate some kind of special punishment for having an extremely bad RPI Factor 2 in non-conference games. The easiest way to do this would be simply to put RPI itself back into the mix somehow.