Conference Tournaments kick off this week, so we look beyond the bubble at the teams with the best shot of ruining someone's hopes of an at-large bid. This week we focus on the tournaments that start early, which means the WCC, OVC, and MVC. We also have an updated S-Curve after the chaos of the past weekend.
https://www.crackedsidewalks.com/2022/03/casing-bid-thieves.html
Although not in a bid thief conference, Jamal Cain and Oakland have a very interesting game today against IUPUI. The opponent only has 5 players.
https://www.sportsline.com/cbb/news/horizon-league-tournament-college-basketball-odds-iupui-with-only-5-players-available-tuesday-vs-oakland/
Quote from: brewcity77 on March 01, 2022, 11:58:06 AM
Conference Tournaments kick off this week, so we look beyond the bubble at the teams with the best shot of ruining someone's hopes of an at-large bid. This week we focus on the tournaments that start early, which means the WCC, OVC, and MVC. We also have an updated S-Curve after the chaos of the past weekend.
https://www.crackedsidewalks.com/2022/03/casing-bid-thieves.html
Ohio State about to take a Q4 loss at home to Nebraska. How detrimental is that?
Now Michigan State blown out by Michigan.
Marquette has a chance to creep up with a win tomorrow.
Quote from: GoldenEagles03 on March 01, 2022, 08:09:19 PM
Ohio State about to take a Q4 loss at home to Nebraska. How detrimental is that?
So apparently not much...OSU falls just 2 spots and by beating OSU Nebraska improves from 166 to 148 therefore making OSU's loss a Q3 and not Q4. I live in Columbus and the sky is very much falling for the fan base though.
Quote from: mu_eyeballs on March 02, 2022, 12:27:50 PM
So apparently not much...OSU falls just 2 spots and by beating OSU Nebraska improves from 166 to 148 therefore making OSU's loss a Q3 and not Q4. I live in Columbus and the sky is very much falling for the fan base though.
From an NET ranking perspective, it won't move them much. At this point in the season, every team has 25+ games that impact their scores (not to mention all their opponents' games) so each individual game can only move their score so much.
But from a resume perspective, adding a Q3 loss, especially one that is a borderline Q4 loss, could drop them several spots on the s-curve, maybe even drop them a whole seed line.
Quote from: TAMU Eagle on March 02, 2022, 12:40:11 PM
From an NET ranking perspective, it won't move them much. At this point in the season, every team has 25+ games that impact their scores (not to mention all their opponents' games) so each individual game can only move their score so much.
And yet, here we are with Nebraska making a pretty large swing (18 places) based on the results of one game out of 30 played so far.
Quote from: TAMU Eagle on March 02, 2022, 12:40:11 PM
But from a resume perspective, adding a Q3 loss, especially one that is a borderline Q4 loss, could drop them several spots on the s-curve, maybe even drop them a whole seed line.
And I'll add the whole quadrant system to my beef with the NET. Why is it that you get equal credit for a win against every team in a wide ranges (say 1 to 30 or from 31 to 75 for home wins). Certainly beating Gonzaga at home is more impressive than beating Boise State--but both would simply be classified as Quadrant 1 wins.
Or how about on the road? Why is it a more valuable win to beat Toldeo on the road rather than Iona (because it's a Q1 win vs Q2) as opposed to beating Gonzaga rather than Toledo (both Q1 wins).
If you're going to include a factor for team strength played home and away, why not simply calculate the road, neutral, and home win values for all 358 D1 teams spaced equally on a continuous spectrum. Beating #1 at home gives you the most NET juice. Beating #2 a little less. Beating #3 a little less than that . . . all the way down to #358.
That way you're not pretending that beating Toldeo on the road is no different than beating Gonzaga at the Kennel.
And yes, I know the other factors will account for the relative strength of Toldeo vs. Gonzaga. But when it comes to reporting metrics, both will show up as a Q1 win, which people obsess over when it comes to figuring out the better team.
Quote from: The Equalizer on March 02, 2022, 06:11:53 PM
And yet, here we are with Nebraska making a pretty large swing (18 places) based on the results of one game out of 30 played so far.
That's because Nebraska is in the middle of the NET rankings rather than the top or the bottom. The NET that we see is not a team's actual NET score, it is just the number that each team's NET score is ranked. Somewhere the NCAA's double secret vault, the NCAA calculates each team's NET score every day. Since the secret sauce has never been made public, we don't know what team's scores are. Like most stats, NET likely falls on a bell curve. The distance between the top ranked NET team and the and second ranked NET team is likely greater than the distance between the 134th ranked NET team and the 168th NET team (those specific numbers are a guess on my part). So the change in score between Ohio State and Nebraska was likely close to equal, but the change in ranking was different because there were likely more teams grouped together in front of Nebraska than there were behind Ohio State.
Quote from: The Equalizer on March 02, 2022, 06:11:53 PM
And I'll add the whole quadrant system to my beef with the NET. Why is it that you get equal credit for a win against every team in a wide ranges (say 1 to 30 or from 31 to 75 for home wins). Certainly beating Gonzaga at home is more impressive than beating Boise State--but both would simply be classified as Quadrant 1 wins.
Or how about on the road? Why is it a more valuable win to beat Toldeo on the road rather than Iona (because it's a Q1 win vs Q2) as opposed to beating Gonzaga rather than Toledo (both Q1 wins).
If you're going to include a factor for team strength played home and away, why not simply calculate the road, neutral, and home win values for all 358 D1 teams spaced equally on a continuous spectrum. Beating #1 at home gives you the most NET juice. Beating #2 a little less. Beating #3 a little less than that . . . all the way down to #358.
That way you're not pretending that beating Toldeo on the road is no different than beating Gonzaga at the Kennel.
And yes, I know the other factors will account for the relative strength of Toldeo vs. Gonzaga. But when it comes to reporting metrics, both will show up as a Q1 win, which people obsess over when it comes to figuring out the better team.
The quadrants don't impact a team's NET score. It is just a sorting system developed by the committee to help the casual fan compare resumes. We don't know exactly what goes into the NET formula, but my understanding that there is something like what you describe in your third paragraph factored in.
First, Quadrant 1 & 2 are further subdivided into A/B. The key I feel is to think of the first two quadrants in terms of neutral court seeds:
Quadrant 1A (Neutral 1-25): This is basically your top-6 seed lines of quality. Winning a Q1A game means you can beat high level, safe NCAA caliber teams.
Quadrant 1B (Neutral 26-50): The cutoff for the last at-large bid is usually the 46th-48th overall seed. Winning a Q1B game means you can beat at-large caliber NCAA teams.
Quadrant 2A (Neutral 51-75): A little fuzzier, but it's the Field of 68, close to 75. Winning a Q2A game is like beating a bubble team or mid-major autobid.
Quadrant 2B (Neutral 76-100): Think of these as low-major autobid teams or NIT teams. The last type of team that means anything positive in the eyes of the Committee.
Also, it's worth remembering before the quadrants, the team sheets broke games into batches of 100 regardless of location. The Quadrants are a much better way to divide the team sheets.