Future algorithm adjustments

[bvankat]

• Consider WAB as an additional resume metric?
  • Does Torvik calculate this early in the season?
• Bonus/penalty for Quad 1 wins and Quad 3/4 losses.
  • 3-4 Q1 wins seems like the high end for 2022 bubble teams.
  • Teams with 3 Q3 losses are very bubbly.
  • Only one team in NET top 70 has more than 1 Q4 loss
• Injury adjustments
  • Could base on Sports Reference Win Shares (#)

[bvankat]

Consider: Adjust for victory/defeat margin within Q1/Q2 games. Nebraska didn't play many good teams close in 2023, lots of blowouts. The predictive metrics did not like that. SOR/KPI gave them credit for playing good teams, so there was a 50+ rank difference between the resume and predictive metrics.

UPDATE: Here's some detailed analysis of a similar erratic team: 2023 Missouri — https://www.rockmnation.com/2023/3/2/23621266/missouri-tigers-basketball-analysis-2022-23-net-rankings-explainer-ncaa-tournament-dennisgats

[bvankat]

Related to the margin comment above: Perhaps Kenpom Luck or Torvik FUN or Haslametrics Consistency metrics can be a proxy for explaining that variance? High-luck teams likely have wide gaps in metrics.

[bvankat]

Kenpom has good thoughts on how the quadrants should be broken down: https://theathletic.com/1465470/2019/12/17/kenpom-an-idea-of-a-better-quadrant-system-to-reward-bubble-teams/

• Argues for smaller Quad 1
• Eliminate the games against the lowest opponents.
• Undefeated in Quad 3-4 is a sign of a good team

[bvankat]

Related to the margin comment above: Perhaps Kenpom Luck or Torvik FUN or Haslametrics Consistency metrics can be a proxy for explaining that variance? High-luck teams likely have wide gaps in metrics.

What about looking at margin in Quad 1 and 2 losses? Close losses indicate higher quality — especially road losses. Blowouts would maybe indicate they're less reliable/lower quality.

Nebraska's current losses in 2023-24 🫣:

• Creighton by 26 (Home, Quad 1)
• Minnesota by 11 (A, II)
• Wisconsin by 16 (A, I)
• Iowa by 18 (A, I)
• Rutgers by 6 (A, II)
• Maryland by 22 (A, II)

[bvankat]

Hoop Explorer lets you build and save a leaderboard with weighted inputs for resume vs efficiency, quality and dominance. Could be a nice way to calculate a bonus/penalty for the quad and margin adjustments. Look especially close at Wins Above Elite. (LINK)

[bvankat]

Might want to add an intangibles bonus for being undefeated in Q3 and Q4. In reality this might offset perceived weakness of playing a soft schedule. In practice this would offset the penalty applied for having NCSOS above 250.

[bvankat]

Game score might be another proxy for game performance vs good and bad teams. You can get a high game score and lose — moral victory. You can get a low game score and win — moral defeat. So what about checking game score in Q1 games and game score in Q4 games and see if they're under- or overperforming?

A better metric would be to calculate expected margin vs actual margin in those games. (LINK)