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RIP RPI

Division I Men’s Basketball Committee adopts new ranking system

The NCAA has developed a new ranking system to replace the RPI as the primary sorting tool for evaluating teams during the Division I men’s basketball season. The new ranking system was approved in late July after months of consultation with the Division I Men’s Basketball Committee, the National Association of Basketball Coaches, top basketball analytics experts and Google Cloud Professional Services.

The NCAA Evaluation Tool, which will be known as the NET, relies on game results, strength of schedule, game location, scoring margin, net offensive and defensive efficiency, and the quality of wins and losses. To make sense of team performance data, late-season games (including from the NCAA tournament) were used as test sets to develop a ranking model leveraging machine learning techniques. The model, which used team performance data to predict the outcome of games in test sets, was optimized until it was as accurate as possible. The resulting model is the one that will be used as the NET going forward.
 
BLUEDOGHOUSE said:
It is better but there is a cap on scoring margin of 10 pts if not mitaken. That to me is a very low cap. Would prefer 20 pt cap. Games are nail bitters all the time until late game fouling which push the result to +10.
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This could mean that coaches will tend to keep their starters in longer just to ensure a 10+ point victory. If you think back to the National Championship game in 2004, its crazy to think the final margin was 9 points. I think at some points we were up by almost 30.
 
Scoring margin cap and the defensive efficiency metric helps us, I think. We aren't going to huge scoring team but I think we may be a very disruptive team on defense when I look at past Hurley teams and the tools he has to work with this year.
 
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gioff23 said:
I'll bet you a cold one that this turns out very well for the schools that were behind the change, that is the so-called P5
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In the SOS algorithm, all non-P5 schools are given a ranking of 300.
 
Ts5034 said:
This could mean that coaches will tend to keep their starters in longer just to ensure a 10+ point victory. If you think back to the National Championship game in 2004, its crazy to think the final margin was 9 points. I think at some points we were up by almost 30.
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IMO that’s much less of a problem than Pitino keeping his starters in the whole game against Weber St and winning by 50, then complaining in March that he’s under seeded when in reality, his team’s efficiency vs the top 100 teams was way worse than it was in November.

Or take UConn’s team last year. If we were down 10 in the second half, forget it. Their foot was off the gas and we’d lose by 20+. I’d rather have something in the 10-15 range than 20. If a team is losing by 15 with 5 minutes left, chances are they’re giving up. Should they? No, but the team they’re playing doesn’t have to benefit any further from it.

This is a cool tool IMO. Not an end all be all by any means, but it beats RPI for sure.
 
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very interested to see how this turns out.

i had made a few attempts at developing a machine learning model based on team stats and kenpom to build my brackets in prior years.

the main issue i foresee with this is machine learning methods (neural networks in particular) are usually a black box in that it can be hard to explain why the model made a specific decision. so when this new model leaves your team out of the tournament it may not give you a clear reason why.

and for those that are always looking for the anti-uconn angle in ncaa decision making, perhaps they trained the model with a bias against uconn, to ensure lower rankings in the future.
 
kobebeanbryant said:
very interested to see how this turns out.

i had made a few attempts at developing a machine learning model based on team stats and kenpom to build my brackets in prior years.

the main issue i foresee with this is machine learning methods (neural networks in particular) are usually a black box in that it can be hard to explain why the model made a specific decision. so when this new model leaves your team out of the tournament it may not give you a clear reason why.

and for those that are always looking for the anti-uconn angle in ncaa decision making, perhaps they trained the model with a bias against uconn, to ensure lower rankings in the future.
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Thankfully the committee will still exist. This will just be used to organize the teamsheets and give the number side context they use in their evaluations.
 
Thanks NCAA, now ECU and Tulsa can continue to schedule the dregs of college basketball. - Mike Aresco
 
Anytime you see "strength of schedule" and "quality of wins and losses", run for the hills.

Who, using what criteria, sets the baseline from which "strength of schedule" is determined at the beginning of the year? Is there some method by which it will be mitigated as the year goes on if teams' schedules are rated inappropriately at the start of the year?

How do you measure "quality of wins and losses"? Using what criteria? Will this system continually adjust the SOS and "quality" measures so early season biases are overcome by the final rating date?

Can't wait for "conspiracy kitty's" take on this, especially as to whether it is designed to benefit the Power Five and the NBE.
 
pj said:
Thanks NCAA, now ECU and Tulsa can continue to schedule the dregs of college basketball. - Mike Aresco
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One might argue that at least ECU IS the dregs of college basketball! Oh, sorry DePaul...
 
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Scrutiner said:
Anytime you see "strength of schedule" and "quality of wins and losses", run for the hills.

Who, using what criteria, sets the baseline from which "strength of schedule" is determined at the beginning of the year? Is there some method by which it will be mitigated as the year goes on if teams' schedules are rated inappropriately at the start of the year?

How do you measure "quality of wins and losses"? Using what criteria? Will this system continually adjust the SOS and "quality" measures so early season biases are overcome by the final rating date?

Can't wait for "conspiracy kitty's" take on this, especially as to whether it is designed to benefit the Power Five and the NBE.
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To confirm your answer to your own question: Most of that is derived from scoring margin throughout the season as games are played.
 
freescooter said:
One might argue that at least ECU IS the dregs of college basketball! Oh, sorry DePaul...
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Thanks, Mike Aresco, for scheduling UConn with the dregs of college basketball every year.
 
auror said:
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pay-no-attention-to-the-man-behind-the-curtain.jpg
 
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auror said:
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NCAA won’t apply NET metric to previous yrs for comparison

Now THAT is ridiculous. No need to see if this is a quality metric via back testing. Just trust us...

auror said:
They [NCAA] heavily outsourced the research.
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Ahhhhhh there's the NCAA I know and love. Passing the buck like an old pro.
 
intlzncster said:
NCAA won’t apply NET metric to previous yrs for comparison

Now THAT is ridiculous. No need to see if this is a quality metric via back testing. Just trust us...
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They don't want us to realize for several more years that it gets more P5 teams into the tourney, with higher seedings.
 
Don’t all these ratings start with a preseason ranking and then go from there? Which gives the teams/conferences that always get the top pre season rankings an advantage.
 
uc1990 said:
Don’t all these ratings start with a preseason ranking and then go from there? Which gives the teams/conferences that always get the top pre season rankings an advantage.
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Most phase out all pre-season impact at some point in the season. For this system, the results before/during the season don't matter in the slightest, only when time to select for NCAA tournament, so there's no real reason to even include anything.
 
auror said: ↑
They [NCAA] heavily outsourced the research.
Click to expand...
Ahhhhhh there's the NCAA I know and love. Passing the buck like an old pro.

I get where your coming from BUT this might be for the best - nobody at the NCAA is smart enough to add 2 + 2 never mind work on something like this
 
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