I posted this in another thread, but we’re #2 on defense and #1 overall on Bart Torvik’s site since Clingan returned on 1/17.
JeebusI posted this in another thread, but we’re #2 on defense and #1 overall on Bart Torvik’s site since Clingan returned on 1/17.
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T-Rank - Customizable College Basketball Tempo Free Stats - T-Rank
T-Rank College Basketball Ratings and Rankings. And fun.barttorvik.com
Must be the 8 Q4 games
why that even matters is ridiculous...who cares if you play the #175 v #325 team??
The issue is that we played teams that are considered very bad and then underperformed the expectations. You don’t get credit for beating a really bad team if you couldn’t cover the spread. These models are all stat based and the numbers from those games don’t flatter us compared to what we’ve done versus better opposition.
According to Torvik the game against Mississippi Valley State was about as bad as our loss to seton hall and we won by 34. If we’re gonna play teams that bad we gotta win 50 plus I guess
Silly stat.
Thx for the info…but that shows it’s a broken model. So beating a bad team by 50 is good but letting your walk ons play and only winning by 35 is bad??? Do they track whose playing ? If not, That’s a model that shows nothing.
There’s plenty of models that track lineups. Every single model on the planet is flawed, that’s why there are so many of them. If we had a perfect model, we wouldn’t have the rankings determined by sports writers who haven’t watched the majority of the games in a given week.
Yes, some of the models like Torvik take that into account and ignore the late game walk on minutes when a game is considered analytically over
Your posts in this thread are so far off base I don't even know where to start, so I'll just go with a broad suggestion of ignore it all
I’m genuinely interested in what you mean.
Basically yes, but I think you're overstating the impact of the games vs a 300+ team over 150-200. It's all about how you perform relative to expectations, so the expectations change depending on opponent. You don't need to outperform lower rated opponents any more than you do middle or high level opponents.
That definitely could be true. I assumed if the difference in the adjusted rating between #150ish and MVSU was bigger than between us and #150, it'd have a pretty substantial impact, but I am definitely always learning. I mostly used AdjEM but I did run the numbers of both offensive and defensive efficiency and it was true for both of those as well.
I think it's actually a level deeper than that. So it's not just that MVSU has a worse defense than UMass Lowell, but we'd be expected to score more points against MVSU. So if we're expected to score 70 and go for 70 against UMass Lowell that's the same as scoring 95 if that's what we're expected to get against MVSU
In real life, there's no benefit. It's a bad line of code in an otherwise good algorithm.
You don't have to embarrass the other team, the advanced models are never looking for a 75 point win. The MVSU game was about as drastic a difference as you'll see and that was projected at 41 points. And FWIW we played our worst game of the season, won by "only" 34 and our advanced metrics barely moved. On KenPom we went from 26.87 to 26.61
TRUE
We play too many of these games. Theyre bad to watch, bad for team development, bad for our budget.
Maybe Torvik or KenPom track this already, correct me if they do...
Bad for team development? Not sure I can say this. Hurley needed to integrate three new players into the starting lineup and develop depth with only one player, Hassan, having significant experience as a role player. And yet we’re #1 with a better record than last season at this juncture.
This is what Haslametrics does. He basically ends the game for scoring margin when it goes analytically final.
