He got his first and-1 vs. Texas Southern. It’s a start.
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I’m no stats guy (more of a stats groupie), but I think that’s incorrect. I agree with you that the preseason ranking is wonky, but I think (1) the algorithm that predicts the season (and includes Dunn wonkiness) and (2) the algorithm that looks at in-season data are separate, which is why I like to look at just the in-season stuff. As with everything, I could be wrong.
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The smart thing would be to avoid doing metric based rankings until there is a sufficient dataset from the current season. In the portal era, preseason metric rankings are completely useless.
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Should have noted, I totally agree with this
Agree, but the fun thing is to look now! Also, I wouldn’t say preseason is completely useless, but I would say trending toward less useful.
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I think there’s too much hand wringing about the national polls. They mean very little until maybe mid-to-late January when jockeying for final poll positions that could impact NET.
But by then things have typically settled either way.
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The one thing that I know as an absolute fact is that our basketball team is freaking amazing this year, and any computer algorithm that says otherwise based on so-called “data” is just some voodoo mumbo jumbo.
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I mean, the smart thing would be for people to just not take it too seriously until there’s sufficient sample size. Those guys are just making public their results and have documented exactly how it works. Everybody arguing about it as if it were gospel before the season or two weeks into the season are more the problem.
Also to be clear, I’m totally ok with it in this instance - but not as much some others - because it’s just sports. There are like no actual real world stakes to putting data out there on team performance and people misinterpreting it. If there were, eh, might take it more seriously.
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Semi-serious thought on this, though, is that KenPom has kinda become like a public utility for the gambling community, and I suspect he’s aware of this.
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He must have been so relieved with that one. You could tell he was getting annoyed against UF with not finishing the and-1s. Hopefully this was just a quick adjustment period to college-level defenders. He certainly looks strong enough to handle contact!
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I mean zero offense by this - folks should have fun however they please! - but not sure I consider gambling outcomes as meaningful real world stakes anybody else should have to plan around. Plus, gamblers should be well aware of these type of models’ shortcomings - if anything they should probably look to exploit that when looking at early season lines if they can somehow.
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I’m stating the obvious here but the sample size is so small that there can be huge swings after each game. Before the Texas Southern game, Torvik had our offense 19th and defense 40th (removing preseason adjustments). Now offense is 49th and defense is 6th.
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This is much better, though I honestly think Duke is a little too high. I don’t say that because I hate them – which I do – but I think they have issues at the 5 that could be exploited by a couple teams ranked lower.
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Agree. I think that’s where the $$ is to be made in college hoops gambling – get your takes in early on where KenPom is off in the preseason, and find the inefficiencies until it calibrates. But I feel like I am noticing more lines adjusting away from KenPom these days, more so than early on in recent seasons. Like the gambling community is figuring it out… (not me, to be clear – no joke. Find the stuff fascinating, but don’t get into it)
It’s a metric. They are intentionally devaluing their metric by including data that is not relevant. Should people take it less seriously? Absolutely. But they craft an important narrative at the beginning of the season that has an effect throughout. Given how subjective the committee’s determination is at the end of the year and how it can be effected by initial KenPom decisions, I think it’s relevant that they include info that is becoming less and less relevant.
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I’ve read that the best way to bet college basketball is to follow a smaller conference very closely all year. It’s impossible to know everything about 360 teams but knowing the little things about 8 or so teams isn’t crazy. Vegas isn’t adjusting lines for random injuries in the NEC that hardly get any action.
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When I was a younger man, I did okay with some MAC-tion (football). It was the year of Big Ben, Burner Turner, et al, so hadn’t yet achieved peak MAC-tion (i.e., until after that). That has poisoned my brain to think I could do that again in the future, but hopefully I have the good season not to put much $$ into it. 
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But I don’t agree that is what they are doing. At least as I understand it (folks should correct me if I’m wrong) the reason they produce these models is not to provide a live ranking of who is the best team or most deserving of inclusion in the tourney. They are predictive models - the goal is to pull together information that will help give a reasonable prediction of how a team will fare in its next game.
Consequently, early in the year it makes sense to pull in data from the prior season and data on players added to the roster. It is very imperfect data, but it still holds some predictive power. In other words, if somebody is asked to call who is going to win a game on the opening night of the season, they’d probably be way better off consulting pre-season Kenpom rankings (as flawed as they are) and making the call than making the call with zero information.
I guess it comes down to a discrepancy in what the models are actually designed to do and how people talk about them. But they weren’t designed to make picks for the tournament.
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Look i get that Kenpom is predictive model. I get what Kenpom is doing but a lot of people who make calls later on do not. Kenpom knows that. Their effect on the game is huge. I think putting together increasingly irrelevant models does more a disservice to the game than keeping them in.
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Sorry, you lost me. What is making kenpom etc increasingly irrelevant?
kenpom itself itself is very relevant when taking into account current year; however, with the pace of transfers and roster uphesion, its early season data is increasingly irrelevant.