Opponent and other news and results 2025-2026

[ugarte]

The point of KRACH (or NPI) for this discussion is to select teams to play in a postseason tournament. For that, I don't want something predictive. I want something that "ranks teams the best it can

You do a fine job capturing a much-abused nuance of statistics: the difference between predictive and descriptive statistics.  However, I cut you off before you got into sampling because sampling muddies the issue. 

ftr i phrased it the way i did because it was a direct quote from bearlover. if a small sample is the best we've got - as he believes, and tbh i figure is probably correct yet still MUCH better than what football has to work with - then that's the data we use. KRACH appears to be the best for the job (and i think everyone here generally agrees) under the circumstances.

i have no opinion on H/A weighting!

[abmarks]

As the one who brought up krach, I can say that no one realized what I was asking.

I was trying to ask Adam if he could recalculate the historic home advantage with a krach adjustment.   He had given us the actual numbers from past season(s) as a measure of the "true" home advantage in terms of wins.

I thought that the historic evaluation would be more meaningful if krach adjusted to show us how much home advantage there really is historically.

  Adam- would still like to see a krach adjusted home advantage (calculating the advantage each game depending on opponent)  and see how much it diverges from the simple star you gave.

I'm not suggesting we krachify the home road weights for noon this way.

BL, we all know you hate krach, but Adam is correct that if you want to compare teams based on records to date, there is no better model, and this one has no arbitrary weights in it.  Also, JTW would have to confirm this, but that model wasn't developed to pick tournament teams.   It was a mathematical model that they thought was the best way of quantifying relative team strength based on games played.   Some did as ocate for that to be used for selection, but pretty sure it wasn't developed for that reason.

And again to BL, I was not looking for a future projection.   I wanted a statistical evaluation of the historical expected performance.    Consider it like xG, only it's xHW.

[BearLover]

BL, we all know you hate krach, but Adam is correct that if you want to compare teams based on records to date, there is no better model, and this one has no arbitrary weights in it.  Also, JTW would have to confirm this, but that model wasn't developed to pick tournament teams.   It was a mathematical model that they thought was the best way of quantifying relative team strength based on games played.   Some did as ocate for that to be used for selection, but pretty sure it wasn't developed for that reason.

I honestly have no idea what you're talking about. I have never said anything bad about KRACH. It's just not meant to be predictive and shouldn't be used to make predictions.

[Trotsky]

We all seem to be talking past each other here.  The Venn diagrams of what people want strongly overlap.  The divergence of how people characterize what each candidate system does are due to differences in information and understanding of the math.  I only listen to Whelan.  The rest of us are toddlers defacing differential equations with crayon.

[adamw]

Misconception means you had the wrong idea.

Being misled implies that someone was actually leading you in that direction. That your misconception was due to others.

Misinterpreting means you made an assumption that was incorrect. So your misconception was due to your own misinterpretation.

Unless you can show where you were led astray, I think that you misinterpreted and weren't misled.

for some people to admit this, would actually require an iota of humility. So - don't hold your breath.

[adamw]

Just to clarify what I mean above—

KRACH (and the Pairwise, and the NPI) are built to pick the 16 teams most deserving of the NCAA tournament (and their order). That is a very different thing than a predictive model. KRACH may well be the best model we have at choosing NCAA teams, but it's not built to be predictive and shouldn't be used that way.

KRACH et al are mostly just a function of winning percentage and strength of schedule. As they should be, because that's how we should choose who has earned an NCAA bid. But you get absurd results when you extrapolate that to future performance. With a large enough, and representative enough, sample, this would start to even out, but in college hockey this isn't possible (because seasons are very short and teams only play a small subset of other teams). 

You can't just plug in two teams' win% and SOS and try to predict which one will win. (Try doing that with college hockey games, you'd lose a ton of money.) There's wayyyyy too much luck and other factors that affect the tiny sample of games on which win% and SOS are based. Again, this is not a knock on KRACH-it's doing its job just fine. Its job is not to predict future performance.

You continue to make a really odd assertion that we (I) don't seem to know this. We're not curing cancer dude. Our Probability Matrix, which I assume you refer to, is just for poops and giggles.  That said, it does provide some utility, because it plays out the schedule based on who wins and loses, including conference tournament brackets. That could get pretty complicating to do by hand. Ergo - SOMETHING has to be used to pick the winner of each game. Thus KRACH. And with 10,000 simulations, it gives people an idea.

No one - ever - claimed that KRACH was some magic potion that predicted the future. You're arguing straw men.

This is also why myself - and others - have been working on using better models, with KRACH as the starting point. But we all have other lives, and it's not easy. There's also no sense of urgency, because the state of the world won't change based upon whether our Matrix is improved.

Other sites have simply taken all the possible win/loss combinations and played things out. Our Matrix decided to do Monte Carlo simulations instead, which allowed us to play out the season much further in advance. That's pretty much it. And I never claimed otherwise.

[adamw]

Anyway, related to the above and also something I was wondering during the podcast—the guest mentioned that coaches and fans have put their faith in these models because its outputs seem acceptable. That is, we see the 16 teams the Pairwise spits out, they pass the smell test, we move on with our lives and don't question the model. But I'm wondering if anyone has ever made a more rigorous attempt to quantify if the model is picking teams properly. I'm not sure how this would look or if it's even possible, but it did strike me as a little spooky that all this time we've been entrusting a computer model whose outputs we don't even have a means of judging past "the smell test."

Decided to split this up into two answers.

I mean, how it would like, can go a million different ways, and I think anyone close to it, does all sorts of tests to tinker around with what it would mean if this was tweaked or that was tweaked. Certainly the Committee/Tim Danehy do. But there is no god-like answer, so I don't even know how you'd answer that question. On what basis would you judge?

[adamw]

I was trying to ask Adam if he could recalculate the historic home advantage with a krach adjustment.   He had given us the actual numbers from past season(s) as a measure of the "true" home advantage in terms of wins.

I thought that the historic evaluation would be more meaningful if krach adjusted to show us how much home advantage there really is historically.

It takes me 30 seconds to run a query on the database to get winners of home and road games. It takes many times longer than that to do what you're asking

[Trotsky]

To return to our opponents, despite taking the last four penalties of the game Yale came from two goals down to beat Q 4-2 tonight!

[Iceberg]

To return to our opponents, despite taking the last four penalties of the game Yale came from two goals down to beat Q 4-2 tonight!

I'm pretty sure that was Yale's first win against Q since the championship game in 2013

[Chris '03]

To return to our opponents, despite taking the last four penalties of the game Yale came from two goals down to beat Q 4-2 tonight!

I'm pretty sure that was Yale's first win against Q since the championship game in 2013

Feb 2018 they said on the broadcast.

[jtwcornell91]

I'm not sure which message to reply to, and I don't have time to wade into the discussion at the moment, except to remind Adam that we actually implemented a version of KRACH that automatically fit the home-ice advantage, which we called KASA.  ("KRACH Adjusted for Site Advantage", a backronym which Ken Butler helped us construct.)

Also, a previous debate on the eLF did lead to a paper entitled "Prediction and Evaluation in College Hockey Using the Bradley-Terry-Zermelo Model": https://arxiv.org/abs/2001.04226

[marty]

RPI with their second win of the season stuns Clarkson who was relying on their backup goalie. 5-1.

My almost 3 year old grandson's first 2 periods watching NCAA Hockey.

Claimed he liked the puck drop but I think he liked playing with the chairs and watching the Zambonis.

[ursusminor]

Does RPI's 5-1 victory over Clarkson not count because CHN thinks the game will start at 7 PM? 

[Dafatone]

Somewhere in all the yelling Adam pointed out that the heavier home/road weighting helps incentivize big teams to play small teams on the road sometimes rather than just say, "we're [insert traditional powerhouse], you gotta come to us if you want to play us."

That's a good enough reason for me to be okay with it.