The T100 is usually a centrist model compared to the other 3 but this week not so much. Losses by Juniata, Baldwin Wallace, and Aurora displaced their T100 ranks farther compared to the other models. Misericordia & Messiah are rated at least 3 spots better in the T100 than any others, too. With a Messiah win coming in the Juniata gym last week, and their only loss a 3-1 defeat in Dallas to the #2 team below, the #1 according to the coaches, I can see how T100 is “singing” that tune. As for Misericordia – They have won 5 of their last 7 – Not to lose sight those two defeats were against 2 of the best 3 in the country with 4 of 6 sets lost by a deuce and one of the remaining two just a 3-point delta. The T100 doesn’t account for point differentials but noticing that just a bit ago sends a confident signal they should be favored over most any other “late teeners,” exactly what you’d expect to be true for a #14. Cal-Lutheran’s 2nd loss pushed the defending champs into the back half of the top 10 recently, for everybody, except Massey, whose model still sees them at #5. This could be a residual carrying over from last year’s stellar play – Not sure. Does anybody other than Coach Judd of Cal-Lu recognize 3 of their 5 losses to D3 programs the last couple years have come at 8 am or 9 am Pacific on the last day of 3- and 5-day road trips? Pretty sure they can be forgiven for that. Particularly because those conditions do not exist in the NCAA format should they be there again this year! Look out for the Kingsman!
This will not be a regular staple of the MORE. However, for those who are curious, you can find the median rank of every team from the same 3 models, for those teams not already listed above, by checking out the following:
Probably one of the last times I will be posting the Match Outcomes Venn diagram. The proportions are all regressing to their two-year averages over the last month. No reason to think it will change on a week-to-week basis. I might toss it out there at the end to see where it lands.
Those that read the latest post regarding the NEXT-GEN NPI might be waiting for the “Possible Chinks in the NPI Armor” series coming up soon, just weeks before its unveiling. Some might be wondering how a model not seen in action by me can be referred to as an “elegant piece” or a “nifty expression” of mathematics, too. I haven’t seen it in action because I was not privy to its 3-year look back, except to be told it offered the same choices as the committee decided upon those years, save for 1 or 2. The only question I asked for and was given an answer to, “What was the rank of the one team the T100 had as its median in 2024?” I did have Fall, 2024 data that lends itself to some clues, but as far as I know, none of these sports committees set its dials exactly like the MVB committee did theirs. Regardless of whether the NPI is great or not so much, it certainly won’t be because the committee failed to do its due diligence. Of this I am certain.
Related to my characterization, it being elegant or nifty. After becoming privy to the actual algorithm, I found myself drawn to it primarily because of its unique differences to the T100 methodology and its interesting conceptual use of numbers to arrive at the results. I was hoping to see something similar to what I was told it was based on, Pairwise Rankings from the Hockey realm, but was a little disappointed to not see that embedded. Maybe it’s a derivative, or maybe it was created by the same author, but to date I am confounded as to why that was the primary talking point from so many in the know early on.
Many NCAA models from the past have so much in common that I really don’t like. It makes me a little skeptical for how accurate the NPI could be across the whole. When you build as many models as I have, you come to expect they all will breakdown under the right set of circumstances. That the NCAA increased the number of total bids across all sports the same year as its inception doesn’t lend confidence, either. However, in the same way I get intrigued at trying to forecast the strength valuation of volleyball teams, it is a similar challenge to attempt to predict how the NPI might demonstrate weakness. With the very limited information I have been able to dig up, the challenge is even greater and forces me to think outside the box more than I have had to do in most of my pursuits along these lines. An exercise of the mind, I suppose. Suits me better than crosswords or Sudoku.
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