Category Archives: 2016-17

2016-17 Week 1 BELOW Rating

Week 1 BELOW for the 2016-17 WCHA Regular Season

2016-17 BELOW, Week 1

TeamWk0Wk1+/-Wk1 EWPRank
7-MTU16431643069.49%2(t) - 0
8-MSU16041604064.54%2(t) - 0
4-BGSU15831583061.72%2(t) - 0
3-BSU15371537055.30%2(t) - 0
9-NMU15001500050.00%2(t) - 0
6-LSSU14751475046.41%2(t) - 0
5-FSU15181469-4945.55%10 - 0
2-UAF14671467045.27%2(t) - 0
0-UAH14071456+4943.70%1 - 6
1-UAA13861386034.16%2(t) - 0

The Results

Well, sometimes that 9.2% shot happens.  The news of the WCHA this week — the only news, but big news nonetheless — is that the Alabama-Huntsville Chargers, who’ve never finished higher than 8th in the league in their three seasons in the WCHA, went out and swept USCHO #20 Ferris State 2-1, 4-3 on Saturday and Sunday.  UAH hadn’t won their first two games of the season since 2001-02 (my senior year at UAH).  It was the Chargers’ second WCHA sweep and first-ever sweep of a ranked opponent.

The BELOW Rating Impact

Yes, yes, I hold an engineering degree from UAH, so this is special to me.  But we also see that it’s big for BELOW, as the pre-season gap in BELOW — 111 points — had every expectation that the Bulldogs would win at least one, and likely both, games this weekend, with an expected winning percentage of 64.5% in their first matchup.  That just didn’t happen.

As a result, the Chargers pick up 49 points in BELOW and now just barely trail the Bulldogs, 1469-1456, in that rating.  UAH jumps from a distant 9th to a close one and is within striking distance of 5th with a good weekend against Michigan Tech.

It’s important to note that this change would still mean that UAH would only be expected to win ~44% of its matches against a league-average (BELOW 1500) opponent, compared to ~37% with last week’s rating.  BELOW now thinks that UAH is merely mediocre and not bad.

Coming Up

This week’s matches should really move the needle, as Bowling Green travels to Bemidji State and Michigan Tech travels to Minnesota State.  I will have those projections later this week.

2016-17 Week 1 ABOVE Predictions

It’s October!  It’s my birthday!  It’s time for hockey!  IT’S TIME FOR NUMBERS!

I won’t bury the lede here: in a 1,000,000-trial Monte Carlo simulation, FSU sweeps about 23.5% of the time, UAH sweeps about 11.6% of the time, and the rest falls in between.  My model is still a work in progress (mainly in the data-management side; the calculations are easy), but it’s pretty simple.

Event% Chances
FSU Sweeps16.5%
UAH Sweeps9.2%
New OT Involved20%

How I get to these numbers – it starts with BELOW

BELOW stands for Bringing Elo to the WCHA.   Elo-style rating systems work on a simple principle: you can go into a match with an estimate for the likelihood that contestant A will win, known as an expected value.  If contestant A wins, they are rewarded with a jump in their rating commensurate with the expected value.  If contestant A had a high expected value, they won’t receive much of a change.

Conversely, contestant B could pull off the upset, and an Elo rating system will reward them for that.  I explained this moderately well in December, and I’ll be refining that soon.  If you’re new here, this is where you should go.

How we got here – re-calculating BELOW

Ferris State, despite all the wonder that it did through the postseason, starts the 2016-17 season with a BELOW rating of 1518, or just a hair above an average baseline of 1500.  Alabama-Huntsville comes in at 1407.  Both teams have been regressed to the mean. by one-third; UAH, since they were farther from 1500 (1361) than the Bulldogs (1527), moved closer.

Introducing ABOVE

ABOVE is Adusting BELOW through Operative Value Experiments, the model that uses that Elo-style rating and iterates, time after time.  This used to be pretty easy, actually: in the regular season, you would win, lose, or tie; now you can win, win in 5×5 overtime, win in 3×3 overtime, or win in a shootout.  I used to assign a different value adjustment based on whether a non-tie was settled in OT, but I didn’t predict those on a macro level.

I actually am predicting 16 outcomes per weekend: two combinations of four results: win, overtime win, overtime loss, and loss by team A.  I could spit that data out at you, because to ABOVE, it actually matters whether Game #001 is a UAH win even if it’s a given that Game #002 is an FSU win.  It doesn’t matter to you.

A brief sidebar as to why it does matter to ABOVE

Think about it, though: if a team with a 1400 ranking beats a team with a 1500 ranking — pretty close to where Ferris-Huntsville is — a split will move the teams closer, but order matters.  To our example: a 100-point differential means that team A is expected to win 64% of the time.  An upset means that team B get 0.64 x 40 = 25.6 points, and the spread is now 1474 – 1426; this ELO Difference Calculator will show that the expected win for team A is now just 57%.  But if the reverse happens, and FSU wins first, the gulf is wider between the two teams, and the value of an upset is greater.  We saw this last season also with Ferris State opening.

In short, a split does not mean that ABOVE will calculate the same BELOW regardless of order.

Say, when do we get that model?

Well, there are two things at work:

  1. I’m flying back today after 12 nights in Iceland.  I haven’t had a chance to work on it while I’ve been here.
  2. I’m not sure yet how I want to model the new overtime.

New overtime

Now, the new OT is weird.  How do you model 3×3?  You can do it two ways:

  1. It’s a crapshoot, so model it as 50-50 and go on with life.
  2. Do some guessing based on GF/GA differential or something silly like that.

There’s also the question of how often teams will push to go into the extended overtime.  My current assumption in ABOVE is, “It’ll be like last year,” but I kinda doubt that.  A weaker team is unlikely to have the skaters to win in 3×3 or in a shootout, and they may see the prospect of getting three points greater than playing for just one.  We don’t know yet!  So I’m trying to go with what makes sense for now, and that’s just … not yet done.


Please leave a comment below or hit me on Twitter @wchaplayoffs.  Today is a travel day for me — KEF to BOS — but I’ll see stuff as I have time.

Say Goodbye to the Western Tie

College hockey was the lone stronghold in the Ties Are Okay part of hockey, but those days are ending, and the WCHA has done their part, announcing today that ties in conference games are a thing of the past.  The 2-1-0 scoring structure is gone, and the 3-2-1-0 structure has arrived.  In short:

  • WCHA teams will play 5×5 for 60:00.  The winner will get 3 points.
  • Teams winning in a 5:00, 5×5 overtime will get a full 3-point win.
  • Teams winning in a subsequent 5:00, 3×3 overtime or a subsequent shootout will get 2 points, with the losing team gaining 1 point.
  • WCHA nets will be shallower — 40″, meeting the NHL standard — than the 44″ standard.

Since the new WCHA was formed in 2013-14, there have been 420 league games.  There were 12 ties in 2013-14, 12 in 2014-15, and 20 in 2015-16.  Even as much as everyone — including me! — made light of ties in the WCHA last year the tie rate faded as the season went on.

I’ll have more on this as the season goes by — this change this close to the season is pretty much submarining my chance of having a public model on October 1.  But here are my preliminary thoughts:

  • I have generally modeled overtime by looking at the amount of overtime to-date in the season (and in the past season if it’s early).  This has been a pretty good model, because the rate of overtime games is roughly even for the fact that we only have 140 games as samples.  (I could model this as a Poisson distribution, but I have better things to do with my time.)
  • I think that I’ll keep that model going forward, using overtime games from the past 140 matches as the basis for whether a game will play past 65:00.  Why?  The incentive is there for the weaker team to hold on for a single point, even if the opponent will get two.
  • After 65:00, it will be something like a coin flip, whether 50-50 or weighted by a goals-for ratio between the two teams.  Example: for those two late-season Mankato-Huntsville ties, I’d do a coin that’s weighted 82/61 between the two teams to determine a winner.
  • The frustration about this is going to be that you’ll have to keep a track of when goals are scored and games are won all season long to figure out which teams are better in a BELOW sense.  I’m going to treat a tie just like I did before and then have a follow-on kabuki dance where we come up with a winner.  While this matters for the standings that a BELOW-based model will output, it won’t matter in terms of BELOW thinking which team is better — i.e., it won’t matter who gets to break a 65:00 tie, much less how they break it.

If you have ideas or questions, leave a comment here or reply to me at @wchaplayoffs on Twitter.

Looking Back: Would Michigan Tech have made the 2016 NCAAs?

In light of everything with the new WCHA playoff system, I had a lingering question: What effect would the semifinal rules have had on Michigan Tech’s chances of making the NCAAs as an at-large team?

Luckily, I knew the guy to ask: Tim Braun of  His answer:

Michigan Tech would still need to win the Title to get in…even sweeping FSU at home and losing to MSU in Houghton would have MTU first team out.

[T]hey’d pickup almost 40 RPI points, enough to pass Cornell, but not UMD…that would get them to 0.5398 (UMD was up at 0.5440).

The new, truly-insular schedule for 2016-17 will make it hard for WCHA teams to make the NCAAs.  WCHA teams play just 32% of their non-conference games at home this season (39% if you count the Alaska tournaments) per’s Michael Napier.  It’s no wonder that the WCHA is looking to reduce the number of league games to give member schools more opportunities to play out-of-conference.  The WCHA’s woeful non-conference totals in 2015-16 — tabulated by Troy Mills of the Beaver Hockey Pond — tells the sad tale of woe:

The WCHA non-conference schedule is complete and the league ended up with a record of 27-36-9.

-5 against Hockey East (3-2-0)
-4 against Atlantic Hockey (3-0-1)
-26 against the NCHC (4-20-2)
-24 against the Big10 (10-9-5)
-7 against the ECAC (4-2-1)
-6 against Arizona State (3-3-0)

It’s the NCHC play that killed the league.  Four teams from the Nacho made the NCAAs, and the results weren’t pretty:

  • UAH went 0-2-0 against eventual national champion North Dakota, although one of those games was 1-0, and split with Colorado College.
  • UAA lost to St. Cloud.
  • UAF also lost to St. Cloud.
  • BSU went 2-0-0 against Duluth, 0-1-1 against North Dakota, and lost to St. Cloud.
  • BGSU lost two games each to Miami and Western Michigan, a fact that probably rankles our friends at
  • FSU went 0-1-1 against Western.
  • LSSU lost to North Dakota, and they sadly got swept at home by newbie Arizona State.
  • MTU didn’t play any NCHC teams, and their big regrets are in conference play.
  • MSU lost three games to St. Cloud and two to Nebraska-Omaha.
  • NMU split with Duluth.

One way to consider the new playoff structure — which I like a lot! — is that playing two or three semifinal games will lower the chance of upsets.  While that lowers the probability of hurting a league team in PWR — again, it kept Tech out in 2016 — Ferris State made the 2014 NCAA field as an at-large despite losing the Broadmoor to Minnesota State.

I hope to have answers on the probabilities for the 2016 semifinals and final game in the next week or so.  But there’s also …

[My thanks to jsmithe for correcting my oversight of LSSU playing NoDak early in the season.]

The New WCHA Playoffs and WCHA Championship

The WCHA announced on Tuesday that they will move to a new on-campus playoff/tournament solution to determine the postseason champion.  The quarterfinals and semifinals will be best-of-three, hosted by the better seeds at each round.  The final game for the Broadmoor Trophy and the league’s automatic qualifier will be hosted by the highest remaining seed on the final weekend prior to NCAA play.

The turn from playoff to tournament at the end is a little interesting, but it makes sense.  A team playing best-of-three two weekends in a row could easily play seven postseason games in 15 days and be at 40+ games before the NCAAs roll around.  That’s a pretty tough task, especially considering that everyone will play games the final two regular season weekends, putting the toll at 11 games in the final month of competition.

That said, the single-game championship feels like a bit of a miss for the league.  I am aware that this comes because league members are keeping at 28 conference games, which means that the league’s regular season will always run to the second weekend in March.  WCHA Commissioner Bill Robertson said on Tuesday that the league will go to 26 or maybe even 24 games in 2017-18.  Keeping the travel down should a #5 or lower seed make the finale is a priority.

I have this idea in my head that I’ll run probabilities for a re-run of the 2016 postseason under the new format.  For example, what are the vanishingly small chances that Lake Superior would’ve hosted Alaska for a single-game championship?  I’d put that at 0.05% or less.  Similarly, what are the chances that Ferris State would’ve won a best-of-three with Michigan Tech and then won a one-game playoff at either Mankato or Bowling Green?  Remember that the first round went chalk this year, and Ferris State’s chances of winning the Broadmoor at the Final Five were just 12%.  It’s an interesting thought exercise and will be a good use of my in-progress tool.

I’m in favor of the changes on the whole.  The Final Five concept was dead, and this was an admission of that fact.  It’s an exciting new concept for a new WCHA, and I welcome the change.

2016 Offseason Conditioning Workouts, Post #1

I was digging through the site for something completely unrelated the other day when I came across Using KRACH, recency, and goal differential for next season and realized that I have, essentially, what I wanted then in BELOW now.  Let me talk about that a little.

  1. Using KRACH wasn’t an easy task.  I never did finish that math major, so I don’t have a great handle on building an algorithm that uses a Bradley-Terry method.  Before you glaze over on me: essentially, B-T methods note that not everyone plays everyone (or more appropriately that all network nodes have interactions with all other network nodes).  An Elo-based algorithm isn’t bound (as much) by that, although it certainly works better when all opponents have played each other.  A hockey-wide Elo algorithm may not make sense.
  2. An Elo-based algorithm has an eye for recency.  Alabama-Huntsville’s end-of-season results with Minnesota State and Bowling Green may have indicated that those two road teams were not as strong as BELOW would have thought them to be (or, alternately, that UAH wasn’t as bad as they appeared to be).  The top KRACH of the 2015-16 season was Minnesota State back in early November  (1744), but it’s Michigan Tech’s strong run to the end that shows the value of recency.  A “big win” back in the pack doesn’t help you much in the long run — ask Ferris State, which got above 1500 (where they never fell below again) with that 7-4 upset of the Mavs, but their more recent work in pulling into the home ice tussle was mediocre, going 1-3-0 down the stretch.  BELOW responded, but … single-game elimination is still a crap shoot, and I had Ferris State winning the Broadmoor 41.5% of the time on the morning of the final, a far sight better than the 12% overall shot I gave them to win the Final 4ive.
  3. I covered goal differential back in January, and my thoughts there still stand.  I’m going to look at modeling 2+ goal differentials by looking at empty-net goals (and all removing all of them), but I don’t think that we can ignore three-goal margins completely.  Say what you will about the 2-2 (OT) WCHA in 2015-16, but there were 42 WCHA games scored by three or more goals.

Essentially, BELOW is what I was looking for a year ago (and two years ago when I wrote this post).  I’m about 25% of the way to a prototype for making model runs.  I hope to have it available for the start of the season.