Navigating the World of NCAA Hockey Rankings: From Polls to NPI

Nearly every Monday morning from late September through mid-April, USCHO.com and USA Hockey Magazine post their weekly college hockey media polls. Understanding the landscape of NCAA hockey rankings requires navigating a complex system involving polls, mathematical formulas, and evolving methods. This article explains the various ranking systems used in college hockey, including the historical Pairwise Rankings, the emerging NPI, and the role of media polls in shaping perceptions and influencing recruiting.

The Allure and Limitations of Media Polls

The USCHO and USA Hockey Magazine polls offer an accessible and easily digestible way for fans to follow the sport. Even if, in any given week, you disagree with the results of the polls, at least you fully understand how they were put together. Their simplicity makes them popular, especially among casual fans. For comparison’s sake, consider men’s college basketball. If you’re a casual fan of that sport, what ranking first comes to mind? The AP Top 25 is likely the answer and that’s undoubtedly where you’re going to go to find out who the #1 team in the country is.

However, these polls are subjective and may not accurately reflect a team's true strength, especially early in the season. For one, the Pairwise isn’t generally a very reliable measuring stick until midseason - usually late November at the very earliest - and that doesn’t satiate most sports fans’ constant hunger to compare their favorite teams to others for the first two or three months of the season.

Despite their limitations in determining NCAA Tournament bids, the polls serve a crucial marketing function. Are NHL media outlets going to stop putting out their weekly power rankings pieces because they have no bearing on the outcome of the season? Are you nuts?? If you want to make the sport more popular, you must capture the attention of as many casual fans as possible. The college hockey establishment understands that. It might be tough for the hardest-core college hockey fans to stomach but there is a difference between what they want in their ideal world (no polls, only math) and the real world where we actually reside. Would it be nice if the college hockey establishment treated the Pairwise with the same reverence as the polls on a weekly basis? Would it be wonderful if teams posted their Pairwise ranking alongside their position in the polls in their weekly graphics? But make no mistake - the polls are not irrelevant.

Recruiting, especially for teams that don’t annually contend for the NCAA Tournament, also relies heavily on the polls. All too often, the college hockey community at large looks at the rankings through the lens of the top contenders, but where the Pairwise Rankings are relevant only for Tournament contenders, the weekly polls are extremely valuable recruiting tools for teams that aren’t always in the Tournament conversation.

The Pairwise Rankings: A Historical Perspective

Unlike many other collegiate sports, Division I college hockey historically relied on a mathematical formula, the Pairwise Rankings, to determine the NCAA Tournament field. The reality of Division I College Hockey is, unlike football, soccer, basketball, volleyball, and most every other collegiate sport, the annual national tournament is not selected by humans. Rather, college hockey’s NCAA Tournament field is selected by a mathematical formula - the Pairwise Rankings (College Hockey News has an excellent primer on the system if you’re new to college hockey or need a refresher on how it all works) - and is not subject to the whims of east coast college hockey journalists who refuse to stay awake long enough to take in NCHC action (it’s like Pac-12 After Dark but on ice).

The Pairwise considered several factors, including:

Winning percentage
Strength of schedule
Home/Road and Overtime Weight
Quality Win Bonus

The Emergence of the NPI: A New Era in College Hockey Rankings

Generally, rules changes in college hockey take place in even year summers, which made it somewhat of a surprise this week when it was mentioned at the AHCA coaching convention in Naples, FL, with NCAA President Charlie Baker, Northeastern AD Jim Madigan, and Hockey East Commissioner Steve Metcalf among the attendees, that the Pairwise was going away. The Pairwise has long been held as the gold standard in college hockey, essentially the highest publicity NCAA team sport that selects teams for its tournament based solely on mathematical record rather than by committee vibes.

The NPI is, at a base level, incredibly similar to RPI and to the old system. There are many sports where the addition of an objective measure is a shock to the system or where the objective measure is a departure from the prior measures. This is not one of them. And the end result is a system that bears a lot of similarities to the one he had already created.

The NPI, or National Performance Indicator, is the new metric adopted by the NCAA to select teams for its tournament. First thing is first, this isn’t a shock. The NCAA D-III Championships Committee recommended using NPI to select participants in team sports last spring, the NCAA began implementing it last fall, and hockey is no exception to the rule, with their mens’s and women’s tournaments both selected using NPI this past spring. The Women’s D-I tournament has already been using NPI as a part of their Pairwise in place of RPI after a trial period, in addition to other sports and divisions who have already started using it. So this has been coming down the pipeline for a while now, and it had already been considered for men’s hockey in previous offseasons, but ultimately pushed back until now.

Read also: Crafting Your NCAA Profile

Like the Pairwise, the NPI incorporates:

Winning percentage. In RPI, this value was worth 25% of a teams calculation.
Strength of schedule. In RPI, strength of schedule was a bane of contention. The remaining 75% of a team’s record was based on 24% strength of opponents and 51% strength of those opponents’ opponents. In default NPI, this is simplified. Strength of schedule is just the NPI rating of the teams you played against, averaged together.
Home/Road and Overtime Weight. You know and love this from Pairwise, and it’s not going anywhere. Currently, a home loss/road win is counted as 1.2 games in the Pairwise, and a home win/road loss is 0.8. Any result that occurs in the 3v3 portion of a game is counted as 2/3 of a win and 1/3 of a loss, while a shootout is a tie. These factors all will still exist in NPI, but the exact values might change, as they have many times in the past.
Quality Win Bonus. This was once again a part of the Pairwise already and is coming back, but in a new way. Previously, a team received bonus RPI for beating a strong opponent, based on team RPI rank. A win over the #1 team in the country received the maximum credit, while beating a team in 20th was worth 1/20 of that credit. Now, the credit will be based on the team’s NPI and how far it is above the baseline for a good team, not their rank. So beating the best team will still give the best credit, while beating any team with a “good” NPI will still give some extra credit. This also allows the system to be more granular, it’s based on your strength, not your rank.
Minimum Countable Wins. This one is new and… you might consider it exciting? It’s really not. You might be familiar with the RPI concept of dropping bad wins. Essentially, if NU plays Stonehill, you expect them to win that game. The math also expects them to win that game. It expects it so much that even if NU does win the game, Stonehill might bring down their strength of schedule so much that they leave the game with a lower RPI than if they hadn’t played at all. That concept still exists with NPI, but it also happens in reverse (Stonehill could lose 20-0 to NU and leave the game with a higher NPI than before.) So to fix that, they just throw out any result that causes either of those things to happen. But at the end of the season, we want to make sure that every team has enough samples going into the math, so if a team has too many wins not counting, some might get added back into the math.

And that’s it. It sounds a lot like the old RPI and Pairwise because it is. The hockey model has been refined a bit and is coming out of our little corner of the NCAA and is spreading to the entire organization. One day, when NPI is just a standard way of doing things, college hockey will be the reason why. Pretty cool.

Flexibility and Potential Adjustments

I said we’d get back to default NPI, and we are. The reason why I called it default NPI is because the sport committee has the power to change the weight of every factor when they implement it. They think strength of schedule should be worth an extra 5%? They can do it. OT wins should be 100%? Sure thing. A quality win should actually be worth double? You bet. The world is their oyster, and reports are that the coaches were presented with a number of different NPI calculations of the 2024-2025 season results, each based on different values being given to each factor. We still don’t know yet what values the committee may decide to change before the season. But at a base level, if they use the same factors that existed in the Pairwise last year, most teams fall in the same spot or within 1 spot of where they were in Pairwise. Personally, I would bet that most things will stay with the same weight they had before, except home/road weight may get a bit closer to baseline. The 20% adjustment has always seemed pretty high.

To clarify further … Committee has a number of different ways the NPI can be calculated. Those "ways" are similar to how Pairwise/RPI can be tweaked … OT weightings, home/road weightings, etc… The underlying "procedure" at the root of NPI doesn't change.

Besides RPI, the other thing going away is the “extra” components of the Pairwise, head to head and record vs. common opponents. This isn’t much of a change. These things still matter, they just matter in that they factor directly into NPI and don’t need to be counted again. These were honestly archaic parts of the Pairwise that served a purpose 20+ years ago but almost never really mattered or changed any team rankings in a meaningful way in recent memory.

RPI: An Early Indicator

As the early season unfolds, many fans of college hockey get very interested in the Rating Percentage Index, or RPI, the system that’s used to determine at-large bids for the NCAA Division I Hockey Tournament. Of course, playoff winners from each of the six major conferences get automatic bids. The other spots in the Big Skate, as well as the seeding of teams in the tournament, are determined by the RPI value for each team. Seeding does get adjusted to avoid regional games between conference rivals and also to minimize travel costs.

The RPI is a system that uses head-to-head results to calculate an index score. Finally, the remaining 54% is based on the winning percentage of your opponents’ competition. There is also a “quality wins bonus” for wins against teams in the top 20.

To start, the Huskies’ winning percentage is 0.500, so they get 0.25 X 0.50 or 0.125 for the first criteria. Currently, Robert Morris has a 3-3 record. Tech gets 0.21 X 0.50 for 0.105. The same is true for Alaska-also 3-3 through the first three weeks. That gives Tech a total of 0.125 + 0.105 + 0.105 of 0.335. The third criterion brings additional complication. Besides their two losses to MTU, RMU swept Bentley and split with Army. Tech, of course, stands at 2-2. Bentley is 1-2, so they sit at .333, while Army is 3-1 for a 0.75 win percentage. Alaska’s opponents include Tech, Denver at 6-0 and Penn State at 5-1. This actually puts Tech in the 8th slot in the nation with an RPI of 0.6800. But don’t get carried away.

The truth is that RPI doesn’t really start to make sense until a good portion of the season has been played.

The Impact of Conference Strength and Scheduling

At the same time, RPI does place a great deal of importance on non-conference games. To start, unless a league does well out of conference, the value of winning and even of losing is reduced greatly once conference play starts. Over the past few seasons, the NCHC has stormed through their non-conference opponents, which has increased the value of every NCHC conference win. For the Old Dog’s taste, that is one of the weaknesses of using a pure “RPI rules all” approach. It’s not just that conference power has a big effect, it’s the fact that most, or even nearly all, non-conference games are played early in the year.

KRACH: An Objective Ranking System

Record vs. The College Hockey News Power Ratings are based upon KRACH, which CHN endorses as the best system to objectively rank teams. Note: The ratings are immediately updated as results come in. St. St. St.

As explained above, KRACH is the implementation of a sophisticated mathematical model known as the Bradley-Terry rating system, first applied to college hockey by a statistician named Ken Butler. The key to understanding KRACH is understanding that it's calculated recursively, so that the end result is self-evident by the results. In other words, if you took one team's schedule to date, and played a theoretical "game" for each game already actually played, using the KRACH ratings themselves in order to predict the winner, then the end result would be a theoretical won-loss percentage that matches the team's actual won-loss percentage. It is not possible to do any better than that with a completely objective method.

Implications of the NPI for Specific Teams

So last but not least, what does this mean for NU? It depends on the factors that the committee ultimately goes with, but at the default values, it looks like a slight disadvantage for NU compared to the current system. The simplification of strength of schedule makes record matter just a little more, so the teams at the top of “bad” conferences like Bentley and Minnesota State will get a bump while teams that finish mid-pack in Hockey East, the Big Ten, or the NCHC will get knocked down a bit. If you want to see a few examples of the math, head on over to BC Interruption, where Grant Salzano broke it down as well and did some base calculations with the factors.

The Ongoing Debate: Subjectivity vs. Objectivity

Hockey is really different in that regard, as some teams get much better and some get much worse from the start to the end of the season. At the NHL level, we often see teams with low seeds either go deep into the playoffs or win the Stanley Cup. The LA Kings were seeded last in the 2012 Cup playoffs, but still hoisted Lord Stanley when the ice chips settled. Last season, the St. Louis Blues overcame a horrendous start to get a mid-level seed but still won the Cup at the end. In that same season, American International, which had never been in an NCAA tournament, managed to win the Atlantic Hockey playoff and grabbed the 16th seed-and then promptly upset #1 overall seed St.

When the NCAA basketball tournament selections are made, RPI is used, but it is not used as a presumably objective tool the way it is in hockey. Would hockey be better or worse using more subjective tools to select teams? The Old Dog thinks it might be a two edged sword because there are tons of controversies in NCAA hockey history from the time before the current RPI system was adopted. At the same time, I’m not really comfortable with games in October having such a major impact. To me, one way around this would be for all of the conferences to schedule so that they have one “open weekend” for their teams in January and possibly February. Still, when it comes to discussing NCAA tournaments, no matter what the sport, any speculation about how tournament teams are selected always creates controversy.

Accounting for Home Ice Advantage

Ice hockey has specific rules to better account for the sport’s quirks and features. Home wins are only worth a 90% weight when calculating that specific game score. Whereas an away win is worth 110% for a win. On the other hand, losing on the road, has 90% of that particular game score, and a home loss is more costly, at 110%. There are no weights applied to neutral-site games. This is obviously acknowledging home ice plays a key role.

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