2000‑01 KRACH Ratings

KRACH is endorsed by College Hockey News as the best system to objectively rank teams. It stands for "Ken's Ratings for American College Hockey", because it was a statistician named Ken Butler who first implemented the methodology for college hockey.

Note: The ratings are immediately updated as results come in. For more, see below the chart or view the FAQ.

Rk Team KRACH Record   Schedule Strength
Rating RRWP Rk W-L-T Pct Ratio Rk SOS
1Michigan State1198.7.8850132-4-4.85005.66714211.5
2St. Cloud State1056.9.8727231-8-1.78753.7067285.2
3Boston College753.4.8353330-8-2.77503.44413218.7
4North Dakota753.1.8352427-7-9.73262.7398274.9
5Colorado College672.1.8211626-12-1.67952.1204317.0
6Minnesota648.9.8167527-12-2.68292.1546301.3
7Wisconsin491.5.778717t21-14-4.58971.4381341.9
8Michigan447.6.7650825-12-5.65481.89711236.0
9Denver372.4.736624t19-15-4.55261.2355301.4
10Providence336.1.72011222-12-5.62821.69018198.9
11Maine322.9.71361519-11-7.60811.55216208.1
12New Hampshire302.9.70291321-12-6.61541.60019189.3
13Northern Michigan260.4.67712118-13-7.56581.30317199.9
14Nebraska-Omaha243.6.66541624-15-3.60711.54531157.7
15Western Michigan237.1.660617t20-13-6.58971.43829164.9
16Minnesota State226.4.65243119-20-1.4875.95110238.1
17Miami214.2.642524t20-16-2.55261.23525173.4
18Mass.-Lowell195.5.62582619-16-3.53951.17128166.9
19Clarkson177.5.60801021-11-3.64291.8003998.6
20Ohio State172.5.60273217-18-2.4865.94723182.0
21St. Lawrence171.7.60191420-12-4.61111.57134109.2
22Boston University165.1.59463914-20-3.4189.72112229.0
23Northeastern150.9.57774013-19-4.4167.71415211.2
24Bowling Green137.0.55953416-19-5.4625.86030159.2
25Merrimack135.6.55773814-20-4.4211.72721186.5
26Michigan Tech128.7.5477558-24-4.2778.3852334.6
27Harvard128.6.54763016-15-2.51521.06232121.0
28Dartmouth120.8.535828t16-14-4.52941.12535107.4
29Cornell119.2.53332216-12-5.56061.2764093.5
30Alaska-Anchorage116.4.5288567-24-5.2639.3583324.8
31Ferris State116.0.52814213-20-5.4079.68926168.4
32Lake Superior103.4.506448t13-23-0.3611.56522183.0
33Rensselaer100.8.501428t17-15-2.52941.1254289.6
34Notre Dame95.9.49215110-22-7.3462.52924181.1
35Alaska-Fairbanks95.1.490448t9-19-8.3611.56527168.2
36Alabama-Huntsville93.8.48801121-12-1.63241.7204654.5
37Yale93.8.48783314-16-1.4677.87936106.7
38Vermont79.2.45623614-18-2.4412.78938100.3
39Massachusetts78.6.4549538-22-4.2941.41720188.7
40Minnesota-Duluth76.2.4490577-28-4.2308.3009253.9
41Princeton68.7.43014310-16-5.4032.67637101.7
42Union60.0.40554112-18-4.4118.7004385.7
43Colgate50.7.37595010-20-4.3529.5454193.0
44Niagara42.8.34673714-19-5.4342.7674555.7
45Wayne State40.8.33862318-14-3.55711.2584932.4
46Mercyhurst34.8.3130722-11-2.65711.9175118.2
47Quinnipiac34.4.3113922-11-4.64861.8465018.6
48Brown30.3.2915594-21-4.2069.26133116.3
49Findlay29.8.2888459-15-2.3846.6254747.7
50Air Force27.6.27723513-16-4.4545.8334833.1
51Iona23.1.25172018-13-4.57141.3335217.3
52Canisius22.1.24521917-12-4.57581.3575316.3
53Bemidji State21.3.2403586-26-4.2222.2864474.5
54Sacred Heart13.8.18552714-12-5.53231.1385812.1
55Connecticut10.1.15184412-19-4.4000.6675415.1
56Army7.9.128946t12-20-0.3750.6005513.2
57Fairfield6.8.115546t11-19-2.3750.6005911.3
58American Int'l6.3.10925210-20-1.3387.5125712.3
59Holy Cross5.0.0915548-22-2.2812.3915612.7
60Bentley2.2.0453604-23-2.1724.2086010.5
RRWPRound Robin Winning Percentage. A team's theoretical winning percentage would be if you played every other team, one time each.
RatioThe Ratio of wins to losses (as opposed to Win %, which is wins divided by games).
SOSStrength of Schedule

Note: For the purposes of NCAA eligibility (and therefore KRACH), a team's record is based only on games against other Division I hockey schools which are eligible for the NCAA Tournament.

KRACH Explained

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. While the model is sophisticated, and needs a computer to calculate, its essential meaning is actually quite simple.

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. Pretty cool.

It is not possible to do any better than that with a completely objective method. Any other method introduces arbitrary-ness and/or subjectivity.

(See the FAQ for a more complete explanation.)

More detailed explanations of the KRACH ratings can be found under the following links

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