2016‑17 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
1Denver644.6.8386224-6-4.76473.2506198.3
2Minnesota-Duluth582.9.8254320-5-7.73442.7655210.8
3Harvard467.9.7941122-5-2.79313.83322122.1
4Western Michigan354.2.74981019-8-5.67192.0488173.0
5Minnesota334.1.7399821-9-2.68752.20011151.9
6Mass.-Lowell325.4.7353722-9-3.69122.23812145.4
7Boston University321.1.733011t21-10-3.66181.9579164.1
8Union275.3.7054423-8-3.72062.57934106.7
9Cornell273.8.7045518-6-5.70692.41227113.5
10Providence272.4.703511t20-9-5.66181.95715139.2
11Penn State267.2.7000620-8-2.70002.33326114.5
12Notre Dame243.0.68211319-10-5.63241.72014141.3
13North Dakota238.3.67842816-14-3.53031.1294211.0
14Vermont218.7.66191918-11-5.60291.51913144.0
15Nebraska-Omaha218.1.661426t16-13-5.54411.1947182.7
16Wisconsin212.7.65641818-11-1.61671.60917132.2
17St. Cloud State202.8.64703415-16-1.4844.9393215.9
18Boston College196.6.64092518-14-4.55561.25010157.3
19Ohio State191.7.635914t17-9-6.62501.66725115.0
20St. Lawrence174.8.61722216-11-7.57351.34520130.0
21Northeastern160.8.600126t16-13-5.54411.19416134.7
22Quinnipiac157.1.59542119-13-2.58821.42931110.0
23Miami142.5.5749469-16-7.3906.6412222.2
24Air Force140.3.5718922-9-5.68062.1304265.9
25Clarkson136.5.566029t15-14-5.51471.06121128.7
26Merrimack130.6.556731t14-14-6.50001.00019130.6
27Bemidji State108.2.51682020-13-3.59721.4834073.0
28Minnesota State105.9.512216t19-11-4.61761.6154365.6
29Princeton104.8.510131t13-13-3.50001.00035104.8
30Connecticut98.1.49583512-14-8.4706.88930110.3
31Yale98.0.49563611-13-5.4655.87128112.5
32Canisius95.0.489114t19-10-7.62501.6675057.0
33Colorado College88.0.4728557-21-4.2812.3911224.9
34Robert Morris87.6.472016t19-11-4.61761.6155554.3
35Michigan Tech84.6.46452318-13-7.56581.3034465.0
36New Hampshire81.3.456038t12-17-5.4265.74432109.3
37Michigan73.1.43364810-17-3.3833.62223117.6
38Dartmouth70.2.42514510-16-3.3966.65733106.8
39Army65.2.40982416-12-5.56061.2765751.1
40Maine63.5.40424911-19-4.3824.61936102.5
41Bowling Green59.3.390231t17-17-2.50001.0004959.3
42Holy Cross54.2.371929t14-13-7.51471.0615851.1
43Arizona State52.0.3639528-19-3.3167.46329112.2
44Colgate48.8.3514518-20-6.3235.47837102.1
45Bentley48.0.348038t11-16-7.4265.7444564.6
46Sacred Heart45.9.339538t12-17-5.4265.7444761.8
47Ferris State43.7.32963713-17-5.4429.7955354.9
48Michigan State43.6.3295566-21-3.2500.33318130.9
49Northern Michigan42.7.32534712-20-4.3889.6364167.1
50RIT41.5.31994413-20-1.3971.6594663.0
51Lake Superior39.2.309538t11-16-7.4265.7445652.8
52Alaska38.8.307542t12-18-4.4118.7005255.5
53Mercyhurst35.6.291842t12-18-4.4118.7005950.9
54Rensselaer29.7.2600578-26-1.2429.3213992.7
55American Int'l26.6.2414508-18-8.3529.5456048.8
56Alaska-Anchorage25.5.2344547-21-6.2941.4174861.2
57Massachusetts24.7.2292585-27-2.1765.21424115.1
58Alabama-Huntsville24.3.2266539-22-3.3088.4475454.3
59Brown20.1.1980594-23-2.1724.2083896.4
60Niagara8.5.0990603-28-3.1324.1535156.0
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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