2017‑18 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
1St. Cloud State519.1.8182320-6-4.73332.7504188.8
2Cornell512.9.8165122-3-2.85195.7503789.2
3Notre Dame439.3.7935422-8-2.71882.5568171.9
4Denver349.2.75628t17-7-6.66672.0007174.6
5Minnesota State347.9.7556225-7-0.78123.5712897.4
6Ohio State306.8.73355t19-8-5.67192.04813149.8
7Minnesota290.1.72331419-13-2.58821.4291203.1
8Clarkson229.8.67885t19-8-5.67192.04819112.2
9Minnesota-Duluth227.7.676920t16-13-3.54691.2075188.6
10North Dakota210.2.660916t14-10-8.56251.28612163.5
11Nebraska-Omaha208.0.65882615-14-1.51671.0693194.6
12Michigan205.7.656520t16-13-3.54691.2079170.4
13Providence193.9.64448t20-9-4.66672.0002997.0
14Northeastern184.2.63375t19-8-5.67192.0483690.0
15Western Michigan177.4.625728t14-14-2.50001.0006177.4
16Penn State158.2.60132714-13-5.51561.06514148.6
17Wisconsin156.2.598733t14-15-4.4848.94111166.0
18Bowling Green153.9.59541019-9-6.64711.8334184.0
19Boston College150.7.590920t16-13-3.54691.20716124.9
20Boston University149.7.589420t16-13-3.54691.20717124.0
21Union142.5.57871220-13-1.60291.5193293.9
22Northern Michigan138.0.57171120-11-3.63241.7204380.3
23Harvard136.9.56991913-10-4.55561.25020109.5
24Colorado College135.1.566928t13-13-4.50001.00015135.1
25Miami122.6.54554910-17-3.3833.6222197.3
26Maine120.3.541316t16-12-4.56251.2863493.6
27Michigan State100.5.501050t11-19-2.3750.60010167.4
28Bemidji State99.1.49791516-11-7.57351.3454773.7
29Mass.-Lowell99.0.497828t16-16-0.50001.0002799.0
30Yale98.3.49622414-12-1.53701.1604084.7
31Princeton96.5.492128t12-12-3.50001.0003096.5
32Connecticut95.5.489833t15-16-2.4848.94123101.5
33Dartmouth92.8.48333712-13-2.4815.9292599.9
34Mercyhurst85.8.46591317-11-4.59381.4625858.7
35Quinnipiac83.6.460039t13-15-4.4688.8823194.8
36Michigan Tech83.1.45852516-14-5.52861.1214674.1
37Massachusetts80.2.450842t13-17-2.4375.77822103.1
38Colgate79.7.44953513-14-5.4844.9393984.9
39Air Force73.0.42981817-13-4.55881.2675957.6
40New Hampshire64.1.401644t10-16-6.4062.6843393.7
41Merrimack63.5.3996539-18-4.3548.55018115.5
42Vermont62.1.394650t9-17-6.3750.60021103.5
43Canisius61.4.392328t15-15-2.50001.0005561.4
44Army55.9.37243612-13-6.4839.9385659.7
45RIT55.0.368739t14-16-2.4688.8825462.3
46Holy Cross50.5.35103812-14-7.4697.8866057.0
47Robert Morris49.9.348342t13-17-2.4375.7785364.1
48Bentley49.6.34744112-15-6.4545.8335759.6
49Ferris State47.6.33875212-21-1.3676.5814281.8
50Sacred Heart45.3.328844t11-17-4.4062.6845066.2
51Alaska44.8.326747t11-18-3.3906.6414969.9
52Arizona State44.6.3258568-19-5.3281.4883591.4
53American Int'l43.9.322544t11-17-4.4062.6845264.2
54Alabama-Huntsville41.5.31125510-20-2.3438.5244479.1
55Niagara41.2.309847t11-18-3.3906.6415164.2
56Lake Superior39.6.30225410-20-4.3529.5454872.6
57Brown36.1.2846576-17-4.2963.4213885.7
58St. Lawrence33.3.2698587-23-2.2500.3332499.9
59Rensselaer27.9.2387595-23-4.2188.2802699.7
60Alaska-Anchorage10.7.1107602-26-4.1250.1434574.9
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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