2012-2013 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 | Sched Strength | |||||
|---|---|---|---|---|---|---|---|---|---|
| Rating | RRWP | Rk | W-L-T | Pct | Ratio | Rk | SOS | ||
| 1 | Minnesota | 339.3 | .7579 | 2 | 26-8-5 | .7308 | 2.714 | 18 | 125.0 |
| 2 | Quinnipiac | 339.1 | .7578 | 1 | 27-7-5 | .7564 | 3.105 | 39 | 109.2 |
| 3 | Mass.-Lowell | 273.9 | .7184 | 3 | 26-10-2 | .7105 | 2.455 | 37 | 111.6 |
| 4 | Notre Dame | 239.4 | .6920 | 5t | 25-12-3 | .6625 | 1.963 | 22 | 122.0 |
| 5 | Minnesota State | 228.1 | .6822 | 8 | 24-13-3 | .6375 | 1.759 | 10 | 129.7 |
| 6 | Miami | 226.5 | .6807 | 5t | 24-11-5 | .6625 | 1.963 | 31 | 115.4 |
| 7 | Boston College | 217.4 | .6723 | 7 | 22-11-4 | .6486 | 1.846 | 27 | 117.7 |
| 8 | North Dakota | 215.4 | .6704 | 11 | 21-12-7 | .6125 | 1.581 | 5 | 136.3 |
| 9 | Denver | 213.5 | .6685 | 15 | 20-13-5 | .5921 | 1.452 | 2 | 147.1 |
| 10 | Wisconsin | 209.0 | .6641 | 9 | 22-12-7 | .6220 | 1.645 | 14 | 127.0 |
| 11 | New Hampshire | 199.0 | .6537 | 12 | 19-11-7 | .6081 | 1.552 | 13 | 128.2 |
| 12 | St. Cloud State | 195.5 | .6500 | 14 | 23-15-1 | .6026 | 1.516 | 12 | 128.9 |
| 13 | Yale | 177.6 | .6294 | 16 | 18-12-3 | .5909 | 1.444 | 21 | 122.9 |
| 14 | Union | 172.7 | .6233 | 10 | 21-12-5 | .6184 | 1.621 | 40 | 106.6 |
| 15 | Western Michigan | 171.8 | .6221 | 13 | 19-11-8 | .6053 | 1.533 | 36 | 112.0 |
| 16 | Boston University | 162.2 | .6095 | 20 | 21-16-2 | .5641 | 1.294 | 16 | 125.3 |
| 17 | Providence | 160.2 | .6068 | 23 | 17-14-7 | .5395 | 1.171 | 4 | 136.8 |
| 18 | Rensselaer | 150.6 | .5931 | 21t | 18-14-5 | .5541 | 1.242 | 24 | 121.2 |
| 19 | Colorado College | 145.6 | .5854 | 32 | 18-19-5 | .4881 | .953 | 1 | 152.7 |
| 20 | Brown | 126.8 | .5542 | 24 | 16-14-6 | .5278 | 1.118 | 34 | 113.4 |
| 21 | Niagara | 126.4 | .5535 | 4 | 23-9-5 | .6892 | 2.217 | 53 | 57.0 |
| 22 | Nebraska-Omaha | 123.8 | .5489 | 29 | 19-18-2 | .5128 | 1.053 | 28 | 117.6 |
| 23 | Cornell | 122.3 | .5460 | 35 | 15-16-3 | .4853 | .943 | 9 | 129.7 |
| 24 | Dartmouth | 121.1 | .5438 | 27 | 15-14-5 | .5147 | 1.061 | 33 | 114.2 |
| 25 | Ohio State | 120.2 | .5421 | 33t | 16-17-7 | .4875 | .951 | 15 | 126.4 |
| 26 | Alaska-Fairbanks | 117.1 | .5360 | 28 | 17-16-4 | .5135 | 1.056 | 38 | 110.9 |
| 27 | Ferris State | 116.9 | .5357 | 31 | 16-16-5 | .5000 | 1.000 | 29 | 116.9 |
| 28 | Michigan | 114.3 | .5307 | 33t | 18-19-3 | .4875 | .951 | 25 | 120.2 |
| 29 | St. Lawrence | 110.6 | .5230 | 25 | 18-16-4 | .5263 | 1.111 | 45 | 99.5 |
| 30 | Northern Michigan | 104.5 | .5100 | 40 | 15-19-4 | .4474 | .810 | 11 | 129.0 |
| 31 | Merrimack | 102.0 | .5045 | 37 | 15-17-6 | .4737 | .900 | 35 | 113.3 |
| 32 | Bowling Green | 92.3 | .4817 | 44 | 15-21-5 | .4268 | .745 | 19 | 124.0 |
| 33 | Minnesota-Duluth | 87.8 | .4704 | 42 | 14-19-5 | .4342 | .767 | 32 | 114.4 |
| 34 | Lake Superior | 86.7 | .4675 | 39 | 17-21-1 | .4487 | .814 | 42 | 106.6 |
| 35 | Michigan Tech | 85.3 | .4637 | 45 | 13-20-4 | .4054 | .682 | 17 | 125.1 |
| 36 | Colgate | 84.6 | .4618 | 41 | 14-18-4 | .4444 | .800 | 43 | 105.7 |
| 37 | Vermont | 83.4 | .4588 | 49 | 11-19-6 | .3889 | .636 | 8 | 131.1 |
| 38 | Robert Morris | 83.3 | .4583 | 18 | 20-14-4 | .5789 | 1.375 | 49 | 60.6 |
| 39 | Massachusetts | 80.3 | .4501 | 47 | 12-19-3 | .3971 | .659 | 23 | 121.9 |
| 40 | Maine | 80.2 | .4499 | 48 | 11-19-8 | .3947 | .652 | 20 | 123.0 |
| 41 | Michigan State | 77.6 | .4424 | 51 | 14-25-3 | .3690 | .585 | 6 | 132.6 |
| 42 | Holy Cross | 77.0 | .4406 | 17 | 20-14-3 | .5811 | 1.387 | 55 | 55.5 |
| 43 | Connecticut | 74.5 | .4332 | 19 | 19-14-4 | .5676 | 1.312 | 54 | 56.7 |
| 44 | Air Force | 73.4 | .4301 | 21t | 17-13-7 | .5541 | 1.242 | 52 | 59.1 |
| 45 | Princeton | 72.0 | .4257 | 46 | 10-16-5 | .4032 | .676 | 41 | 106.6 |
| 46 | Harvard | 66.5 | .4082 | 52 | 10-19-3 | .3594 | .561 | 26 | 118.6 |
| 47 | Mercyhurst | 66.0 | .4064 | 26 | 19-17-5 | .5244 | 1.103 | 51 | 59.8 |
| 48 | Canisius | 65.4 | .4046 | 30 | 19-18-5 | .5119 | 1.049 | 47 | 62.4 |
| 49 | Clarkson | 62.1 | .3932 | 53 | 9-20-7 | .3472 | .532 | 30 | 116.7 |
| 50 | Penn State | 55.9 | .3708 | 36 | 11-12-0 | .4783 | .917 | 48 | 61.0 |
| 51 | RIT | 51.6 | .3540 | 38 | 15-18-5 | .4605 | .854 | 50 | 60.5 |
| 52 | Bemidji State | 50.7 | .3501 | 56 | 6-22-8 | .2778 | .385 | 7 | 131.7 |
| 53 | Northeastern | 49.8 | .3467 | 54 | 9-21-4 | .3235 | .478 | 44 | 104.1 |
| 54 | Alaska-Anchorage | 38.5 | .2959 | 57 | 4-25-7 | .2083 | .263 | 3 | 146.4 |
| 55 | American Int'l | 36.4 | .2852 | 43 | 12-17-6 | .4286 | .750 | 58 | 48.5 |
| 56 | Bentley | 30.2 | .2520 | 50 | 12-20-3 | .3857 | .628 | 59 | 48.1 |
| 57 | Army | 19.3 | .1834 | 55 | 7-22-5 | .2794 | .388 | 57 | 49.9 |
| 58 | Sacred Heart | 6.8 | .0774 | 58 | 2-30-4 | .1111 | .125 | 56 | 54.5 |
| 59 | Alabama-Huntsville | 6.3 | .0719 | 59 | 1-20-1 | .0682 | .073 | 46 | 85.9 |
| RRWP | Round Robin Winning Percentage. A team's theoretical winning percentage would be if you played every other team, one time each. |
| Ratio | The Ratio of wins to losses (as opposed to Win %, which is wins divided by games). |
| SOS | Strength 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


NCAA Tournament Info