2011-2012 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-Duluth | 351.0 | .7511 | 1 | 18-5-4 | .7407 | 2.857 | 28 | 122.8 |
| 2 | Boston University | 340.1 | .7456 | 5T | 16-8-1 | .6600 | 1.941 | 11 | 175.2 |
| 3 | Michigan | 320.9 | .7354 | 9 | 16-9-4 | .6207 | 1.636 | 5 | 196.1 |
| 4 | Boston College | 315.7 | .7325 | 13T | 16-10-1 | .6111 | 1.571 | 2 | 200.9 |
| 5 | Mass.-Lowell | 307.2 | .7276 | 2 | 17-7-0 | .7083 | 2.429 | 25 | 126.5 |
| 6 | Notre Dame | 304.5 | .7260 | 16 | 16-10-3 | .6034 | 1.522 | 3 | 200.1 |
| 7 | Ferris State | 291.6 | .7182 | 7 | 17-8-4 | .6552 | 1.900 | 17 | 153.5 |
| 8 | Maine | 281.9 | .7119 | 8 | 15-8-3 | .6346 | 1.737 | 14 | 162.3 |
| 9 | Minnesota | 257.0 | .6946 | 4 | 19-9-1 | .6724 | 2.053 | 27 | 125.2 |
| 10 | Northern Michigan | 255.5 | .6934 | 23 | 12-9-6 | .5556 | 1.250 | 1 | 204.4 |
| 11 | Ohio State | 253.4 | .6919 | 18 | 14-9-5 | .5893 | 1.435 | 9 | 176.6 |
| 12 | Merrimack | 246.1 | .6863 | 5T | 14-6-5 | .6600 | 1.941 | 24 | 126.8 |
| 13 | Michigan State | 242.8 | .6837 | 24T | 14-11-4 | .5517 | 1.231 | 4 | 197.3 |
| 14 | Miami | 239.7 | .6812 | 24T | 15-12-2 | .5517 | 1.231 | 6 | 194.7 |
| 15 | Western Michigan | 232.2 | .6750 | 22 | 14-10-5 | .5690 | 1.320 | 10 | 175.9 |
| 16 | North Dakota | 208.4 | .6536 | 17 | 15-10-2 | .5926 | 1.455 | 18 | 143.3 |
| 17 | Lake Superior | 196.9 | .6422 | 27 | 14-11-5 | .5500 | 1.222 | 15 | 161.1 |
| 18 | Colorado College | 195.1 | .6404 | 10 | 15-9-1 | .6200 | 1.632 | 30 | 119.6 |
| 19 | Denver | 192.4 | .6376 | 13T | 15-9-3 | .6111 | 1.571 | 29 | 122.5 |
| 20 | Northeastern | 180.6 | .6247 | 32T | 11-11-3 | .5000 | 1.000 | 8 | 180.6 |
| 21 | Union | 174.7 | .6178 | 3 | 16-6-6 | .6786 | 2.111 | 40 | 82.7 |
| 22 | Cornell | 139.1 | .5702 | 12 | 11-6-5 | .6136 | 1.588 | 37 | 87.6 |
| 23 | Bemidji State | 132.9 | .5605 | 32T | 12-12-3 | .5000 | 1.000 | 22 | 132.9 |
| 24 | St. Cloud State | 128.5 | .5533 | 41 | 11-14-4 | .4483 | .812 | 16 | 158.1 |
| 25 | Alaska | 127.3 | .5513 | 47 | 9-14-4 | .4074 | .688 | 7 | 185.1 |
| 26 | Nebraska-Omaha | 125.5 | .5484 | 28T | 12-10-5 | .5370 | 1.160 | 33 | 108.2 |
| 27 | Colgate | 122.3 | .5428 | 19T | 14-10-3 | .5741 | 1.348 | 36 | 90.7 |
| 28 | New Hampshire | 121.2 | .5409 | 46 | 10-14-2 | .4231 | .733 | 13 | 165.3 |
| 29 | Wisconsin | 120.0 | .5389 | 35T | 12-13-2 | .4815 | .929 | 23 | 129.3 |
| 30 | Massachusetts | 119.9 | .5386 | 39 | 9-11-5 | .4600 | .852 | 19 | 140.7 |
| 31 | Harvard | 111.0 | .5222 | 31 | 7-6-9 | .5227 | 1.095 | 35 | 101.3 |
| 32 | Providence | 107.8 | .5160 | 43 | 10-13-2 | .4400 | .786 | 20 | 137.2 |
| 33 | Michigan Tech | 106.4 | .5132 | 35T | 12-13-2 | .4815 | .929 | 31 | 114.6 |
| 34 | Quinnipiac | 98.8 | .4975 | 19T | 13-9-5 | .5741 | 1.348 | 42 | 73.3 |
| 35 | Bowling Green | 71.7 | .4300 | 50T | 8-16-5 | .3621 | .568 | 26 | 126.3 |
| 36 | Clarkson | 69.4 | .4234 | 30 | 13-11-5 | .5345 | 1.148 | 46 | 60.5 |
| 37 | Dartmouth | 68.5 | .4205 | 32T | 9-9-4 | .5000 | 1.000 | 43 | 68.5 |
| 38 | Princeton | 64.2 | .4074 | 44 | 7-10-6 | .4348 | .769 | 39 | 83.5 |
| 39 | RIT | 64.1 | .4072 | 13T | 15-9-3 | .6111 | 1.571 | 50 | 40.8 |
| 40 | Minnesota State | 58.0 | .3871 | 50T | 10-18-1 | .3621 | .568 | 34 | 102.2 |
| 41 | Niagara | 57.8 | .3862 | 19T | 12-8-7 | .5741 | 1.348 | 48 | 42.9 |
| 42 | Yale | 55.4 | .3779 | 40 | 9-11-2 | .4545 | .833 | 44 | 66.5 |
| 43 | St. Lawrence | 54.6 | .3752 | 48 | 9-15-3 | .3889 | .636 | 38 | 85.9 |
| 44 | Air Force | 54.2 | .3738 | 11 | 13-7-6 | .6154 | 1.600 | 56 | 33.9 |
| 45 | Alaska-Anchorage | 52.4 | .3669 | 53 | 6-17-2 | .2800 | .389 | 21 | 134.7 |
| 46 | Brown | 48.2 | .3509 | 45 | 8-11-3 | .4318 | .760 | 45 | 63.4 |
| 47 | Robert Morris | 46.1 | .3425 | 28T | 13-11-3 | .5370 | 1.160 | 51 | 39.8 |
| 48 | Mercyhurst | 44.5 | .3356 | 24T | 14-11-4 | .5517 | 1.231 | 54 | 36.1 |
| 49 | Vermont | 44.4 | .3353 | 56 | 5-20-1 | .2115 | .268 | 12 | 165.5 |
| 50 | Connecticut | 40.6 | .3188 | 35T | 12-13-2 | .4815 | .929 | 47 | 43.7 |
| 51 | Holy Cross | 36.7 | .3007 | 38 | 11-13-3 | .4630 | .862 | 49 | 42.6 |
| 52 | Rensselaer | 32.7 | .2808 | 52 | 7-18-2 | .2963 | .421 | 41 | 77.7 |
| 53 | Bentley | 30.4 | .2684 | 42 | 9-12-6 | .4444 | .800 | 52 | 38.0 |
| 54 | Canisius | 20.7 | .2095 | 49 | 8-15-4 | .3704 | .588 | 55 | 35.2 |
| 55 | Army | 12.9 | .1501 | 54 | 3-15-7 | .2600 | .351 | 53 | 36.8 |
| 56 | Alabama-Huntsville | 11.2 | .1345 | 58 | 2-25-1 | .0893 | .098 | 32 | 114.0 |
| 57 | American Int'l | 8.3 | .1067 | 55 | 5-20-2 | .2222 | .286 | 58 | 29.1 |
| 58 | Sacred Heart | 3.3 | .0463 | 57 | 2-24-1 | .0926 | .102 | 57 | 31.9 |
| 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