KRACH Ratings
KRACH is endorsed by College Hockey News as the best system to objectivly 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 | Michigan | 769.4 | .8567 | 1 | 31-5-4 | .8250 | 4.714 | 12 | 163.2 |
| 2 | North Dakota | 613.7 | .8289 | 5 | 26-10-4 | .7000 | 2.333 | 1 | 263.0 |
| 3 | Colorado College | 585.3 | .8226 | 4 | 28-11-1 | .7125 | 2.478 | 7 | 236.2 |
| 4 | Miami | 558.6 | .8163 | 2 | 32-7-1 | .8125 | 4.333 | 24 | 128.9 |
| 5 | Denver | 471.8 | .7922 | 7T | 26-13-1 | .6625 | 1.963 | 5 | 240.4 |
| 6 | New Hampshire | 427.7 | .7773 | 3 | 25-9-3 | .7162 | 2.524 | 11 | 169.5 |
| 7 | Michigan State | 294.5 | .7151 | 7T | 24-11-5 | .6625 | 1.963 | 20 | 150.0 |
| 8 | St. Cloud State | 285.5 | .7096 | 19 | 19-15-5 | .5513 | 1.229 | 9 | 232.4 |
| 9 | Minnesota | 268.4 | .6984 | 21 | 19-16-9 | .5341 | 1.146 | 8 | 234.1 |
| 10 | Boston College | 265.7 | .6965 | 10 | 21-11-8 | .6250 | 1.667 | 15 | 159.4 |
| 11 | Minnesota State | 239.0 | .6768 | 20 | 19-16-4 | .5385 | 1.167 | 10 | 204.9 |
| 12 | Wisconsin | 230.4 | .6699 | 31 | 15-16-7 | .4868 | .9487 | 4 | 242.8 |
| 13 | Minnesota-Duluth | 204.6 | .6469 | 40 | 13-17-6 | .4444 | .8000 | 2 | 255.8 |
| 14 | Notre Dame | 192.5 | .6349 | 13 | 24-15-4 | .6047 | 1.529 | 27 | 125.8 |
| 15 | Michigan Tech | 185.3 | .6273 | 43 | 14-20-5 | .4231 | .7333 | 3 | 252.6 |
| 16 | Clarkson | 180.7 | .6224 | 11 | 21-12-4 | .6216 | 1.643 | 31 | 110.0 |
| 17 | Boston University | 177.0 | .6182 | 25 | 19-17-4 | .5250 | 1.105 | 14 | 160.1 |
| 18 | Vermont | 171.0 | .6113 | 23T | 17-15-7 | .5256 | 1.108 | 17 | 154.3 |
| 19 | Princeton | 157.1 | .5940 | 12 | 21-13-0 | .6176 | 1.615 | 34 | 97.26 |
| 20 | Massachusetts | 143.5 | .5755 | 35 | 14-16-6 | .4722 | .8947 | 13 | 160.4 |
| 21 | Northern Michigan | 140.5 | .5710 | 28T | 20-20-4 | .5000 | 1.000 | 22 | 140.5 |
| 22 | Northeastern | 138.3 | .5677 | 34 | 16-18-3 | .4730 | .8974 | 18 | 154.1 |
| 23 | Harvard | 134.5 | .5620 | 18 | 17-13-4 | .5588 | 1.267 | 32 | 106.2 |
| 24 | Mass.-Lowell | 134.3 | .5617 | 32 | 16-17-4 | .4865 | .9474 | 21 | 141.8 |
| 25 | Providence | 130.7 | .5561 | 38 | 14-17-5 | .4583 | .8462 | 16 | 154.5 |
| 26 | Cornell | 124.1 | .5452 | 15 | 19-14-3 | .5694 | 1.323 | 37 | 93.82 |
| 27 | Nebraska-Omaha | 115.0 | .5294 | 33 | 17-19-4 | .4750 | .9048 | 25 | 127.1 |
| 28 | Maine | 112.6 | .5248 | 42 | 13-18-3 | .4265 | .7436 | 19 | 151.4 |
| 29 | Ferris State | 112.2 | .5242 | 23T | 18-16-5 | .5256 | 1.108 | 33 | 101.3 |
| 30 | Alaska-Anchorage | 104.0 | .5083 | 55 | 7-21-8 | .3056 | .4400 | 6 | 236.5 |
| 31 | Quinnipiac | 99.14 | .4982 | 17 | 20-15-4 | .5641 | 1.294 | 44 | 76.61 |
| 32 | Bowling Green | 98.03 | .4958 | 36 | 18-21-0 | .4615 | .8571 | 30 | 114.4 |
| 33 | Niagara | 97.14 | .4939 | 6 | 22-10-4 | .6667 | 2.000 | 49 | 48.57 |
| 34 | Union | 94.23 | .4875 | 26 | 15-14-6 | .5143 | 1.059 | 41 | 88.99 |
| 35 | Yale | 94.09 | .4872 | 22 | 16-14-4 | .5294 | 1.125 | 43 | 83.63 |
| 36 | Merrimack | 88.74 | .4750 | 44 | 12-18-4 | .4118 | .7000 | 26 | 126.8 |
| 37 | Colgate | 87.51 | .4721 | 28T | 18-18-6 | .5000 | 1.000 | 42 | 87.51 |
| 38 | Bemidji State | 77.30 | .4462 | 27 | 17-16-3 | .5139 | 1.057 | 45 | 73.12 |
| 39 | Lake Superior | 77.22 | .4460 | 49 | 10-20-7 | .3649 | .5745 | 23 | 134.4 |
| 40 | Dartmouth | 74.81 | .4395 | 41 | 12-16-4 | .4375 | .7778 | 36 | 96.19 |
| 41 | Ohio State | 63.75 | .4067 | 51 | 12-25-4 | .3415 | .5185 | 29 | 122.9 |
| 42 | St. Lawrence | 62.51 | .4028 | 45 | 13-20-4 | .4054 | .6818 | 39 | 91.68 |
| 43 | Alaska | 60.84 | .3973 | 53 | 9-21-5 | .3286 | .4894 | 28 | 124.3 |
| 44 | Robert Morris | 57.66 | .3865 | 28T | 15-15-4 | .5000 | 1.000 | 48 | 57.66 |
| 45 | Air Force | 55.06 | .3774 | 9 | 21-11-6 | .6316 | 1.714 | 52 | 32.12 |
| 46 | Rensselaer | 48.29 | .3518 | 50 | 11-23-4 | .3421 | .5200 | 38 | 92.87 |
| 47 | RIT | 44.92 | .3380 | 14 | 19-12-6 | .5946 | 1.467 | 53 | 30.63 |
| 48 | Brown | 33.57 | .2849 | 57T | 6-21-4 | .2581 | .3478 | 35 | 96.53 |
| 49 | Army | 31.97 | .2764 | 16 | 19-14-4 | .5676 | 1.313 | 59 | 24.36 |
| 50 | Wayne State | 30.58 | .2689 | 54 | 11-25-2 | .3158 | .4615 | 46 | 66.26 |
| 51 | Western Michigan | 30.48 | .2683 | 59 | 8-27-3 | .2500 | .3333 | 40 | 91.45 |
| 52 | Mercyhurst | 27.91 | .2536 | 39 | 15-19-7 | .4512 | .8222 | 50 | 33.94 |
| 53 | Sacred Heart | 23.66 | .2273 | 37 | 16-19-3 | .4605 | .8537 | 57 | 27.71 |
| 54 | Alabama-Huntsville | 21.65 | .2140 | 57T | 6-21-4 | .2581 | .3478 | 47 | 62.26 |
| 55 | Canisius | 19.85 | .2013 | 47 | 11-20-6 | .3784 | .6087 | 51 | 32.61 |
| 56 | Holy Cross | 17.55 | .1842 | 48 | 10-19-7 | .3750 | .6000 | 54 | 29.25 |
| 57 | Connecticut | 17.28 | .1821 | 46 | 13-21-3 | .3919 | .6444 | 58 | 26.81 |
| 58 | Bentley | 14.57 | .1602 | 52 | 9-21-6 | .3333 | .5000 | 55 | 29.15 |
| 59 | American Int'l | 11.78 | .1356 | 56 | 8-23-5 | .2917 | .4118 | 56 | 28.62 |
| 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