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 | Denver | 616.5 | .8312 | 2 | 25-7-4 | .7500 | 3.000 | 7 | 205.5 |
| 2 | Miami | 545.7 | .8145 | 1 | 24-5-7 | .7639 | 3.235 | 13 | 168.7 |
| 3 | Wisconsin | 465.4 | .7912 | 5 | 22-9-4 | .6857 | 2.182 | 4 | 213.3 |
| 4 | North Dakota | 367.1 | .7534 | 9T | 20-11-5 | .6250 | 1.667 | 3 | 220.3 |
| 5 | St. Cloud State | 340.6 | .7407 | 9T | 20-11-5 | .6250 | 1.667 | 8 | 204.3 |
| 6 | Boston College | 290.9 | .7128 | 6T | 21-10-3 | .6618 | 1.957 | 24 | 148.7 |
| 7 | Minnesota-Duluth | 250.9 | .6856 | 19 | 20-15-1 | .5694 | 1.323 | 10 | 189.7 |
| 8 | Bemidji State | 250.5 | .6853 | 3 | 23-8-3 | .7206 | 2.579 | 34 | 97.1 |
| 9 | Colorado College | 246.6 | .6823 | 23 | 18-15-3 | .5417 | 1.182 | 6 | 208.6 |
| 10 | Alaska | 242.8 | .6794 | 9T | 18-9-9 | .6250 | 1.667 | 25 | 145.7 |
| 11 | New Hampshire | 238.2 | .6758 | 18 | 16-11-7 | .5735 | 1.345 | 12 | 177.1 |
| 12 | Minnesota | 224.8 | .6646 | 32T | 17-17-2 | .5000 | 1.000 | 2 | 224.8 |
| 13 | Michigan State | 224.0 | .6640 | 13T | 19-11-6 | .6111 | 1.571 | 28 | 142.6 |
| 14 | Northern Michigan | 218.3 | .6590 | 16 | 17-11-8 | .5833 | 1.400 | 18 | 155.9 |
| 15 | Ferris State | 213.2 | .6544 | 13T | 19-11-6 | .6111 | 1.571 | 32 | 135.7 |
| 16 | Nebraska-Omaha | 208.2 | .6497 | 17 | 20-14-6 | .5750 | 1.353 | 20 | 153.9 |
| 17 | Vermont | 198.7 | .6405 | 22 | 15-12-7 | .5441 | 1.194 | 14 | 166.5 |
| 18 | Yale | 193.8 | .6356 | 4 | 19-7-3 | .7069 | 2.412 | 39 | 80.4 |
| 19 | Michigan | 186.3 | .6277 | 21 | 21-17-1 | .5513 | 1.229 | 22 | 151.6 |
| 20 | Mass.-Lowell | 172.2 | .6119 | 20 | 18-14-4 | .5556 | 1.250 | 30 | 137.7 |
| 21 | Maine | 171.2 | .6107 | 28T | 16-15-3 | .5147 | 1.061 | 15 | 161.4 |
| 22 | Cornell | 170.1 | .6094 | 8 | 17-8-4 | .6552 | 1.900 | 35 | 89.5 |
| 23 | Boston University | 169.3 | .6085 | 28T | 16-15-3 | .5147 | 1.061 | 16 | 159.7 |
| 24 | Massachusetts | 161.8 | .5993 | 26T | 18-16-0 | .5294 | 1.125 | 27 | 143.8 |
| 25 | Minnesota State | 161.5 | .5989 | 38T | 15-18-3 | .4583 | .846 | 9 | 190.8 |
| 26 | Ohio State | 158.8 | .5955 | 35 | 14-16-6 | .4722 | .895 | 11 | 177.5 |
| 27 | Northeastern | 152.8 | .5877 | 32T | 16-16-2 | .5000 | 1.000 | 21 | 152.8 |
| 28 | Merrimack | 138.8 | .5678 | 36 | 15-17-2 | .4706 | .889 | 17 | 156.1 |
| 29 | Union | 123.3 | .5434 | 12 | 18-10-6 | .6176 | 1.615 | 40 | 76.3 |
| 30 | Lake Superior | 119.4 | .5367 | 37 | 15-18-5 | .4605 | .854 | 29 | 139.8 |
| 31 | Notre Dame | 116.7 | .5320 | 40 | 13-17-8 | .4474 | .810 | 26 | 144.1 |
| 32 | Alaska-Anchorage | 115.5 | .5298 | 50T | 11-21-2 | .3529 | .545 | 5 | 211.7 |
| 33 | Quinnipiac | 81.6 | .4580 | 24 | 19-16-2 | .5405 | 1.176 | 46 | 69.3 |
| 34 | St. Lawrence | 81.0 | .4567 | 25 | 17-14-7 | .5395 | 1.171 | 47 | 69.2 |
| 35 | Colgate | 80.3 | .4550 | 26T | 15-13-6 | .5294 | 1.125 | 45 | 71.4 |
| 36 | Rensselaer | 76.8 | .4458 | 31 | 18-17-4 | .5128 | 1.053 | 44 | 73.0 |
| 37 | Western Michigan | 75.5 | .4423 | 53 | 8-20-8 | .3333 | .500 | 23 | 151.0 |
| 38 | Providence | 74.5 | .4396 | 50T | 10-20-4 | .3529 | .545 | 31 | 136.5 |
| 39 | Robert Morris | 61.6 | .4017 | 47 | 10-18-5 | .3788 | .610 | 33 | 101.0 |
| 40 | Princeton | 57.0 | .3864 | 41 | 12-16-3 | .4355 | .771 | 42 | 73.9 |
| 41 | Niagara | 54.6 | .3781 | 46 | 11-19-4 | .3824 | .619 | 36 | 88.2 |
| 42 | Michigan Tech | 47.9 | .3533 | 58 | 5-28-1 | .1618 | .193 | 1 | 248.3 |
| 43 | Alabama-Huntsville | 47.4 | .3511 | 45 | 10-17-3 | .3833 | .622 | 41 | 76.2 |
| 44 | RIT | 47.1 | .3501 | 6T | 22-11-1 | .6618 | 1.957 | 52 | 24.1 |
| 45 | Bowling Green | 44.4 | .3389 | 56 | 5-25-6 | .2222 | .286 | 19 | 155.2 |
| 46 | Harvard | 43.0 | .3332 | 52 | 9-19-3 | .3387 | .512 | 37 | 83.9 |
| 47 | Dartmouth | 41.0 | .3245 | 49 | 10-19-3 | .3594 | .561 | 43 | 73.1 |
| 48 | Brown | 38.9 | .3152 | 48 | 10-18-4 | .3750 | .600 | 48 | 64.8 |
| 49 | Sacred Heart | 34.5 | .2943 | 15 | 18-12-4 | .5882 | 1.429 | 51 | 24.2 |
| 50 | Clarkson | 34.4 | .2936 | 54 | 9-24-4 | .2973 | .423 | 38 | 81.3 |
| 51 | Air Force | 25.0 | .2415 | 32T | 14-14-6 | .5000 | 1.000 | 49 | 25.0 |
| 52 | Canisius | 22.6 | .2263 | 28T | 15-14-5 | .5147 | 1.061 | 58 | 21.3 |
| 53 | Mercyhurst | 19.4 | .2048 | 38T | 15-18-3 | .4583 | .846 | 54 | 23.0 |
| 54 | Army | 18.1 | .1955 | 43 | 11-16-7 | .4265 | .744 | 50 | 24.4 |
| 55 | Holy Cross | 17.1 | .1877 | 42 | 12-17-6 | .4286 | .750 | 55 | 22.8 |
| 56 | Bentley | 14.3 | .1654 | 44 | 12-19-4 | .4000 | .667 | 57 | 21.5 |
| 57 | Connecticut | 7.6 | .1006 | 55 | 7-25-3 | .2429 | .321 | 53 | 23.7 |
| 58 | American Int'l | 5.9 | .0811 | 57 | 5-24-4 | .2121 | .269 | 56 | 22.0 |
| 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