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 | Miami | 579.2 | .8218 | 1 | 20-4-6 | .7667 | 3.286 | 11 | 176.3 |
| 2 | Denver | 551.0 | .8148 | 3 | 18-6-4 | .7143 | 2.500 | 4 | 220.4 |
| 3 | Wisconsin | 468.0 | .7910 | 5T | 16-7-4 | .6667 | 2.000 | 1 | 234.0 |
| 4 | St. Cloud State | 417.9 | .7734 | 5T | 18-8-4 | .6667 | 2.000 | 7 | 209.0 |
| 5 | Colorado College | 346.6 | .7426 | 11T | 17-10-3 | .6167 | 1.609 | 6 | 215.4 |
| 6 | Minnesota-Duluth | 314.8 | .7259 | 11T | 18-11-1 | .6167 | 1.609 | 8 | 195.7 |
| 7 | Boston College | 275.9 | .7022 | 8 | 16-8-2 | .6538 | 1.889 | 20 | 146.1 |
| 8 | Bemidji State | 271.8 | .6995 | 2 | 18-6-2 | .7308 | 2.714 | 34 | 100.2 |
| 9 | North Dakota | 270.4 | .6985 | 21 | 13-10-5 | .5536 | 1.240 | 5 | 218.1 |
| 10 | Maine | 253.0 | .6862 | 14 | 14-9-3 | .5962 | 1.476 | 14 | 171.4 |
| 11 | Vermont | 234.9 | .6722 | 17 | 13-9-4 | .5769 | 1.364 | 13 | 172.3 |
| 12 | Michigan State | 228.7 | .6671 | 13 | 17-10-5 | .6094 | 1.560 | 19 | 146.6 |
| 13 | New Hampshire | 222.3 | .6616 | 20 | 13-10-4 | .5556 | 1.250 | 10 | 177.9 |
| 14 | Ferris State | 221.6 | .6610 | 10 | 17-9-4 | .6333 | 1.727 | 30 | 128.3 |
| 15 | Massachusetts | 203.4 | .6444 | 15 | 16-11-0 | .5926 | 1.455 | 25 | 139.9 |
| 16 | Minnesota | 194.7 | .6358 | 32T | 13-13-2 | .5000 | 1.000 | 9 | 194.7 |
| 17 | Michigan | 188.6 | .6294 | 22T | 16-13-1 | .5500 | 1.222 | 17 | 154.3 |
| 18 | Cornell | 183.1 | .6235 | 7 | 13-6-3 | .6591 | 1.933 | 36 | 94.7 |
| 19 | Yale | 173.2 | .6124 | 4 | 14-6-3 | .6739 | 2.067 | 39 | 83.8 |
| 20 | Northern Michigan | 172.5 | .6116 | 29 | 12-10-8 | .5333 | 1.143 | 18 | 150.9 |
| 21 | Alaska | 168.2 | .6065 | 25T | 11-9-8 | .5357 | 1.154 | 21 | 145.8 |
| 22 | Union | 157.4 | .5931 | 9 | 15-7-6 | .6429 | 1.800 | 37 | 87.5 |
| 23 | Lake Superior | 152.7 | .5869 | 22T | 14-11-5 | .5500 | 1.222 | 32 | 124.9 |
| 24 | Northeastern | 152.2 | .5863 | 31 | 13-12-1 | .5192 | 1.080 | 24 | 140.9 |
| 25 | Nebraska-Omaha | 152.2 | .5862 | 30 | 14-12-6 | .5312 | 1.133 | 28 | 134.3 |
| 26 | Boston University | 150.9 | .5845 | 36 | 11-12-3 | .4808 | .926 | 16 | 163.0 |
| 27 | Alaska-Anchorage | 146.4 | .5784 | 44 | 10-16-2 | .3929 | .647 | 3 | 226.3 |
| 28 | Mass.-Lowell | 145.5 | .5771 | 25T | 14-12-2 | .5357 | 1.154 | 31 | 126.1 |
| 29 | Minnesota State | 143.7 | .5746 | 38 | 12-14-2 | .4643 | .867 | 15 | 165.8 |
| 30 | Ohio State | 139.0 | .5677 | 39T | 11-14-3 | .4464 | .806 | 12 | 172.3 |
| 31 | Notre Dame | 135.6 | .5626 | 35 | 12-13-7 | .4844 | .939 | 22 | 144.3 |
| 32 | Rensselaer | 101.6 | .5032 | 22T | 15-12-3 | .5500 | 1.222 | 40 | 83.1 |
| 33 | St. Lawrence | 99.9 | .4997 | 19 | 14-10-5 | .5690 | 1.320 | 43 | 75.7 |
| 34 | Merrimack | 95.8 | .4913 | 43 | 10-15-0 | .4000 | .667 | 23 | 143.8 |
| 35 | Quinnipiac | 82.7 | .4612 | 25T | 14-12-2 | .5357 | 1.154 | 45 | 71.7 |
| 36 | Western Michigan | 82.5 | .4608 | 46 | 8-15-5 | .3750 | .600 | 26 | 137.6 |
| 37 | Providence | 78.3 | .4500 | 47 | 9-16-2 | .3704 | .588 | 29 | 133.1 |
| 38 | Princeton | 69.4 | .4259 | 37 | 10-11-2 | .4783 | .917 | 42 | 75.7 |
| 39 | Robert Morris | 69.3 | .4255 | 45 | 8-14-5 | .3889 | .636 | 33 | 108.9 |
| 40 | Colgate | 67.4 | .4202 | 32T | 11-11-5 | .5000 | 1.000 | 46 | 67.4 |
| 41 | Michigan Tech | 56.5 | .3856 | 57 | 5-22-1 | .1964 | .244 | 2 | 231.1 |
| 42 | Niagara | 50.2 | .3631 | 51 | 7-15-4 | .3462 | .529 | 35 | 94.8 |
| 43 | Alabama-Huntsville | 42.9 | .3340 | 49 | 7-13-2 | .3636 | .571 | 44 | 75.1 |
| 44 | Harvard | 39.4 | .3187 | 52 | 6-14-3 | .3261 | .484 | 41 | 81.4 |
| 45 | Bowling Green | 38.5 | .3148 | 56 | 4-19-4 | .2222 | .286 | 27 | 134.8 |
| 46 | Brown | 36.0 | .3029 | 48 | 7-13-3 | .3696 | .586 | 48 | 61.4 |
| 47 | Sacred Heart | 35.6 | .3011 | 18 | 14-10-4 | .5714 | 1.333 | 51 | 26.7 |
| 48 | RIT | 32.6 | .2859 | 16 | 16-11-1 | .5893 | 1.435 | 57 | 22.7 |
| 49 | Canisius | 27.9 | .2605 | 25T | 13-11-4 | .5357 | 1.154 | 54 | 24.2 |
| 50 | Dartmouth | 26.2 | .2508 | 53 | 6-16-1 | .2826 | .394 | 47 | 66.6 |
| 51 | Clarkson | 25.5 | .2464 | 54 | 5-20-3 | .2321 | .302 | 38 | 84.3 |
| 52 | Air Force | 23.4 | .2332 | 32T | 12-12-6 | .5000 | 1.000 | 56 | 23.4 |
| 53 | Army | 21.9 | .2236 | 39T | 10-13-5 | .4464 | .806 | 49 | 27.1 |
| 54 | Bentley | 21.7 | .2220 | 39T | 11-14-3 | .4464 | .806 | 50 | 26.9 |
| 55 | Mercyhurst | 20.1 | .2115 | 42 | 12-16-2 | .4333 | .765 | 52 | 26.3 |
| 56 | Holy Cross | 13.0 | .1555 | 50 | 7-15-5 | .3519 | .543 | 55 | 23.9 |
| 57 | American Int'l | 6.4 | .0887 | 55 | 5-19-2 | .2308 | .300 | 58 | 21.5 |
| 58 | Connecticut | 6.1 | .0850 | 58 | 4-22-3 | .1897 | .234 | 53 | 26.2 |
| 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