So we're going to pretend all my losses were by 1 point?
The first S in SRS stands for Simple because the SRS is simply the sum of two variables: a team’s average margin of victory (or points differential) and a team’s strength of schedule.
But what if we only care about wins and losses? Even in that case, we still care about strength of schedule. The BCS mandates that the computer systems used to provide the official BCS ratings ignore margin of victory. Essentially, that’s what I’m doing here. To provide Elo-style ratings for NFL teams, I made each win a one-point win, each loss a one-point loss, and each tie worth 0 points. Therefore, a team’s MOV perfectly matches its record, leaving just the SOS to shuffle the deck.
Is this useful for anything? No. That’s why it’s a Friday night checkdown.
Rk | Team | G | MOV | SOS | SRS | Record |
|---|---|---|---|---|---|---|
| 1 | Houston Texans | 13 | 0.692 | 0.011 | 0.704 | 11-2-0 |
| 2 | New England Patriots | 13 | 0.538 | 0.116 | 0.654 | 10-3-0 |
| 3 | San Francisco 49ers | 13 | 0.462 | 0.081 | 0.543 | 9-3-1 |
| 4 | Green Bay Packers | 13 | 0.385 | 0.107 | 0.492 | 9-4-0 |
| 5 | Atlanta Falcons | 13 | 0.692 | -0.273 | 0.42 | 11-2-0 |
| 6 | Denver Broncos | 13 | 0.538 | -0.166 | 0.373 | 10-3-0 |
| 7 | Chicago Bears | 13 | 0.231 | 0.121 | 0.352 | 8-5-0 |
| 8 | Seattle Seahawks | 13 | 0.231 | 0.114 | 0.345 | 8-5-0 |
| 9 | Indianapolis Colts | 13 | 0.385 | -0.053 | 0.332 | 9-4-0 |
| 10 | Baltimore Ravens | 13 | 0.385 | -0.135 | 0.249 | 9-4-0 |
| 11 | New York Giants | 13 | 0.231 | -0.04 | 0.191 | 8-5-0 |
| 12 | St. Louis Rams | 13 | 0 | 0.175 | 0.175 | 6-6-1 |
| 13 | Minnesota Vikings | 13 | 0.077 | 0.067 | 0.144 | 7-6-0 |
| 14 | New York Jets | 13 | -0.077 | 0.172 | 0.095 | 6-7-0 |
| 15 | Washington Redskins | 13 | 0.077 | -0.003 | 0.074 | 7-6-0 |
| 16 | Dallas Cowboys | 13 | 0.077 | -0.012 | 0.065 | 7-6-0 |
| 17 | Cincinnati Bengals | 14 | 0.143 | -0.203 | -0.06 | 8-6-0 |
| 18 | Pittsburgh Steelers | 13 | 0.077 | -0.138 | -0.061 | 7-6-0 |
| 19 | Miami Dolphins | 13 | -0.231 | 0.126 | -0.105 | 5-8-0 |
| 20 | Buffalo Bills | 13 | -0.231 | 0.067 | -0.164 | 5-8-0 |
| 21 | Arizona Cardinals | 13 | -0.385 | 0.203 | -0.181 | 4-9-0 |
| 22 | Detroit Lions | 13 | -0.385 | 0.188 | -0.197 | 4-9-0 |
| 23 | Tampa Bay Buccaneers | 13 | -0.077 | -0.162 | -0.239 | 6-7-0 |
| 24 | Tennessee Titans | 13 | -0.385 | 0.134 | -0.25 | 4-9-0 |
| 25 | New Orleans Saints | 13 | -0.231 | -0.035 | -0.266 | 5-8-0 |
| 26 | Cleveland Browns | 13 | -0.231 | -0.125 | -0.356 | 5-8-0 |
| 27 | Carolina Panthers | 13 | -0.385 | 0.014 | -0.371 | 4-9-0 |
| 28 | San Diego Chargers | 13 | -0.231 | -0.165 | -0.396 | 5-8-0 |
| 29 | Philadelphia Eagles | 14 | -0.429 | -0.048 | -0.476 | 4-10-0 |
| 30 | Jacksonville Jaguars | 13 | -0.692 | 0.141 | -0.551 | 2-11-0 |
| 31 | Oakland Raiders | 13 | -0.538 | -0.112 | -0.651 | 3-10-0 |
| 32 | Kansas City Chiefs | 13 | -0.692 | -0.148 | -0.84 | 2-11-0 |
{ 1 comment… read it below or add one }
Elo is definitely an interesting concept. I think in it’s traditional chess style format, it can definitely work for professional leagues. The Carl Meyer book, Neil referred to a couple of months ago has a chapter on it. I set up a spreadsheet to work up College Football in an Elo Style taking into account scores, but now realise that you can’t really apply it to College sports because of the wide variety in strength of opponents.
It makes the assumption everyone starts from 0 and that everyone is equal (which in the College game really isn’t the case but I would expect is more appropriate for the NFL) so hence best example FSU got about 14 or 15 points for wins over Murray St and Savannah St, yet A&M only got about 5 points for beating Alabama (incidentally overall for the season it put Alabama first, from FSU who had an unrealistic score based on their first two games and then Notre Dame so it was generating the right kind of ranking).