Sev09's football computer rankings - 2013 season

Whats your formula?

I like how you came up with #2 at least

Workout the formula or is hard to see where you went wrong, but clearly something is way off.

As bad as Arky was last year, they were much better than many of the teams ahead of them.

It appears your formula weighs win loss record too much without a corresponding weight given to strength of opponent.

Interested to know the formula too, especially considering how Bama is ranked #7 and Oklahoma #17, with the same record and OU winning head-to-head.

UCF had a better record than Baylor, and beat them.

I know it's a computer "power ranking," and can't take into account the actual games necessarily, but if you have a sec to determine what major criteria is being used.

By the way, I'm not disparaging your rankings, just bringing up talking points. Good work.

does it factor in miracles?

Suspect...... just kidding.

How did you come up with your metrics? I think more people would take this a bit more seriously if they knew how you arrived at your claim.

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What's your formula?

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It's both simple and complicated at the same time. I'll start at the most granular level.

1.) Compute Rushing Power and Passing Power of each team. These are each calculated using important stats such as passing yards, completion %, Passing TDs, rushing yards, rushing tds, etc. MINUS interceptions and fumbles lost, times a multiplier, for passing and rushing power, respectively.

2.) Calculated average of Rushing and Passing Power to calculate Offense Power Index (OPI).

3.) Calculate Oppositions' rushing and passing power against, which measures the teams Defense Power Index.

4.) Defense Power Index (DPI) is then adjusted with additional considerations such as sacks, interceptions, forced fumbles, TFL, etc. for a small addition of "Defense Style Points". This correction takes into consideration the "eyeball test" and other physicality stats. After this correction, the DPI and OPI of the best teams are around 90-100 in either category, depending on their strengths.

5.) Power Index (PI) is then calculated as an average of the OPI and DPI. There are also certain measures in place, for example: If a team has a DPI of over 90, the DPI will be weighted more heavily in the PI calculation, since that is an outstanding number. Vice Versa for OPI > 90.

6.) After these detailed calculations, sort the teams by wins (descending), losses (ascending), and PI (descending).

7.) Then, I rank the conference's SOS by calculating the average ranking per conference, and assign relative Win/Loss multipliers.

8.) These Win/Loss multipliers are then applied to each teams' WL record.

9.) FINALLY, the final rankings are calculated as [Adjusted Wins] * (1 + (0.01*[PI]), descending.

These detailed calculations account for a team's true strength and capabilities. In theory, of course. I can't wait to see the results.

That might explain why the Big10 gets a lot of value in your rankings. Not wrong necessarily, but if the SOS of Big10 schools is "too high" then you'll get that fluctuation.

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South Alabama ranked TWICE...


HOW AM I SUPPOSED TO TAKE THESE RANKINGS SERIOUSLY?!

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That was a hasty stitching together of multiple screenshots. Sorry about that.

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Slow day at the office?

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This has been a couple weeks in the making - part of a bet between a buddy of mine.