An additional point of note/clarification: It does not matter to SOR which games on a schedule were won or lost; only the number of wins/losses.

For example, Alabama's SOR would be the same as it is now if we reversed the results of their FSU and UGA games.

Finally, SOR employs the cdf for the Poisson binomial distribution to combine each of the individual exp win pct values and a team's results into a single chance-of-record-or-better value. That's it!

The expected win pct values incorporate the opponent's up-to-date FPI strength and advantages related to home field, travel distance, and rest.

You can see how each of LSU's opponents' chance to win values vary based on those factors (very little, except for hfa).

Let's use 8-0 Texas A&M as an example.

This is their schedule, so far, and the expected win pct that an average top 25 team would have against each team on the schedule (AVGTOPTM_EXP_WINPCT):

There seems to be some interest in how SOR is calculated, so I will do a quick thread.

If you aren't familiar with SOR (Strength of Record), it's defined at the bottom of the CFB FPI Resume page
t.co/3JZenVc4nt

BPI R1

Those 6-6 teams are better than 9 of the 12 teams SMU played in the regular season

I don't fault him for advocating for what's best for his team (SMU making the playoff over Bama) but I really need people to understand just how much harder things are for Bama.