PAYING ATTENTION TO THE RPI FORMULA IN YOUR NON-CONFERENCE SCHEDULING: FOLLOW UP

I my previous post I described an experiment I ran to see how much non-conference scheduling matters.  The experiment's results said that it matters a lot -- indeed, a whole lot.  In fact, it mattered so much that wanted to come up with a new and different experiment to see if it would produce similar results.

In the new experiment, I started with the 2018 season exactly as played.  That season ended up with Clemson having an ARPI rank of #46 (although Massey gave them a rank of #22).  In that season, here are Clemson's opponents with the game locations and results, plus the opponents' ARPI ranks, ranks as contributors to opponents' strengths of schedule, and Massey ranks (which I consider to be the best indicators of the opponents' true strength):

What's most notable here is that Clemson's opponents' average rank as contributors' to its strength of schedule was considerably poorer than their average ARPI rank and even more poor than their average Massey rank.

For the experiment, I simply substituted, for each opponent, a different opponent with a better rank as contributor to opponents' strengths of schedule:

As you can see, the opponents' average ARPI ranks are the same as they were for Clemson's actual schedule.  In other words, from an RPI formula perspective, the two schedules were equal in strength.  But look at the opponents' average rank as contributors to Clemson's strength of schedule.  They now are much better than the opponents' average ARPI rank.  And, they are 91 rank positions better than under the schedule Clemson actually played.  Plus, according to Massey, this experiment schedule actually is significantly weaker than the ARPI says it is and much weaker than Clemson's actual schedule was.

So, as stated above, according to the ARPI formula, based on Clemson's actual schedule, their rank was #46.  With the substitute opponents, but same results, what does the ARPI formula say its rank is?  #23!  Even though playing an equally difficult schedule according to the ARPI and a significantly easier schedule according to Massey.

But, according to Massey, when I substituted Radford for Oregon as an opponent, I substituted a #108 team for a #56 team.  Clemson lost to Oregon, so in alternative schedule experiment I have Clemson losing to Radford.  Suppose Massey is right and Radford is much weaker than Oregon.  Then it's fair to expect that Clemson would beat Radford.  If I change the experiment to give Clemson a win in that game, the ARPI formula now gives it a rank of #17.

And further, when I substituted South Florida for South Carolina, according to Massey I substituted a #30 team for a #18 team.  Suppose Massey is right about South Florida.  If I change the experiment to give Clemson a win in that game, the ARPI formula now gives it a rank of #8.

The point of all this is:  Clemson, by playing a 2018 schedule intended to maximize its ARPI rank, could have ended up with a rank in the #8 to #23 area, rather than the #46 it actually received.  And it could have done this with a schedule that would look equally as strong as the one it actually played, so far as the Women's Soccer Committee would be concerned.

Conclusion.  My first experiment said that if you schedule with a view to how your schedule will relate to the RPI formula, it can make a whole lot of difference in what your final ARPI rank will be.  It made so much of a difference that I wanted to do a different experiment to see if it produced relatively similar results.  I did perform that experiment, as described above, and it confirmed what the first experiment indicated.  If you schedule with a view to how your schedule will relate to the RPI formula, it can make a whole lot of difference for your final ARPI rank.