2025 ARTICLE 13: 2025 PRE-SEASON PREDICTIONS AND INFORMATION, PART 6, GEOGRAPHIC REGIONS IN RELATION TO NCAA RPI RANKS AND STRENGTH OF SCHEDULE RANKS

This article, for the geographic regions within which the teams from each state play most of their games, provides information similar to that provided for conferences in 2025 Article 12.  A map showing the four regions is at the RPI for Division I Women's Soccer RPI: Regional Issues page.

As you can see, when averaged across a region, the differences between average NCAA RPI ranks and average Strength of Schedule contributor ranks under the NCAA RPI formula are relatively small.  This makes sense, since each region has an array of strong and weak teams and conferences.  As a generalization, however, looking at the numbers for the regions' teams opponents, overall and on average teams from the West region are discriminated against due to the way the NCAA formula computes Strength of Schedule, the Middle region experiences no impact, and the North and South regions are benefitted by discrimination.

To be clear, there are teams and conferences from all of the regions that the NCAA RPI formula discriminates against and in favor of.  The numbers above simply show the net effect of the discrimination for each region.

A particular concern this year is a significant reduction in out-of-region competition, most likeky due to less funding being available for travel.  The following table shows the extent of the reduction looking at the nation as a whole:

As you can see, the number of out-of-region games will be reduced by 28.1% from what the number historically has been.

A break down of the numbers from the preceding table by region shows reductions in the number of out-of-region games as follows:

Middle  18.3%

North  28.5%

South  30.0%

West  31.7%

These reductions should be a concern for the Women's Soccer Committee.  The NCAA RPI already has a problem ranking teams dispersed among the conferences and across the regions within a single national system.  The reductions in out-of-region play are likely to make the problem worse. 

 

2025 ARTICLE 12: 2025 PRE-SEASON PREDICTIONS AND INFORMATION, PART 5, CONFERENCES IN RELATION TO NCAA RPI RANKS AND STRENGTH OF SCHEDULE RANKS

 In 2025 Pre-Season Predictions and Information, Parts 4 and 4B, for the individual teams I showed the relationship between predicted NCAA RPI ranks and Strength of Schedule Contribution ranks under the NCAA RPI formula, both for the individual teams and for their opponents.  In this article, I will show the same information, but for each conference.  This gives a good picture of how the NCAA RPI discriminates among conferences because of the defective way it calculates Strength of Schedule.

This table has the conferences in NCAA RPI rank order, based on the average rating of their teams.  See below the table for comments.

In the table, the first two green-highlighted columns on the left show, for each conference, the difference between its teams' average NCAA RPI rank and its teams' average Strength of Schedule contributor rank under the NCAA RPI formula.  As you read down the table from the strongest conferences at the top to the weakest at the bottom, you can see the clear pattern: For stronger conferences, the conference teams' Strength of Schedule contributor ranks are poorer than the teams' actual ranks say they should be; and for weaker conferences they are better than they should be.

The next two salmon-highlighted columns look at how this plays out for the conference teams' schedules.  The first of those columns shows the conferences' teams' opponents' average ranks and the second column shows those opponents' average ranks as Strength of Schedule contributors.  The pattern here is the same:  Stronger conferences' opponents' Strength of Schedule Contributor ranks are poorer than the opponents' actual ranks say they should be; and the opposite is true for the weaker conferences.

The next four columns break the numbers for the conference teams' schedules down into conference opponents (green-highlighted) and non-conference opponents (salmon-highlighted).  Given that in conference play, the conferences' teams are playing each other, it is no surprise that the contrasts between the conference opponents' NCAA RPI ranks and their ranks as Strength of Schedule contributors follow the same basic pattern.  For the non-conference opponents, where the individual teams have more control over their schedules, the pattern is similar but less extreme and with a little more variability.

It is important here to point out that coaches in top tier and most coaches in middle tier conferences are aware of these patterns and often take them into consideration in their non-conference scheduling.  They also are aware, however, that in the NCAA Tournament seeding and at large selection processes, good results against highly ranked opponents matter, including against highly ranked non-conference opponents.  Further, coaches of teams with NCAA Tournament aspirations often want to play at least some strong non-conference opponents.  This means that they sometimes decide to schedule opponents whose Strength of Schedule contributions are likely to be poorer than their RPI ranks say they should be, essentially deciding to take a potential RPI "hit" in exchange for the potential of a good result against a highly ranked opponent.

NOTE:  Being aware of the scheduling dilemma I just described, I designed my Balanced RPI, which is a modification of the NCAA RPI, with the specific objective of eliminating the difference between teams' ranks and their ranks as Strength of Schedule contributors.  Thus under the Balanced RPI, if a team has a rank of X, that also is either exactly or very close to exactly the team's rank as a Strength of Schedule contributor.  In other words, if the NCAA were to use the Balanced RPI, coaches no longer would have this scheduling dilemma.   (As an additional benefit, the RPI no longer would discriminate among conferences in relation to conference strength.)