The previous post in this series addressed the myth that strength of schedule controls the RPI, while winning percentage is relatively insignificant. Now I’ll examine the common complaint that merely playing “so and so” can lower or raise your RPI, regardless of the outcome. This is a statement that can’t be refuted because it’s true. And this post isn’t really a defense, but a demonstration as to how the RPI works.

The effect of an RPI fluctutation merely due to whom one plays is obvious early in the year. By the end of the season this effect is reduced, but not eliminated. The RPI is only meaningful at the end of the year, so that’s the perspective one should take when poking holes in it. And the RPI really only matters to a few teams at the end of the year, and those are the teams in the 35-70 range that are under consideration for the NCAA tournament. So for an example we should examine a bubble team’s data at the end of the season.

Therefore let’s look at the #43 team from last year, Gonzaga. They weren’t really a bubble team, but their non-conference schedule provides more variety than anyone elses, so they are a great team to examine. Gonzaga played #1 Kentucky, but also #308 Long Beach St. Here’s how Gonzaga’s RPI rank would have looked with certain games removed from their schedule:

Loss vs. #1 Kentucky............43 (no change)
Win  vs. #308 Long Beach........38 (+5)
Win  vs. #232 Washington St.....40 (+3)
Win  vs. #161 Washington........43 (no change)

As the game against Kentucky indicates, losing to a highly ranked team doesn’t help a bubble team’s RPI much. So Gonzaga was not helped by losing to Kentucky, yet they did suffer for beating LBSU and WSU. The RPI is a mish-mash of results, where sometimes winning hurts (but you knew this). The thing is, almost everybody has games against weak teams on their schedule and feels this effect to some degree.

And this effect might not be so bad. One point to consider is this: how would you replace the stinker teams on the schedule? One way is to schedule a non-D1 team, a game that won’t even exist is the eyes of the NCAA. Supposedly the committee frowns on such tactics, but to what degree who knows. The other option is to schedule a better team.

The problem is, the better the team you play, the more likely you are to lose, and a loss will certainly hurt your RPI. Gonzaga’s loss to #82 San Diego had as much negative impact as their win against LBSU. Had they scheduled anyone worse than #82 and lost, the effect would have been worse than the win against LBSU. And the risk of losing to a team ranked 101-200 is twice that of playing someone ranked 201 or higher. Teams ranked 40-60 in the RPI – the bubble teams – were 130-13 (.909 win %) against teams ranked 201+ in the RPI, but they were 146-36 (.802) against teams 101-200.

So in exchange for playing a nearly risk-free game, why shouldn’t a team be penalized? True, sometimes one can’t anticipate just how bad a scheduled team will be in the upcoming year. But for the most part, I’d say a team knows when they’re scheduling a win. And a few teams seem to do this better than others (I’m looking at you Georgetown, Virginia, and Pitt). A little incentive to avoid this practice isn’t a bad thing.

There are some improvements that could be made to the formula to make it more fair to teams that can’t help playing bad teams because of conference affiliation. Add margin of victory, or throw out the games against the 1 or 2 (or more) worst rated teams on the schedule. But any change would make a simple formula more complicated. The best thing the RPI has going for it is its simplicity. And unlike the BCS, the RPI is only a tool that humans use to make their own decisions, so whether Gonzaga finished 43rd or 38th wasn’t a big deal.

Next week: The effect of not acknowledging home court advantage.