College Basketball Power Index Betting System

By Adam, NCAA Basketball Handicapper, Predictem

There is a betting system for college basketball and it requires using data called the Basketball Power Index (or BPI). These stats are numbered 1 through 100, with 100 being the best, and are calculated using wins, pace of play, scores, venue, player injuries, and strength of schedule to basically quantify how good a team is. You can find them for the teams in the previous season on

What we want to focus on is the average opponent’s power index (AOPR) for our given team(s). We do this by averaging out all of the Indexes of the opponents the team has played. Also called AOPR (average opponent player rating) or a variation of strength of schedule, this number can be found in a variety of places including sportsbooks, albeit they sometimes use a different index for the rating, but it will still be on the 1-100 scale so you can experiment with your sources.

We will also need the average points scored for and against the teams we are evaluating. These can be found in most places or easily calculated by adding up the scores and dividing by the number of games played.

The first step is to divide the higher AOPR of the teams in your matchup by the lower team’s AOPR. This produces in effect how much harder the higher team’s schedule has been and will be a small percentage. For instance, let’s say Rutgers has an AOPR of 90 and Villanova has an AOPR of 81. 90 divided by 81 equals 1.11, so Rutgers has an 11% harder schedule than Villanova.

Next, we take each team’s average points scored for and divide it by the median score in all of college basketball (use 71 points). If Rutgers scored an average of 68 points, we divide 68 by 71 to get .958. If Villanova scored an average score of 76 points, we divide 76 by 71 and get 1.07.

Now, since Rutgers had a harder schedule, we increase their rating we just calculated by 11% and get 1.064. For Villanova, we decrease their rating by 11% and get .952.

Finally, to get our anticipated points, we need average points allowed for each team. Then we multiply the preceding numbers by average points ALLOWED by the opponent we are looking at. For Rutgers, assume Villanova allows 70 points. We multiply 1.064 by 70 and get our predicted score of 74. Assuming Rutgers allows, say, 65 points, we find Villanova’s anticipated score by multiplying 65 by 1.07 to get 70 points. The anticipated score is Rutgers 74 – Villanova 70. But there is one last thing we must do, which is account for home team advantage. To do that, add 2 points to the home team and subtract 2 for the away team. If Rutgers is home, we can anticipate a score of Rutgers 76 – Villanova 68.

As with all betting systems, do not see it as foolproof, and never bet over your head. Also, they are more indicative of success the larger the sample size is, in both data, and bets made using the system. So it actually pays off (hopefully, literally) to place many bets at a time using the system to eliminate the variance of a small sample size.

So, here it is for quick reference, condensed for ease of reading:

1. Need to look up: Each team’s AOPR, average points for, average points against.

2. Team A will be team with higher AOPR than their opponent Team B.

3. Divide A’s AOPR by B’s to get percent advantage.

4. Divide A’s and B’s average points for by the league median (71).

5. Take that number and increase A by the percent advantage (from step #3). Decrease B by the percent advantage (#3).

6. Multiply A’s outcome (from #5) with B’s average points against.

7. Multiply B’s outcome (from #5) with A’s average points against.

8. Add 2 points to the home team.

9. Subtract 2 points from the away team.

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