Sports Betting: Standard Deviations Of Over/Under Margins By Total



Many of you may have wondered how accurate sportsbooks were when setting the over/under totals for the NBA, NFL, NCAAB, and NCAAF. In order to determine their accuracy levels, we must calculate the standard deviations for the game totals. Standard deviation is defined as the amount of variation or dispersion of a set of data values. A low standard deviation indicates that data points tend to be close to the average while a high standard deviation implies that data points are spread out over a wider range of values. Additionally, correlation is defined as the extent that two or more variables fluctuate together. A positive correlation suggests that these variables increase or decrease in parallel while a negative correlation shows the extent to which one variable increases as the other decreases. Based on these explanations, it would seem that the margin of error increases as more points are scored. Let’s take a look at standard deviations of over/under margins by total for the four aforementioned leagues, with the two variables being over/under sports betting totals set by sportsbooks and the subsequent variance in final game totals after the games have finished.

Standard Deviation In NBA Totals

A positive correlation of 0.33 was present between larger totals lines and variances in final game totals. While a correlation of 0.33 fails to provide statistical significance, there was a stark difference in games with totals under 200 points and games with totals over 200 points – the variance between the two is nearly a full point. Although this information is not enough to imply that game totals over 200 points should be avoided entirely, it does signal that lower totals under 200 points are more predictable than higher totals.

Standard Deviation In NCAAB Totals

The correlation doubled between NBA and NCAAB – 0.33 and 0.66 respectively. A correlation of 0.66 indicates a strong relationship between larger totals lines and larger variances in final game totals. Based on this analysis, it appears that as the over/under totals set up sportsbooks increases, the final game totals become less predictable as well. While lower game totals looked as if they had high variances as well, this may simply be due to a small sample size.

Standard Deviation In NFL Totals

The correlation between larger totals lines and variances in final game totals was calculated to be -0.02. This figure allows us to conclude that a significant correlation in NFL totals fails to exist. As a result, final game totals tend to be clustered more closely to the over/under totals lines set by sportsbooks before the game. Since there is less variance in the NFL, this makes for better teaser opportunities.

Standard Deviation In NCAAF Totals

Similar to NCAAB, the correlation between large totals lines and variances in final game totals was computed to be 0.60. This correlation figure indicates a solid relationship – the higher the totals lines set by sportsbooks, the higher the variance in the actual outcomes of game totals. From the analysis, it was also evident that for game totals exceeding 54 points, the variance was one-and-a-half points larger than game totals below 54 points.

Conclusion

Based on the data analysis of the four leagues, the results revealed that college sports were much less predictable than professional sports. This is likely due to the fact that the skill and talent levels of college players tend to encompass a much wider range compared to professional athletes who have already made it to the big leagues. As a result, the higher unpredictability of college sports may, at least in part, be attributed to the larger variations in skill and talent levels as well.