In a game that has less scoring, it would make sense that oddsmakers would be more accurate on the lines. The less total points scored by either team should make it much easier to determine the final score.

The more accurate the line is at certain totals could be a great resource in several different ways.

If oddsmakers are more accurate with a lower total, then you could have a huge advantage with a teaser. If they aren’t accurate on higher totals then it would make sense to avoid teasers.

Look at How Accurate Oddsmakers Are With ATS Margins Based on Total

That is the theory anyway, but below are the results from our research. First, let’s take a closer look at some of the elements of our research.

Explanation of Terms

Standard deviation is a measure of how spread out numbers are, or how far they are from the mean. It tells you how tightly all the various examples are clustered around the average in a set of data.

Here is an example:

Let’s say Springfield Elementary has a higher mean test score than Shelbyville Elementary. Your first reaction might be to say that the kids at Springfield are smarter.

But a bigger standard deviation for one school tells you that there are relatively more kids at that school scoring toward one extreme or the other. By asking a few follow-up questions you might find that, say, Springfield’s mean was skewed up because the school district sends all of the gifted education kids to Springfield. Or that Shelbyville’s scores were dragged down because students who recently have been “mainstreamed” from special education classes have all been sent to Shelbyville.

In this way, looking at the standard deviation can help point you in the right direction when asking why information is the way it is. RobertNiles.com

You will also find a correlation number listed below each table. This number informs us how effective the total is at determining the standard deviation. This number will always come between +1 and -1. A number of +0.5 or less than -0.5 would indicate a strong linear relationship.

Here’s a quick example to help better understand. Let’s say your local pool tracked how many customers they have based on the temperature. They could determine what days will be busier than others assuming there is a correlation. More customers as the temperature increases would be a strong indication of a positive correlation between the number of customers and the temperature.

Basketball & Football Score Variability Using Standard Deviation Chart

We are displaying the results of our research in the form of scatter charts. This should help you visualize the data.

In terms of a strong correlation, you would want to see the data points clustered in a rising line. The more spread out the data points, the weaker the correlation.

Standard Deviation in NFL Games

Correlation: 0.22

There is a slight correlation between ATS margin standard deviations and totals, but not a statistically significant one.  That means the accuracy on predicting the final scoring margin from oddsmakers is random in relation to the size of the total in NFL games.

Standard Deviation in College Football Games

Correlation: 0.35

Again, we have a correlation that is insignificant statistically with college football totals and the standard deviation of ATS margins.  However, there are some outliers in college football.  When the total gets above 61 points, the average standard deviation of ATS margins is 15.61, while it is 14.32 when the total is set between 40 to 50 points.  This does indicate slightly less accuracy from the oddsmakers on the final scoring margin as the total increases.

Standard Deviation in NBA Games

Correlation: 0.17

In the NBA games with extremely low totals of 180 points or less are much closer in ATS margin than the games where the total is set over 201.5 points.  However, there is not a significant difference in the data set as a whole.  The correlation in NBA games is the lowest among the four major sports being measured.

Standard Deviation in College Basketball Games

Correlation: 0.46

The correlation in college basketball was greater than any other sport.  Basically this means there is a gradual increase in the volatility of ATS margins as the total increases. It is not a drastic increase, but definitely something worth noting.

Conclusions

There is not a lot of correlation between expected ATS margins and the total. Unfortunately, there’s nothing that stands out as a great statistical advantage.

In general, lower totals do tend to have less variance. However, the relationship between the size of the total and amount of variance in the ATS margin is statistically insignificant.

While it may seem like nothing can be gained from this data, that is not entirely the case. We now know that regardless of the total, the ATS margin should not change much. That tells me the oddsmakers are just as good at predicting the outcome of high scoring games as they are in lower scoring games.

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