Why can averages distort tips? Important concepts in betting
The most popular method of processing data in betting is the use of averages, but is it the most useful method? Modus and median are often the best alternative, so understanding them is crucial to the success of bets.
The problem of average scores for players in bookmakers’ offices
Because of simplicity, many players use average scores to evaluate the team in statistical terms. But how many people are aware of the limitations of this method?
For example, by betting on the total number of goals scored in football, players can assume that by calculating the average number of goals scored in previous games, they can predict the exact number of goals expected in the upcoming match. But is it really appropriate to use the average score here?
As an example, let’s look at the number of goals scored in the English Premier League compared to the Spanish example in the 2013/2014 season. The average number of goals per game in these leagues was 2.77 and 2.75 respectively. These data may lead the player to believe that in the La Liga, matches are played more often for total less than 2.5 than in submarines. However, this is not the case – 48.4% of the matches in the submarine submarines end at TM2.5, compared to 47.3% in the Example.
Although the overall distribution of the number of goals is similar, submarines most often score two goals per match, and in the Example this figure is 3 goals, as can be seen in the picture below. The average indicator masks and hides this fact from us.
Why is this happening? Although the averages give us an overall picture of performance, they do not show how the goals are distributed.
Another example of the danger of using average scores is when betting on handicaps in dwarf football matches, which are considered boys for each qualifying round. But are they as bad as they look? The average number of goals in their matches can be high, but this figure can be the result of rare but very large losses to the team. As a result, players make mistakes, often overestimating the expected number of goals in the match.
Below we will consider the alternatives to the average score – modus and median – and use three sets of numbers and two scenarios in which the average score does not provide adequate information.
First scenario: presence of deviations to a lesser or greater extent
Although all three sets have the same arithmetic mean and the sum of the numbers in each set is 25, they have a completely different distribution.
Set A can be called symmetrically distributed. Two numbers out of five have the same deviation from the average in both directions: 4 less than 5 and 6 more than 5 by the same value.
The mean value is ideal for use in cases of symmetrical distribution, when deviations from the mean value are the same and occur equally often, and the mean value is in the middle of the set of values.
In contrast to this distribution, Set B has four numbers smaller than the average and only one higher. This can be called an asymmetric distribution.
When using a large database, players can check the suitability of the average score for analysis using other measurement methods – modus and median.
Second scenario: different distributions
The two sets in our example can be both symmetrically distributed but not equally distributed. For example, Set C is symmetrically distributed, as is Set A, because they have equal values above and below the mean and the deviation from the mean is the same in both sets.
However, although the average is arithmetic in both sets of 5, the use of an average is more appropriate for set A because it contains more numbers equal to the average. The difference between the two sets lies in the variance in the values of each set. Therefore, we have to measure this dispersion as well.
To do this, players must calculate the range and standard deviation. The range is the difference between the maximum and minimum values, it is not difficult to calculate the range. On the other hand, the standard deviation is a more complex parameter. In general terms, as applied to this article, this value reflects the change of values in the set relative to the average value.
Conclusion
By understanding the limitations of the averages, distortions and differences in dispersion, players will be in a better position to use these methods in forecasting.