ANALYSING YOUR DATA - BASIC
When you run a basic level simulation you will receive a wealth of information on your screen. This article is to help you make sense of it all
and, hopefully, to use that information profitably. To illustrate the instructions, we will be looking at a fictional encounter between two
90-something ranked teams, Syria playing at home to El Salvador. This simulation has been run 49 times.
On the basic level simulation, you will see three tables of information which represent results information, averages and odds information.
The result information is presented in a similar format to the league tables that you should already be familiar with. The columns are as follows: Won, Drawn, Lost, Goals For and Goals Against. After these are the average goals for and against - rounded to the nearest 0.1 of a goal.
The averages section displays information on all three kinds of average: mean, median and mode. All three of these have their uses so here's a quick refresher course.
The mean is what you get if you add a list of numbers together and divide by the number of items in the list.
Consider the list 1,1,1,2,2,5,9 . If you add the seven numbers up, you get 21. Divide by seven and you get a mean of 3
The median is what you get if put you list of numbers in order and remove the highest and lowest until you are left with the number in the middle. The number of simulations you can run in FootySimulator is always an odd number so that there is always a number in the middle.
Consider the list 1,1,1,2,2,5,9 . If you remove the three highest and the three lowest numbers, you are left with a median of 2
The mode is the most common number, regardless of whether it is in the middle. It is possibly the most relevant of the three averages in FootySimulator as it represents the score which is most likely to occur rather than the middle or 'fairest' score.
Consider the list 1,1,1,2,2,5,9 . The most common number, or mode, is 1.
All of these averages have their merits so this summary screen displays all three, along with a percentage likelihood of the mode score happening. In the Syria-El Salvador example, there is nearly a 50% chance that El Salvador will not score. To assist you, an extra column recommendation appears. This will display a number for each team if the data from all the averages is is pointing to one score above all others. In this case, the recommendation for each team is none meaning that the data is too inconclusive to make a confident prediction. There are two reasons why this should be so in this particular case. Firstly the two teams were quite evenly matched and it is easier to predict the result of a one-sided game than a close one. Secondly, the simulation was only best of 49. The more times you run a simulation, the more accurate it will be as anything can happen in a one-off. To get simulations I can trust, I run them between 499 and 1999 times for each match. This level of detail is not available on the free site.
This section shows the odds that FootySimulator thinks the bookmakers should be offering based on the results it has processed. Bearing in mind my comments above about the accuracy level going up when more simulations are run (I would never invest money based on a best of 49 prediction) , what you should be doing here is comparing the odds bookmakers are offering with these figures.
In this particular example, Syria are being offered at 1.66 (or 4/6 in old money). So, as a sensible value better, you would only bet on them if you saw better odds such as 1.80 (4/5). Likewise, this table is telling you that El Salvador would be worth betting on if you were able to get odds better than 5.00 (4/1).
The final column is to assist spread betters. Spread betting firms usually offer markets on a team's goal superiority to 0.1 of a goal. In this case, FootySimulator believes Syria have a superiority of 0.8 goals (the 0.1 goals either side represents the Bookmaker's profit margin). In short you would be advised to back El Salvador if you were given a goal start and to back Syria if they were penalised 0.6 goals or less.
Note that the odds have been displayed in decimal rather than traditional form in this instance because, when they were run, the preferences were set to decimal odds. You can change your own preferences to toggle between decimal and traditional layout.
On the basic level simulation, you will see three tables of information which represent results information, averages and odds information.
How to analyse results information generated by our football simulations
| TEAM | W | D | L | F | A | AVF | AVV | |
| Syria | 29 | 11 | 9 | 81 | 42 | 1.7 | 0.9 | |
| El Salvador | 9 | 11 | 29 | 42 | 81 | 0.9 | 1.7 | |
The result information is presented in a similar format to the league tables that you should already be familiar with. The columns are as follows: Won, Drawn, Lost, Goals For and Goals Against. After these are the average goals for and against - rounded to the nearest 0.1 of a goal.
How to analyse averages generated by our football simulations
| AVERAGES | MEAN | MEDIAN | MODE | RECOMMENDATION | |
| Syria | 2 | 1 | 1 (34.6%) | none | |
| El Salvador | 1 | 1 | 0 (46.9%) | none | |
The averages section displays information on all three kinds of average: mean, median and mode. All three of these have their uses so here's a quick refresher course.
The mean is what you get if you add a list of numbers together and divide by the number of items in the list.
Consider the list 1,1,1,2,2,5,9 . If you add the seven numbers up, you get 21. Divide by seven and you get a mean of 3
The median is what you get if put you list of numbers in order and remove the highest and lowest until you are left with the number in the middle. The number of simulations you can run in FootySimulator is always an odd number so that there is always a number in the middle.
Consider the list 1,1,1,2,2,5,9 . If you remove the three highest and the three lowest numbers, you are left with a median of 2
The mode is the most common number, regardless of whether it is in the middle. It is possibly the most relevant of the three averages in FootySimulator as it represents the score which is most likely to occur rather than the middle or 'fairest' score.
Consider the list 1,1,1,2,2,5,9 . The most common number, or mode, is 1.
All of these averages have their merits so this summary screen displays all three, along with a percentage likelihood of the mode score happening. In the Syria-El Salvador example, there is nearly a 50% chance that El Salvador will not score. To assist you, an extra column recommendation appears. This will display a number for each team if the data from all the averages is is pointing to one score above all others. In this case, the recommendation for each team is none meaning that the data is too inconclusive to make a confident prediction. There are two reasons why this should be so in this particular case. Firstly the two teams were quite evenly matched and it is easier to predict the result of a one-sided game than a close one. Secondly, the simulation was only best of 49. The more times you run a simulation, the more accurate it will be as anything can happen in a one-off. To get simulations I can trust, I run them between 499 and 1999 times for each match. This level of detail is not available on the free site.
How to analyse betting information generated by our football simulations
| Match Odds | Price | Spread |
| Syria | 1.66 | 0.7 to 0.9 |
| Draw | 4.33 | |
| El Salvador | 5.00 |
This section shows the odds that FootySimulator thinks the bookmakers should be offering based on the results it has processed. Bearing in mind my comments above about the accuracy level going up when more simulations are run (I would never invest money based on a best of 49 prediction) , what you should be doing here is comparing the odds bookmakers are offering with these figures.
In this particular example, Syria are being offered at 1.66 (or 4/6 in old money). So, as a sensible value better, you would only bet on them if you saw better odds such as 1.80 (4/5). Likewise, this table is telling you that El Salvador would be worth betting on if you were able to get odds better than 5.00 (4/1).
The final column is to assist spread betters. Spread betting firms usually offer markets on a team's goal superiority to 0.1 of a goal. In this case, FootySimulator believes Syria have a superiority of 0.8 goals (the 0.1 goals either side represents the Bookmaker's profit margin). In short you would be advised to back El Salvador if you were given a goal start and to back Syria if they were penalised 0.6 goals or less.
Note that the odds have been displayed in decimal rather than traditional form in this instance because, when they were run, the preferences were set to decimal odds. You can change your own preferences to toggle between decimal and traditional layout.
