Sannolikheter i fotbollsmatcher : -Kan man skapa användbara odds med hjälp av statistiska metoder?

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Betting under ordered forms has been around for a long time, but the recent increase in Internet betting and the large sums of money that are now involved makes it even more important for betting companies to have correct odds.


The purpose of the essay is to calculate probabilities for outcomes of football games using a statistical model and to see if you can find better odds than a betting company.

The data contains the 380 games from the 2004/2005 season and the variables form, head-to-heads, league position, points, home/away, average attendance, promoted team, distance and final league position from previous season.


After performing an ordered probit regression we only find the variable “form of the away team” to be significant at the 5 % level. We suspect the presence of multicollinearity and perform a VIF-test which confirms this. To fix this problem we perform a second ordered probit regression where a number of variables are combined to index variables. In the second regression we once again find only one significant variable. This time it is the variable “difference between home and away teams’ final league position”. A reason for the lack of significant variables could be the size of the data. A new model with five variables is examined and it results in four significant variables.


The calculated odds pick the correct result in 200, 203 and 198 out of 380 games respectively, compared to 197 out of 380 for Unibet. Betting one krona on the lowest calculated odds from the second model will result in a positive yield for season 2004/2005 when using Unibet’s odds.

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