Date: 06.09.2022     Day: Tuesday

League: EUROPE Champions League – Group Stage
Match: RB Leipzig vs  Shakhtar Donetsk
Odds: 1.35     Fulltime 1:4


Date: 06.09.2022     Day: Tuesday

League: EUROPE Champions League – Group Stage
Match: Salzburg vs  AC Milan
Odds: 2.00     Fulltime 1:1


Date: 06.09.2022     Day: Tuesday

League: EUROPE Champions League – Group Stage
Match: Benfica  vs  Maccabi Haifa
Odds: 1.40    Result: 2:0


Date: 06.09.2022     Day: Tuesday

League: EUROPE Champions League – Group Stage
Match: Sevilla  vs  Manchester City
Tip: OVER 2.5 goals
Odds: 1.65    Result: 0:4

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Gambling sure manipulated games

Betting on RESEARCHED FIXED SOCCER MATCHES  is one of the most popular soccer markets for recreational bettors. In this article betting expert Joseph Buchdahl analyses correct score betting using “true” score odds. Is correct score betting profitable ? Read on to find out.

Whenever I walk past a bookmaker on my RESEARCHED FIXED SOCCER MATCHES I am always met with an enticing offer of a correct score bet to lure me into the shop. Typically, such offers will say something like “Tottenham to win 2-0 pays £100 for a £10 stake”.

Whilst the rewards look attractive, these adverts do not exist for the benefit of the customer. Rather, they hide what the bookmakers know is a large advantage for them. This article will investigate just how large that advantage really is.

Correct score betting

A popular market in football betting is predicting the final score of a game. Unlike straight match odds for which there are just three possible outcomes – home, draw or away – there are many more possible scores.

Bookmakers will typically limit the number of correct score odds to a maximum number of goals per team. If we call that number n, the maximum number of possible scores quote by the bookmaker is then given by the formula (n+1)2. For example, games that finish with anything from 0 to 6 goals for either team can have 49 possible scores.


Unsurprisingly, the odds for correct score betting are considerably longer than the match odds. That is because each possible score has a much lower chance of happening than just a straight home, draw or away result. Even the most common scores – 1-1, 1-0 and 2-1 – have all occurred less than 12% of the time throughout English football league history.

Betting correct scores 


In June 2016 I wrote about something called the favourite–longshot bias. This is the tendency for bettors to overvalue (and over-bet) longshots and undervalue (and under-bet) favourites. Because we are rather poor at assessing true probabilities, particularly for events that have either a very low or very high probability of outcome, we will readily wager too much money on things that have little chance of happening and not enough on things that are very likely to happen.

At the same time, bookmakers must protect themselves against the possibility of large payouts, particularly when prediction errors for lower probability outcomes can have a much greater impact (as we will see later in the article). As a consequence, they will shorten prices for longshots considerably more than for favourites when applying their margin.

Modelling correct scores


In April 2017, fixedmatches.cc author Benjamin Cronin showed us how to use the Poisson distribution to predict the correct score of a football match.

Whilst not a perfect model for predicting correct scores (it considers home and away goals as independent whilst in reality they will not be) it does a pretty reasonable job of simulating score probabilities which closely correlate with actual result frequencies. Specifically, Ben looked at the game played between Tottenham and Everton during the 2016/17 Premiership campaign.

By looking at games the two clubs had played the season before, Ben’s model predicted Tottenham would score 1.623 goals. Obviously, this is an absurdity; teams don’t actually score fractions of goals. Statistically, however, this is telling us is that Tottenham could be expected to score an average of 1.623 goals if playing many games at home against a team as strong (or weak) as Everton.

Rigged football results 

Comparing modelled and actual betting odds

How do these ‘true’ correct score odds compare to actual published odds for that game? The average market prices as recorded by the odds comparison Oddsportal.com are shown below.

The theoretical margin for this book is 40%. A casual comparison of this table with the ‘true’ odds above reveals that as the score becomes less likely, the actual odds start to deviate significantly from the ‘true’ ones. Clearly, just as for match odds, the bookmaker does not apply his margin equally across all outcomes. The less probable the outcome, the larger the specific margin weight for that score.

Best market odds. The theoretical margin for the best prices that were available is still 14%.

The Favourite–Longshot Bias and correct score betting

The simplest way to estimate the strength of the specific margin weight applied by the bookmaker for each score is to divide the actual odds by the modelled ‘true’ odds.

For example, the 0-0 score had an average RESEARCHED FIXED SOCCER MATCHES of 11.23. Dividing this by the modelled price for the RESEARCHED FIXED SOCCER MATCHES – 11.55 – gives a figure of 97.2%. This is equivalent to the expected return on investment (ROI) a bettor could expect to make. For every $100 wagered, he would expect to return $97.20 or lose $2.80.