While bookmakers are constantly improving their soccer prediction methods and trying to avoid paying out, we can still find flaws in their predictions. The question is how. There is no million dollar answer. However, there are two ways that will allow you to beat the bookies. One way is to analyze non-measurable match information. Another way is to improve the statistical prediction models used by bookmakers.
The first method requires you to analyze data such as match type or priority, which is not used in statistical models. Among the most prominent factors that can influence the outcome of a football match are:
- Match Type which can be an international/national league, a cup or a friendly match. Especially profitable for you are the cup finals, where the media picks out the favorites and better-informed punters can benefit from betting on the high-priced underdogs.
- Match priority. Each team has to define their priority for the next matches, since the resources of the team are limited. The European national cups are good examples for the best teams of low priority games.
- match time is important, as soccer predictions are often inaccurate at the beginning and end of the season.
- players injuries, illnesses and transfers especially in the cases of key players. Bookmakers’ odds are usually calculated before this information is available.
- european leagues – Predictable and unpredictable. The Italian, Norwegian, French and Spanish leagues are considered predictable. The unpredictable ones are the English and German leagues, especially at the beginning and end of the season.
- Other factors it’s pitch conditions, team managers, match attendance, weather conditions and, of course, sheer chance.
Analyzing all that information from each match would be a complicated and time-consuming task. The alternative is to use advanced statistical prediction methods, which are an improvement on bookmakers’ prediction models.
Why can your models be further improved? First of all, by carefully analyzing the bookmakers’ predictions, it is easy to notice that their models are based on average statistics. Low odds usually correspond to teams with high positions in the table and vice versa. It’s clear that the accuracy of his models suffers when team abilities change. So, by taking into account team skill dynamics, you can increase your profits by betting on high-priced underdogs.
Second, bookmakers’ models do not distinguish between the attacking and defensive strengths of football teams and do not take into account that football teams choose different strategies when playing at home or away. Once you learn to distinguish between attacking and defensive strengths, you will be able to easily predict the total number of goals and beat the bookies on under or over bets.
Statistical models that have been developed in recent years explain historical match outcomes in terms of changes in skills and strategy. Bookmakers do not use such advanced models. Properly designed and optimized time-dependent models can predict up to 70% of matches, outperforming bookmakers’ predictions whose accuracy is much lower.