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  • Majdi Awad ,
  • Reem Abdel Halim ,
  • Ismail Bardawil
Majdi Awad
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Reem Abdel Halim
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Ismail Bardawil
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Despite the prevalence and success of prediction algorithms in several areas, most notably medicine, climate and geology, their successes in the field of football are still very modest, and this is completely logical. The outcome of the match depends on a large and varied human effort, as it is not limited to the level of the two competing teams, but politics and economics play a very important role, especially in major tournaments such as the World Cup held in Qatar.
In this paper, we will propose mathematical methods to predict the results of football matches in general, according to a number of data and information.
Financial institutions including Goldman Sachs, UBS and ING have not been able to predict the winner of the last two World Cups, although Liberium Capital made an exception after Joachim Clement’s algorithm figured out the winner of the previous two World Cups. But Joachim Clement told the Financial Market Watch news site that his model determines only 45 percent of a team’s chances of winning the championship, while the remaining 55 percent is sheer luck.
We do not seek in this paper to leave an opportunity for luck, we will develop a number of different mathematical equations, each of which serves a form of football matches. Then we will programmatically formulate these mathematical equations to create applications capable of picking the winning team.
We believe that mathematics is the language of the universe and we will speak this language simply to determine the winning team in any football match.
Note: our test case will be all matches in QATAR 2022 world-Cup.