Στατιστικά μοντέλα για την ανάλυση της απόδοσης των ομάδων στο παγκόσμιο κύπελλο ποδοσφαίρου
Statistical models for the performance analysis of teams in the FIFA World Cup
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Keywords
Ποδόσφαιρο ; Παγκόσμιο κύπελλο ποδοσφαίρου ; Στατιστική ανάλυση ; Μηχανική μάθηση ; Γενικευμένα γραμμικά μοντέλαAbstract
Statistical analysis and data science have emerged
as crucial tools in many areas of human activity in recent years. Thanks
to advancements in technology and computing power, we can now process and
analyze large volumes of data with speed and precision. These capabilities
have enabled the development of more sophisticated methods of prediction
and decision-making, which also find application in sports. In football,
the use of statistical analysis and data analytics has revolutionized how
teams prepare and compete. From analyzing player and team performance to
predicting match outcomes, data utilization has become an integral part of
the modern approach to the sport. Coaches, analysts, and scouts use
advanced tools to identify opponents' weaknesses, improve their
strategies, and maximize their teams' performance. This thesis focuses on
analyzing the factors that influence the success of national football
teams in the World Cup from 2012 onwards. Through the use of statistical
models and machine learning techniques, it explores the characteristics
that contribute to a team's successful trajectory, the factors that
differentiate winners from losers, and potential changes in how teams
approach matches over the course of the tournaments. The findings of this
research provide valuable insights into the factors that influence match
outcomes and team progress, enhancing the understanding of the game and
effectiveness in such a competitive field as the World Cup.