Razvoj sustava upravljanja nogometnim timovima korištenjem metoda strojnog učenja

master's thesis

• Title (english): Development of football team management system using machine learning methods
• Author: Anđelko Nikić
• Mentor: Mirjana Pejić Bach (mentor)
• Committee member: Mirjana Pejić Bach (predsjednik povjerenstva)
• Committee member: Tomislav Globan (član povjerenstva)
• Committee member: Nikola Vlahović (član povjerenstva)
• Granter: University of Zagreb; Faculty of Economics and Business; (Department of Informatics); Zagreb
• Defense date and country: 2024-03-01, Croatia
• Scientific / art field, discipline and subdiscipline: SOCIAL SCIENCES; Economics; Business Informatics

Abstract

Sport je najpopularnija vrsta zabave na svijetu, a nogomet najpopularniji od svih. On se kroz godine razvija u svim segmentima: taktički, strategijski, tehnički i fizički. Za taj razvoj zaslužna je i tehnologija koja dobiva sve više pažnje. Cilj ovoga rada je približiti čitatelju nogomet i tehnologiju koja koristi izvan terena i na terenu. U prvome dijelu ovoga rada stavljen je naglasak na svojevrsnu suradnju tehnologije i nogometa. Kreće se od najstarije upotrebe pa sve do složenih analiza i metoda strojnog učenja. Navedeni su i objašnjeni sustavi kojima se koriste nogometni timovi kako bi stekli konkurentsku prednost. U drugome dijelu rada govori se o značenju otkrivanja znanja u bazama podataka, u kojim se još industrijama ta znanstvena disciplina koristi te zašto je tako važna za svijet u kojem živimo. Prikazane su i razne metode otkrivanja znanja iz baza podataka, među njima i klaster analiza koja će biti iskorištena kasnije u istraživanju. Za kraj je ostavljeno autorsko istraživanje koje se temelji na bazi podataka koja sadrži podatke o nogometnim momčadima koje se natječu u najboljih 5 liga na svijetu u sezoni 2021.-2022. Radi se o podacima kao što je broj zabijenih golova, broj dobivenih žutih i crvenih kartona, posjed lopte i dr. U dva navrata korištena je metoda klasteriranja odnosno klaster analiza. Zaključak rada je taj da je engleska Premier liga najbolja i najgledanija liga s razlogom te da najbolje nogometne ekipe igraju nogomet visokog intenziteta, vrlo napadački te da nastoje čuvati loptu u svome posjedu što je duže moguće.

Abstract (english)

Sports are the most popular form of entertainment in the world, and football is the most popular of all. Over the years, he has developed in all segments: tactical, strategic, technical and physical. Technology, which is receiving more and more attention, is also responsible for this development. The aim of this work is to bring football and the technology it uses off the field and on the field closer to the reader. In the first part of this paper, emphasis is placed on a kind of cooperation between technology and football. It ranges from the oldest usage all the way to complex analysis and machine learning methods. The systems used by football teams to gain a competitive advantage are listed and explained. The second part of the paper talks about the meaning of discovering knowledge in databases, in which other industries this scientific discipline is used and why it is so important for the world in which we live. Various methods of discovering knowledge from databases are also presented, among them cluster analysis, which will be used later in the research. Finally, author's research based on a database containing data on football teams competing in the top 5 leagues in the world in the 2021-2022 season is left. This is data such as the number of goals scored, the number of yellow and red cards received, possession of the ball, etc. On two occasions, the method of clustering or cluster analysis was used. The conclusion of the paper is that the English Premier League is the best and most watched league for a reason and that the best football teams play high-intensity, very attacking football and try to keep the ball in their possession as long as possible.

• Keywords: nogomet; tehnologija; otkrivanje znanja u bazama podataka; klaster analiza; rudarenje podataka
• Keywords (english): football; technology; knowledge discovery in databases; cluster analysis; data mining
• Language: croatian
• URN:NBN: urn:nbn:hr:148:364603
• Study programme: Title: Business economics; Study programme type: university; Study level: integrated undergraduate and graduate; Academic / professional title: sveučilišni magistar ekonomije/sveučilišna magistra ekonomije (sveučilišni magistar ekonomije/sveučilišna magistra ekonomije)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2024-03-04 12:23:38