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Title:Primeri uporabe podatkov iz velikih baz v nogometu : diplomsko delo
Authors:ID Koren, Marcel (Author)
ID Bratina, Tomaž (Mentor) More about this mentor... New window
Files:.pdf VS_Koren_Marcel_2023.pdf (973,89 KB)
MD5: 3C7D04B54A6AE6A8D3664F4D3D5CF806
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:PEF - Faculty of Education
Abstract:V svetu športa je nenehno izobraževanje pri trenerskem poklicu neizbežno, saj le tako ti kot strokovni delavec in tvoja ekipa neprestano napredujeta in ne zaostajata za konkurenco. Ne glede na raven športnega udejstvovanja, si lahko s pregledom aktualnih znanstvenih raziskav pridobimo nova znanja. Predstavili smo mnoga spoznanja iz strokovnih del, ki so privedla do korenitih sprememb v nogometni igri. Z neučinkovitostjo strelov z razdalje se je temu prilagodil slog nogometne igre (Harper, 2021) . Čeprav se je povišala intenziteta obremenitev v zadnjih letih (Bush, Barnes, Archer, Hogg, & Bradleya, 2015) se je zmanjšalo število poškodb (Henriques, 2018) . Moč je opaziti višji odstotek natančnosti podaj (McKenna, 2017) , zmanjšal se je čas nogometaša na žogi (igralec je med igro 98,8 % časa brez žoge (Di Salvo, 2007) in mnogo več. Potrebno je poudariti, da obstaja nepredstavljivo velik razkorak med neprofesionalno in profesionalno ravnjo, ne zgolj s finančnega vidika, ampak tudi med količino in dostopnostjo informacij o lastnih igralcih, medsebojni primerjavi ekip, zunanjih dejavnikih, nogometnem tržišču in navijačih, vendar izhodišča in spoznanja lahko delno uporabimo tudi na amaterskem nivoju. Naloga je predstavljena iz analitičnega in statističnega razmišljanje na karseda zanimiv in praktičen način. Dandanes se v nogometnem svetu popolnoma nič ne prepušča golemu naključju.
Keywords:nogomet, šport, baza podatkov, statistična analiza
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[M. Koren]
Year of publishing:2023
Number of pages:1 spletni vir (1 datoteka PDF (X, 49 str.))
PID:20.500.12556/DKUM-85751 New window
UDC:796.332:004.65(043.2)
COBISS.SI-ID:176980995 New window
Publication date in DKUM:12.12.2023
Views:762
Downloads:53
Metadata:XML DC-XML DC-RDF
Categories:PEF
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:10.09.2023

Secondary language

Language:English
Title:Big Data Use Case Examples In Football
Abstract:In sports, constant education in the coaching profession is inevitable, assuming that a professional worker and his team do not want to lag behind the competition. Regardless of the level of sports participation, we can gain new knowledge by reviewing current scientific research. We presented many findings from professional works that led to radical changes in the football game. Because of the ineffectiveness of shots from a distance, the style of football has adapted. Although the intensity of activities has increased in recent years, the number of injuries has reduced. The soccer player's time spent on the ball has decreased (the player is without the ball 98.8% of the time during the game). It should be emphasized that there is a large gap between the non-professional and professional levels, not only from a financial point of view but also between the amount and availability of information about own players, comparison of teams, external factors, the football market, and fans, but starting points and insights can be partly also used at the amateur level. The dissertation is presented from an analytical and statistical point of view in a very attractive and practical way.
Keywords:football, sport, big data, statistical analysis


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