Olympic games are one of the most known and followed events in the world. The first Olympic games were held in Greece in 776 a.C. in the city of Olimpia and consisted of a single running race among the local population. Nowadays every four years, the best athletes of the world compete in all the principal sports practiced in the five main continents. Due to the prestige associated with this event, all of the participating countries are interested in conquering the higher medal count, guaranteeing a professional preparation to their athletes and sometimes also giving them monetary prizes in case of success. Since the end of the 60’, it was considered of great interest to understand if the macro variable could explain the number of medals won by each country, finding out that population and GDP were the main factors that contributed to the Olympic triumphs. In recent years, macro variables seem to give worse results compared to the past. The objective of this thesis is to understand if there are new macro variables that can predict the number of medals won by each nation during the Olympic games and deepen the analysis considering the differences in gender by creating three clusters: Female, Male and aggregated genders. Three Olympic Games editions, 2004, 2008 and 2012 have been used as training set, the 2016 edition instead, as testing set. Tobit and Multiple Linear Regression’s predictions have been compared together with the reference research of Bernard and Busse (2000). The models eventually have been evaluated through MAE and accuracy to determine the best model for all of the clusters.
I giochi Olimpici sono uno degli eventi più conosciuti e seguiti al mondo. I primi giochi Olimpici si svolsero in Grecia nel 776 a.C. nella città di Olimpia e all’epoca consistevano in una singola gara di corsa che veniva disputata tra la popolazione locale. Oggi, ogni quattro anni, i migliori atleti del mondo competono tra di loro in tutte le principali discipline praticate nei 5 maggiori continenti. Per via del prestigio associato a questo evento, tutti gli stati partecipanti sono interessati nel conquistare il maggior numero di medaglie, garantendo una preparazione professionale ai propri atleti e a volte anche dando loro primi in denaro in caso di successo. Dalla fine degli anni 60’ fu considerato di grande interesse comprendere se le macro-variabili potessero spiegare il numero di medaglie vinte da ciascuna nazione, scoprendo che la popolazione e il PIL erano i principali fattori che contribuivano ai trionfi Olimpici. Negli ultimi anni, le macro variabili sembrano avere un comportamento peggiore rispetto al passato. L’obiettivo di questa tesi è capire se esistono nuove macro variabili capaci di predire il numero di medaglie vinte da ogni nazione durante i Giochi Olimpici e approfondire l’analisi considerando differentemente i generi creando tre cluster: donne, uomini e l’insieme dei due precedenti. Le tre edizioni Olimpiche del 2004, 2008 e 2012 sono state utilizzate come training set, quella del 2016 invece come testing. Le previsioni effettuate tramite Tobit e regressione Lineare Multipla sono state comparate con la ricerca di riferimento di Bernard & Busse del 2000. I modelli infine sono stati valutati attraverso il MAE (Mean Absolute Error) e l’Accuracy ( percentuale di previsioni esatte) per determinare il miglior modello per tutti i cluster.
Predicting Olympic Games : do macro variables still matter ? Insight from a prediction model applied to both genders
TAMAGNI, LUCA
2019/2020
Abstract
Olympic games are one of the most known and followed events in the world. The first Olympic games were held in Greece in 776 a.C. in the city of Olimpia and consisted of a single running race among the local population. Nowadays every four years, the best athletes of the world compete in all the principal sports practiced in the five main continents. Due to the prestige associated with this event, all of the participating countries are interested in conquering the higher medal count, guaranteeing a professional preparation to their athletes and sometimes also giving them monetary prizes in case of success. Since the end of the 60’, it was considered of great interest to understand if the macro variable could explain the number of medals won by each country, finding out that population and GDP were the main factors that contributed to the Olympic triumphs. In recent years, macro variables seem to give worse results compared to the past. The objective of this thesis is to understand if there are new macro variables that can predict the number of medals won by each nation during the Olympic games and deepen the analysis considering the differences in gender by creating three clusters: Female, Male and aggregated genders. Three Olympic Games editions, 2004, 2008 and 2012 have been used as training set, the 2016 edition instead, as testing set. Tobit and Multiple Linear Regression’s predictions have been compared together with the reference research of Bernard and Busse (2000). The models eventually have been evaluated through MAE and accuracy to determine the best model for all of the clusters.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/154460