Publication
LoLChrono : League of Legends player chronological data
| datacite.subject.fos | Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática | pt_PT |
| dc.contributor.advisor | Afonso, Ana Paula Pereira | |
| dc.contributor.advisor | Carmo, Maria Beatriz Duarte Pereira do | |
| dc.contributor.author | Almeida, Pedro Manuel Petinga de | |
| dc.date.accessioned | 2024-12-04T15:51:27Z | |
| dc.date.available | 2024-12-04T15:51:27Z | |
| dc.date.issued | 2024 | |
| dc.date.submitted | 2024 | |
| dc.description | Tese de Mestrado, Engenharia Informática, 2024, Universidade de Lisboa, Faculdade de Ciências | pt_PT |
| dc.description.abstract | In the past years, the entertainment industry has focused more and more on the digital evolution of entertainment and through this the popularity of videogames has seen a rise. Consequently, the competitive side of videogames rose along with them. These videogames competitions, or esports for short, create a plethora of interest from many different stakeholders in the videogame industry. More specifically competitive videogame organizations have risen in the past years. These organizations go through several steps to guarantee the best possible results come from their matches. Therefor there is a big focus on analysing past matches to evolve throughout time with the mistakes and errors made by the players. The amount of data created from these games that requires analysis is huge and that deters many regular players from trying to convey knowledge from it, in professional teams, coaches and analysts take care of this process. In previous projects, our colleagues developed an application that focused on analysing multiple matches of League of Legends and infer helpful data for both players and their teams through multiple visualization and analysis techniques. We had the goal of analysing these previous projects and attempt to apply similar techniques to new games and datasets. To achieve this, we set out to build a dataset of games for a new game type, with the intention to replicate past studies. Unfortunately it was not possible to conclude the creation of the dataset, and therefore we looked once again back to League of Legends to create a web application that could focus on telemetry data from players of League of Legends. This prototype was built to facilitate the gathering and analysis of player telemetry data. Finally we decided to evaluate the usability of our application through the use of a testing group for which we used the System Usability Scale (SUS). | pt_PT |
| dc.identifier.tid | 203875419 | |
| dc.identifier.uri | http://hdl.handle.net/10400.5/95962 | |
| dc.language.iso | eng | pt_PT |
| dc.subject | Dados temporais de jogadores | pt_PT |
| dc.subject | Aplicações de web | pt_PT |
| dc.subject | Esports | pt_PT |
| dc.subject | Análise de dados de utilizadores | pt_PT |
| dc.subject | League of Legends | pt_PT |
| dc.subject | Teses de mestrado - 2024 | pt_PT |
| dc.title | LoLChrono : League of Legends player chronological data | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | Mestrado em Engenharia Informática | pt_PT |