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Fusion: Practice and Applications
Volume 15 , Issue 2, PP: 132-144 , 2024 | Cite this article as | XML | Html |PDF

Title

Online Game Outcome Prediction Model Using Weighted-Based Feature Approach

  M. Asyhraf Zamir Zamri 1 ,   Nurul Aswa Omar 2 * ,   Isredza Rahmi A. Hamid 3

1  FAC. of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, MALAYSIA
    (asyhraf18@gmail.com)

2   FAC. of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, MALAYSIA
    (nurulaswa@uthm.edu.my)

3   FAC. of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, MALAYSIA
    (rahmi@uthm.edu.my)

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Doi   :   https://doi.org/10.54216/FPA.150212

Received: August 12, 2023 Revised: December 25, 2023 Accepted: April 15, 2024

Abstract :

Recently, the popularity of online games has risen drastically due to the latest technology that can connect players globally. League of Legends (LoL) holds the title of being the most extensively played Multiplayer Online Battle Arena (MOBA) game globally. This issue compels a substantial volume of preceding research that still analyzes and predicts the game outcomes with traditional methods that can be inaccurate and imprecise. Furthermore, these methods are frequently associated with the high rates of both false positive and false negative results. Hence, this paper presents a weighted-based feature predictor model to enhance the prediction accuracy. The approach predicts the game outcome of League of Legends matches in the Latin America North (LAN) and North America (NA) regions. We utilize player mastery and win rate for each summoner as the features. The data preparation process includes a weighted algorithm calculation and then evaluation using Naïve Bayes and Support Vector Machine algorithm. The outcomes illustrate that the weight-based feature approach can predict the outcome of LoL matches with an average accuracy of over 97 percent. This approach can be a valuable technique for players, teams, and coaches to analyze their performance and make strategic decisions.

Keywords :

Weighted based; Prediction Model; Player Mastery; Player Win rate; League of Legends.

 

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Cite this Article as :
Style #
MLA M. Asyhraf Zamir Zamri , Nurul Aswa Omar , Isredza Rahmi A. Hamid. "Online Game Outcome Prediction Model Using Weighted-Based Feature Approach." Fusion: Practice and Applications, Vol. 15, No. 2, 2024 ,PP. 132-144 (Doi   :  https://doi.org/10.54216/FPA.150212)
APA M. Asyhraf Zamir Zamri , Nurul Aswa Omar , Isredza Rahmi A. Hamid. (2024). Online Game Outcome Prediction Model Using Weighted-Based Feature Approach. Journal of Fusion: Practice and Applications, 15 ( 2 ), 132-144 (Doi   :  https://doi.org/10.54216/FPA.150212)
Chicago M. Asyhraf Zamir Zamri , Nurul Aswa Omar , Isredza Rahmi A. Hamid. "Online Game Outcome Prediction Model Using Weighted-Based Feature Approach." Journal of Fusion: Practice and Applications, 15 no. 2 (2024): 132-144 (Doi   :  https://doi.org/10.54216/FPA.150212)
Harvard M. Asyhraf Zamir Zamri , Nurul Aswa Omar , Isredza Rahmi A. Hamid. (2024). Online Game Outcome Prediction Model Using Weighted-Based Feature Approach. Journal of Fusion: Practice and Applications, 15 ( 2 ), 132-144 (Doi   :  https://doi.org/10.54216/FPA.150212)
Vancouver M. Asyhraf Zamir Zamri , Nurul Aswa Omar , Isredza Rahmi A. Hamid. Online Game Outcome Prediction Model Using Weighted-Based Feature Approach. Journal of Fusion: Practice and Applications, (2024); 15 ( 2 ): 132-144 (Doi   :  https://doi.org/10.54216/FPA.150212)
IEEE M. Asyhraf Zamir Zamri, Nurul Aswa Omar, Isredza Rahmi A. Hamid, Online Game Outcome Prediction Model Using Weighted-Based Feature Approach, Journal of Fusion: Practice and Applications, Vol. 15 , No. 2 , (2024) : 132-144 (Doi   :  https://doi.org/10.54216/FPA.150212)
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