Analysis of Afl Results for Years 2016 and 2017 Using Elo Models
Keerthi Prasad K1, NithyaPreetha2, Gokul Prasad K3, P.S.Rajeswari4
1Er. Keerthi Prasad. K, Research Scholar, RMIT, Australia.
2Dr.NithyaPreetha P, Assistant, Professor, Faculty of Management, SRM Institute of Science and Technology,Kattankulathur,TamilNadu,India.
3Gokul Prasad.K,Research Scholar,VIT.
4Dr.P.S.Rajeswari, Assistant Professor, Faculty of Management, SRM Institute of Science andTechnology,Kattankulathur,TamilNadu,India,603203.
Manuscript received on 02 June 2019 | Revised Manuscript received on 10 June 2019 | Manuscript published on 30 June 2019 | PP: 341-349 | Volume-8 Issue-8, June 2019 | Retrieval Number: H6352068819/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The research consists of the score data analysis for the years 2016 and 2017. The research reveals interesting analysis of ELO models based ratings and their consistency. ELO ratings only focus on team-level outcomes and not on individual players. AFL and its sister sites for generating ELO ratings for individual players. However, it may be possible to use various ELO models show facts on accuracy between different models based on the comparison between the models.
Keyword: ELO models, Optimize, Exploration, Comparison
Scope of the Article: Predictive Analysis