Intelligent Cricket Team Selection by Predicting Individual Players' Performance using Efficient Machine Learning Technique
release_ntaqwtl67jfbzegolinnteszvi
2020 p3406-3409
Abstract
In any game, selection of best players in a team plays vital role in overall team performance. The team selection in any sport is the key task to ensure good performance of the team. Players are selected based on different criteria. In game of cricket selection of players should consider parameters like players own performance, ground condition, weather forecasting, opposition strength and weakness etc. Machine learning can play vital role in players' performance prediction. Machine learning uses historical data of team performance and past performance of individual players to predict overall performance of team. Prediction of individual player performance helps in team building process. Recently many researchers proposed model for prediction of player's performance for a game of cricket. Researchers' uses machine learning approach for prediction. However existing studies omits some vital features related to ground and weather in their study which have potential to make huge impact on player's performance. We performed detailed study and literature survey to propose efficient performance prediction of players for game of cricket. Our model will help in best team selection and thus improves overall team performance.
In application/xml+jats
format
Archived Files and Locations
application/pdf 412.4 kB
file_e3w3w5d3fjbkne2m5pap7iaihu
|
www.ijeat.org (publisher) web.archive.org (webarchive) |
Open Access Publication
Not in DOAJ
In ISSN ROAD
Not in Keepers Registry
ISSN-L:
2249-8958
access all versions, variants, and formats of this works (eg, pre-prints)
Crossref Metadata (via API)
Worldcat
SHERPA/RoMEO (journal policies)
wikidata.org
CORE.ac.uk
Semantic Scholar
Google Scholar