Abstract Cricket is an extremely popular game. More than a million cricketers play cricket daily in India alone and aspire to become professional cricketers. Cricket Talent identification and enhancement is a challenging problem due to lack of quality coaches, meagre infrastructural facilities, and poor linkages of coaching academies & cricket authorities. In India, the problem is even tougher as the majority of the population resides in villages. Many of talented players do not get timely recognition of cricket boards’ authorities thus amounting to waste of talent. Many keep on pursuing cricket despite of being non-talented. Due to lack of application of appropriate scientific methods the selection process is also criticized as biased by many. In this paper, we present a web based system viz. Cricket Talent Identification, Enhancement and Selection (C-TIES) for addressing the above issues. C-TIES utilize a cricket talent knowledgebase of experts’ opinions aggregated by applying OWA Aggregation Operator and Relative Fuzzy Linguistic Quantifier (RFLQ). The C-TIES system classifies the cricket talent level of an enthusiast into five different classes by applying Normalized Adequacy Coefficient (NAC). The Talent Enhancement and Talent Selection subsystems also uses appropriate algorithms based on OWA, RFLQ and NAC to respectively enable identification of weaknesses in a player and select most talented n-players from a larger group of players. Thus, system reduces the time for identifying weaknesses and also provides a relatively better unbiased selection method for short listing players. The system has been developed using Struts 2.0, Hibernate, J2EE, Ajax, MySql are used.
Read full abstract7-days of FREE Audio papers, translation & more with Prime
7-days of FREE Prime access