Automated Cricket Squad Prediction: Cricket Squad Prediction Based on Social-media and Performance

Abstract

Cricket is one of the 2nd most popular games on the planet and has become an inseparable part of our culture. There are mainly three renowned formats of cricket – One Day International (ODI), Test Match and T20. People of Sri Lanka are very concerned about the national cricket squad before any matches or any series. Selecting a perfect 15 players of the squad isn’t an easy task. Cricket board, captain and coach play a vital role to select the most suitable players for a match to win by preserving many parameters in their heads such as – analyzing the strike rate, past scored runs compared with the balls faced, total fifties and centuries, wickets, economy rate, etc. Besides this perfect prediction and combination selection process is needed to win any cricket matches. Social media has become a platform of the first choice where one can express their feelings with freedom. The games furthermore, matches being played are also discussed on social media such as Twitter. In this paper, authors efforts are made to research the possibility of using collective information obtained from user posts on Twitter. The author's motive is to analyze the public tweets on Twitter and compare it with players' previous performance (Cric-info) in international matches and select the topmost suitable fifteen players among them for the Sri Lankan national team. Sri Lanka’s most of the national players are selected based on the political support or board members support. So there is no chance of getting entered in the national team for the talented person. So this system could be a solution for many players who have not represented Sri Lanka yet. This automated strategy is very useful for the selection board committee, viewers, sponsors, commentators, and sports analysts. Automated cricket squad prediction replacing the traditional way of team selection. This team selection process considers public tweets about players performance on twitter during matches and compares it with the players' previous performance. So there is only a chance of getting into the team based on public opinion as well as players previous performance. Compared to the existing systems, this system is first of its kind in social-media analysis along with the performance for choosing players for the national cricket team. This system eases out the work of the selection committee.