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Whenever we talk about fast sports world, cricket maintains an important place due to its record breaking history and beautiful audience. The fans are always found active in supporting their flag teams through national slogans and face makeup’s which not only add emotions to this game but also excitement and passion. Those participants that join live cricket matches on media channels and internet are also very thrilled to watch for favoritism behavior which tells them about “who is more expected or favorite to win the match or series or cup” in view of their scores and preceding performances. At times this favoritism behavior becomes very crucial for the gaming fans during situations when both teams are playing competitively or performing equally thus making it intricate to expect about the winning team.
In early times of cricket consistency in favoritism behavior was one of the characteristic of the matches, when popular teams usually win against less popular teams and big scorer or low scorer usually win or lose respectively. In present era of cricket unlike past, there is no doubt in commenting that this behavior is jumping around dramatically more than expectations and giving surprises to the viewers, a good example will be T20 matches. These unusual fluctuations put spectators and commentators in a situation of nervousness or confusion and make it tricky to forecast about winning team. Favoritism relates to the Top Ten Ranking list produced by ICC. List is built on seasonal performance of cricket teams in all three formats i.e. Test, ODI and T20s. If top team plays against 4th ranked team the top team will get the favorite position before the start of match. During the live cricket match, due to performance variations, teams get different positions from favoritism behavior. In a live cricket match, if the favorite position holder team does not perform well the team which is not favorite will take over the favorite position and create fluctuation in the position which can produce related advantages. For an example, if favorite (30% winning chance) team becomes most favorite (70% winning position) during the match then this new position will consider as safe point. Similarly this will also happen when non-favorite team becomes half favorite or more during the match.
Information about favoritism behavior is very seldom due to its critical nature and rare availability of historical data. Although data with respect to indiviual or teams score, match results and competition track records among teams are accessible but knowledge about "who was favorite at start of the match, half inning favorite, 2nd inning favorite and so on" is difficult to obtain. The record of this favoritism behavior is a point which could be very helpful in viewing the comprehensive glimpse of trend preceding the upcoming match, series or tournament among different teams. It is worthwhile to comment that favoritism behavior could be placed as one of the significant indicators about any sports on which all participants are depending to make hypothesis about the match , series or tournament outcome.
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