Regression Analysis of Ipl Players Auction Essay Example for Free

Regression Analysis of Ipl Players Auction Essay additive regression molding has been developed using rearwards variable selection method. The criterion used for Backward method is Probability of F-to-remove gt= 0. 100 As seen from the above table in our model the R fledge prise of is 0. 618 and Adjusted R Square value is 0. 592. Team variable is removed Cricket in the T20 format is considered a young mans sport, is there evidence that the histrions worth is influenced by age? From our analysis we have seen that the price of a player is greater if the player is little than 25 years of age. Identify the predictor that has the highest impact on the price of players. Batting strike set out and bowling strike rate do not have signifi lowlifet impact on the pricing. This can be explained by very low R2 = 0. 014 for bowling strike rate and R2 = 0. 034 for batting strike rate. roll Strike Rate vs Sold Price Batting Strike Rate vs Sold Price The human foot price has the highest impact on Selling Price of the players. When compared to others, the base price has the highest R square valueHow much should Mumbai Indians offer Sachin Tendulkar if they would like to retain him? Is the model sufficient to predict the price of Icon players? jibe to model, the sold price of Sachin is 1800000 but fair value of Sachin Tendulkar is 1598610. 008 which minimum amount should be paid. Icon player should get 15% premium over second highest pay. But this factor is not considered in our analysis. Hence, our model cant predict the value of icon players.