1. The document analyzes Indian cricket team's T20 performance data using statistical tools to determine the most consistent players and better batsmen/bowlers. 2. Tools used include standard deviation, coefficient of variance, correlation, and chi-square tests to analyze batsmen and bowler data and conclude which players should be part of the final T20 team. 3. The analysis found Gautam Gambhir, Yuvraj Singh, Rohit Sharma, Virender Sehwag, MS Dhoni, RP Singh, Irfan Pathan, and Harbhajan Singh to be the most consistent performers based on their statistical results.

1. Group No. 3Quants Live Project

2. OverviewObjectiveIntroductionTools UsedImplementationConclusion

3. ObjectiveTo find out the most consistent playerTo find out the better Batsmen/BowlerTo conclude that the runs scored are independent of days and weeks

4. Introduction.. We have analyzed T20 Cricket data of the Indian Team’s performance at the International Level.

5. Data obtained is of batsmen and bowlers which is distinguished.

6. ASSUMPTION- Player will not be considered for the consistency test if played only 1 match.Tools UsedStandard DeviationCoefficient of VarianceCorrelationChi - square

7. Standard Deviation Is most useful in describing or analyzing a data.

8. It is also useful for comparative purposes.

9. It is the minimum when the deviations are measured from the arithmetic mean.

10. It is the square root of varianceVariance for Ungrouped data1/n ∑xi^2 – mean^2

11. Coefficient of Variance It is also known as Relative dispersion.

12. It is a stastical measure introduced by Karl Pearson.