International Journal of Computer Engineering & Technology (IJCET) Volume 9, Issue 5, September-October 2018, pp. 10 15, Article ID: IJCET_09_05_002 Available online at http://www.iaeme.com/ijcet/issues.asp?jtype=ijcet&vtype=9&itype=5 Journal Impact Factor (2016): 9.3590(Calculated by GISI) www.jifactor.com ISSN Print: 0976-6367 and ISSN Online: 0976 6375 IAEME Publication ANALYSIS AND COMPARATIVE STUDY OF 10 YEARS CRICKET SPORTS DATA OF INDIAN PREMIERE LEAGUE (IPL) USING R PROGRAMMING Dr. Parag C. Shukla Assistant Professor & Head, Department of MCA, Atmiya University, Rajkot, India Dr. Hetal R. Thaker Assistant Professor, Department of MCA, Atmiya University, Rajkot, India ABSTRACT Nowadays, analytics is playing a key role in any field. Analytics is used in our day to day life. People don t want to purchase even without analytics. Before few months IPL (Indian Premier League for Cricket) auction was taking placed. Even franchises are interested to pick a cricket player based on their past performances. For all this, they need accurate data and analytics with the comparative study to pick a particular player for their team. Here, we are comparing the last 10 years cricket sports data of IPL with interesting facts. We can perform much analytics but here we are focusing on the comparison between popular players, team, and fielders. Performance of top-10 players in each category like batting, bowling and fielding. Valuable player for the specific team. Key words: Data Analytics, IPL Analytics, Sports Analytics. Cite this Article: Dr. Parag C. Shukla and Dr. Hetal R. Thaker, Analysis and Comparative Study of 10 Years Cricket Sports Data of Indian Premiere League (IPL) using R Programming. International Journal of Computer Engineering and Technology, 9(5), 2018, pp. 10-15. http://www.iaeme.com/ijcet/issues.asp?jtype=ijcet&vtype=9&itype=5 1. INTRODUCTION Cricket is popular sports in India, and many people want to know comparative study between different players, team etc. Before few months IPL (Indian Premier League for Cricket) auction was taking placed. Most of the franchises were interested to pick a cricket player based on their past performances. Many franchises have hired data analysts to do the analysis of the player. For all this, they need an accurate data and analytics with the comparative study to pick the particular player for their team. Here, we are comparing the last 10 years cricket sports data of IPL with interesting facts. We can perform much analytics but here we are http://www.iaeme.com/ijcet/index.asp 10 editor@iaeme.com
Analysis and Comparative Study of 10 Years Cricket Sports Data of Indian Premiere League (IPL) using R Programming focusing on Comparison between popular players, team. Performance of top-10 players in each category like batting, bowling, and fielding. Valuable player for a specific team. Here, we analyze the past 10 years data of IPL and summarize total runs by applying sum function for batsman_runs and we arranged the same in descending order. So, we can get the first cricketer who made the highest runs. Suresh Raina is the person who made the highest runs in the history of IPL. Surprisingly if you find the top-10 catcher of IPL history and if you are not counting wicket keepers catch then Suresh Raina is again come in the top of the table. So, we can conclude that Suresh Raina is the best batsman and best fielder in IPL. Top-10 Batsman in IPL History from 2008 to 2017 Figure 1 Top-10 Batsman in IPL History from 2008 to 2017 Top-10 Catcher in IPL History from 2008 to 2017 Figure 2 Top-10 Catcher in IPL History from 2008 to 2017 http://www.iaeme.com/ijcet/index.asp 11 editor@iaeme.com
Dr. Parag C. Shukla and Dr. Hetal R. Thaker 2. PERFORMANCE OF SURESH RAINA Figure 3 Performance of Suresh Raina Comparison between Virat Kohli and Suresh Raina Runs by each Season Figure 4 Comparison between Kohli and Raina Runs by each Season http://www.iaeme.com/ijcet/index.asp 12 editor@iaeme.com
Analysis and Comparative Study of 10 Years Cricket Sports Data of Indian Premiere League (IPL) using R Programming Comparison between Virat Kohli and Suresh Raina Type of Dismissals Figure 5 Virat Kohli Vs Suresh Raina Type of Dismissals Comparison between Virat Kohli and Suresh Raina Strike Rate By Over Figure 6 Virat Kohli Vs Suresh Raina Strike Rate By Over http://www.iaeme.com/ijcet/index.asp 13 editor@iaeme.com
Dr. Parag C. Shukla and Dr. Hetal R. Thaker Comparison between Virat Kohli & Suresh Raina By Number of Over Faced Figure 7 Virat Kohli Vs Suresh Raina By Number of Over Faced Comparison of Tendulkar, Ganguly, Dhoni, Kohli and Raina By Strike Rate Figure 8 Comparison of Tendulkar, Ganguly, Dhoni, Kohli, Raina Strike Rate http://www.iaeme.com/ijcet/index.asp 14 editor@iaeme.com
Analysis and Comparative Study of 10 Years Cricket Sports Data of Indian Premiere League (IPL) using R Programming 3. CONCLUSIONS Suresh Raina is the person who made the highest runs in the history of IPL from 2008 to 2017. Surprisingly if you find the top-10 catcher of IPL history and if you are not considering wicket keepers catch then Suresh Raina again comes on top of the table. So, we can conclude that Suresh Raina is the best batsman and best fielder in IPL. See a figure-4 comparison between Kohli and Raina runs through each season. In 2008,2009,2010,2012,2014,2017 Raina was the top-scorer than Kohli. We also did the comparison of both the stars in the type of dismissals, strike rate by over and Number of overs faced by both. We also did the comparison of stars like Sachin Tendulkar, Saurav Ganguly, MS Dhoni, Suresh Raina & Virat Kohli innings strike rate over wise and no doubt god of the cricket Sachin Tendulkar's strike rate is highest in 20 th over in IPL history with compare to Ganguly, Dhoni, Kohli, and Raina. ACKNOWLEDGEMENT We are very much thankful to Kaggle for providing us ball by ball data. This is never ever possible without Deliveries and Matches information that we get from the Kaggle. Also thankful to open source community to teach us how to write code in R. We are also thankful to the coder of kernels, who gave us hint that how to write a script in R. REFERENCES [1] @article{title = {Analyzing Varieties of Agricultural Data Using Big Data Tools Pig}, journal = {Oriental Journal of Computer Science and Technology}, year = {2017}, author = {Radadiya, Bankim L.}, volume = {10}, number = {4}, pages = {810-816} } [2] @article{title = {Elementary Concept of Big Data and Hadoop }, journal = {International Journal on Recent Trends and Innovation Trends in Computing and Communication}, year = {2017}, author = {Bhimani, Girish C.}, volume = {5}, number = {7}, pages = {749-752} } [3] @article{title = {NoSQL Databases : Big Data Characteristics and Comparison of traditional and big data analytics}, journal = {Quest International Multidisciplinary Research Journal}, year = {2015}, author = {Atkotiya, Kishor and Shukla, Parag}, volume = {4}, number = {11}, pages = {106-110} } [4] Wickham H (2009). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. ISBN 978-0-387-98140-6, http://ggplot2.org. [5] grid: R Core Team 2013. R: A language and environment for statistical computing. R foundation for statistical computing, Vienna, Austria. http://www.r-project.org/ [6] devtools: Hadley Wickham and Winston Chang, 2013. Devtools: Tools to make R code easier. [7] gridextra: Miscellaneous Functions for" Grid" Graphics. R package version 2.2. 1 B Auguie - Google Scholar, 2016 [8] dplyr: A Grammar of Data Manipulation. R package version 0.5. 0 [9] H Wickham, R Francois, L Henry, K Müller - 2016 - R Core Development Team Vienna [10] reshape2: Flexibly reshape data: a reboot of the reshape package. R package version. 2012; H Wickham [11] RColorBrewer: ColorBrewer palettes. R package version 1.1-2 E Neuwirth - 2014 [12] For data [Online Resource] https://www.kaggle.com/ http://www.iaeme.com/ijcet/index.asp 15 editor@iaeme.com