My book ‘Cricket analytics with cricketr and cricpy’ is now on Amazon

‘Cricket analytics with cricketr and cricpy – Analytics harmony with R and Python’ is now available on Amazon in both paperback ($21.99) and kindle ($9.99/Rs 449) versions. The book includes analysis of cricketers using both my R package ‘cricketr’ and my python package ‘cricpy’ for all formats of the game namely Test, ODI and T20. Both packages use data from ESPN Cricinfo Statsguru. The paperback is available on Amazon for $21.99 and the kindle version is available for $9.99/Rs 449

Pick up your copy today!

The book includes the following chapters

CONTENTS

Introduction 7
1. Cricket analytics with cricketr 9
1.1. Introducing cricketr! : An R package to analyze performances of cricketers 10
1.2. Taking cricketr for a spin – Part 1 48
1.2. cricketr digs the Ashes! 69
1.3. cricketr plays the ODIs! 97
1.4. cricketr adapts to the Twenty20 International! 139
1.5. Sixer – R package cricketr’s new Shiny avatar 168
1.6. Re-introducing cricketr! : An R package to analyze performances of cricketers 178
1.7. cricketr sizes up legendary All-rounders of yesteryear 233
1.8. cricketr flexes new muscles: The final analysis 277
1.9. The Clash of the Titans in Test and ODI cricket 300
1.10. Analyzing performances of cricketers using cricketr template 338
2. Cricket analytics with cricpy 352
2.1 Introducing cricpy:A python package to analyze performances of cricketers 353
2.2 Cricpy takes a swing at the ODIs 405
Analysis of Top 4 batsman 448
2.3 Cricpy takes guard for the Twenty20s 449
2.4 Analyzing batsmen and bowlers with cricpy template 490
9. Average runs against different opposing teams 493
3. Other cricket posts in R 500
3.1 Analyzing cricket’s batting legends – Through the mirage with R 500
3.2 Mirror, mirror … the best batsman of them all? 527
4. Appendix 541
Cricket analysis with Machine Learning using Octave 541
4.1 Informed choices through Machine Learning – Analyzing Kohli, Tendulkar and Dravid 542
4.2 Informed choices through Machine Learning-2 Pitting together Kumble, Kapil, Chandra 555
Further reading 569
Important Links 570

Also see
1. My book “Deep Learning from first principles” now on Amazon
2. Practical Machine Learning with R and Python – Part 1
3. Revisiting World Bank data analysis with WDI and gVisMotionChart
4. Natural language processing: What would Shakespeare say?
5. Optimal Cloud Computing
6. Pitching yorkpy … short of good length to IPL – Part 1
7. Computer Vision: Ramblings on derivatives, histograms and contours

To see all posts click Index of posts

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