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International Journal of Physical Education, Sports and Health
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P-ISSN: 2394-1685 | E-ISSN: 2394-1693 | CODEN: IJPEJB

Impact Factor (RJIF): 5.38

2016, Vol. 3, Issue 5, Part I

Editing the worm graph alias ball by ball data and predicting the winner for cricket


Author(s): Prasant Nair

Abstract:
Data mining means extraction of hidden predictive information from large databases. And data visualization places the extracted data in a visual context to bring out patterns, trends, and correlations that might go undetected in text-based data. The cricket data, whether the ball by ball data or the over by over data of any match is large and lack predictive value in its raw state. The worm graph turns this data into a visual form of cumulative runs and fall of wickets. But again, it lacks predictive value. This paper prepares an easy predictive model for cricket which any student, housewife, teenager or old age person can try himself. Under this In-play method, you remove the ‘nines’ from the current score; then the same worm now zooms out (during first innings itself) which team will win the match? This is a special tribute to William Playfair, the inventor of the time series line chart.

Pages: 513-518  |  1685 Views  243 Downloads

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How to cite this article:
Prasant Nair. Editing the worm graph alias ball by ball data and predicting the winner for cricket. Int J Phys Educ Sports Health 2016;3(5):513-518.

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