Dibyojyoti Bhattacharjee

Predicting the Performance of Bowlers in IPL: An Application of Artificial Neural Network

Application of data mining tools is often used in professional sports for evaluating players/teams’ performance. Cricket is one of those sports where a large amount of numerical information is generated in every game. The game of cricket got a new dimension in April 2008, when Board of Control for Cricket in India (BCCI) initiated the Indian Premier League(IPL). It is a franchise based Twenty20 cricket tournament where teams are formed by competitive bidding from a collection of Indian and International players. Since, valuations of the players are determined through auction, so performance of individual player is always under scanner. The objective of this study is to analyze and predict the performance of bowlers in IPL, using artificial neural network. Based on the performance of bowlers in the first three seasons of IPL, the paper tries to predict the performances of those bowlers who entered in the league in its fourth season as their maiden IPL venture. The performances of these bowlers in IPL-IV are predicted, and the external validity of the model is tested using their actual performance in IPL-IV. This prediction can help the franchises to decide which bowler they should target for their team.

An unusual occurrence of plasmid-mediated blaOXA-23 carbapenemase in clinical isolates of Escherichia coli from India

The blaOXA-23 group was considered as the first group of OXA-type β-lactamases conferring carbapenem resistance and has been reported worldwide in Acinetobacter baumannii, however their presence in Escherichia coli is very rare and unique. This study describes an unusual occurrence of blaOXA-23 in 14 clinical isolates of E. coli obtained from intensive care unit patients admitted to a tertiary referral hospital in India. The blaOXA-23 gene was found located within a self-conjugative plasmid of IncFrepB and IncK incompatibility types and simultaneously carrying blaCTX-M-15, blaVEB-1, blaPER-1 and/or blaNDM-1. The copy number of blaOXA-23 within the IncK-type plasmid was inversely proportional to increasing concentrations of imipenem, whereas in the case of the IncFrepB-type the result was variable; and increased copy number of the IncK-type plasmid was observed with increasing concentrations of meropenem. Plasmids encoding blaOXA-23 could be successfully eliminated after single treatment and were found to be not highly stable, as complete loss of plasmids was observed within 5-10 days. This study emphasises that carbapenem stress invariably altered the copy number of two different Inc type plasmids encoding the blaOXA-23 resistance gene and also highlights a potential threat of clonal expansion of this class D carbapenemase through a heterologous host in this country, which is in second incidence globally.

A Double Weighted Tool to Measure the Fielding Performance in Cricket

Though several statistics are used to quantify the batting and bowling performance of cricketers, there is no such measure for the fielders in cricket. This article introduces a measure that can be used to gauge the fielding performance of cricketers. The various parameters that are considered for fielding are quantified to scores based on the ball-by-ball information of a match for each fielder. Subjective weights are assigned to these parameters based on the relative importance of different alternatives under various fielding circumstances. The weights are then combined with the scores of each of the on-field performances of a fielder to get his corresponding fielding score. Two different measures of fielding performance are proposed and their relative differences are discussed. To demonstrate these measures, the final of the first Twenty20 World Cup tournament played on 24 September 2007 is considered. The outcomes obtained from the two measures are accordingly compared.

Simulation Study to Compare the Random Data Generation from Bernoulli Distribution in Popular Statistical Packages

In study of the statistical packages, simulation from probability distributions is one of the important aspects. This paper is based on simulation study from Bernoulli distribution conducted by various popular statistical packages like R, SAS, Minitab, MS Excel and PASW. The accuracy of generated random data is tested through Chi-Square goodness of fit test. This simulation study based on 8685000 random numbers and 27000 tests of significance shows that ability to simulate random data from Bernoulli distribution is best in SAS and is closely followed by R Language, while Minitab showed the worst performance among compared packages.

Quantifying the pressure on the teams batting or bowling in the second innings of limited overs cricket matches

A team batting second in a limited overs match is under pressure to score the required number of runs for victory in the allotted number of overs without losing all its wickets. The bowling team has to prevent its opponents from reaching the target for victory. The objective of this study is to define methods that can be used to assess the pressure on the two teams’ batsmen and bowlers when playing the second innings of a Twenty20 or One-day match, and also to define methods to determine the best partnership and the turning point in such an innings. Methods are also defined to determine the batting and bowling performances of individual players in a specific match. These measures can be quite useful for selectors to assess how the players perform under pressure.

On Performance Measurement of Cricketers and Selecting an Optimum Balanced Team

A cricket squad that participates in a tournament generally comprises of fifteen players. A balanced squad contains players having different expertise like batting, bowling, wicket keeping, etc. Keeping in view the cricketing requirements, selecting an optimal squad is a difficult decision-making problem. In order to attain that, the study proposes a composite index to measure the performance of cricketers irrespective of their expertise. Then using a binary (0-1) integer programming method a balanced squad of 15 players is selected. To apply the tool to practice, optimum balanced squads are selected from amongst the Indian players who participated in the Indian Premier League (IPL), based on the proposed performance measure for different seasons. The team so selected is compared to the actual Indian team selected for the International Cricket Council (ICC) Twenty20 World Cups following the IPLs in the year 2009, 2010 and 2012. It is seen that the actual Indian team is not much variant to the optimal squad of ICC Twenty20 World Cup 2012 but things are different during the years 2009 and 2010. The optimization technique discussed in this study can be helpful for the balanced team selection of other team sports as well.

A Bayesian Classification Model for Predicting the Performance of All-Rounders in the Indian Premier League

The game of cricket got a new dimension, when the Indian Premier League (IPL), a competition of twenty over-a-side featuring eight teams named after various Indian cities/states started in 2008. The teams were franchisee driven and the players were selected via competitive bidding from a pool of available players. All-rounders i.e. players with the ability to both bat and bowl play a noteworthy part in cricket, whatever is the version of the game. The study measures the performance of all-rounders in Indian Premier Leagues (IPL) based on their strike rate and economy rate. The all-rounders are divided into four non-overlapping class viz. performer, batting all-rounder, bowling all-rounder and under performer. Stepwise multinomial logistic regression is used to determine the significant predictors responsible for such categorization. A Naive Bayesian classification model is developed that can use the significant predictors to forecast the class in which an incumbent all-rounder is expected to lie. The classifier is build based on the performance of all-rounders who participated in IPL-I and II, and the validity of the classifier is subsequently tested over the incumbent all-rounders of IPL-III. The classifier though moderately successful in predicting the appropriate class of the incumbent all-rounders in IPL III, is expected to perform better in future with increase in the size of training sample. This classification would be useful for the participating teams’ management while deciding about which all-rounder to be bided for and to what amount in the next addition of the league.

Satisfaction an Antecedent of Word-of-mouth among Electronic Banking Users: A Study on Salaried Employees

The study attempts to investigate whether the satisfaction pertaining to the use of electronic banking (e-banking) channels has any impact on word-of-mouth (WOM) among specific group of population, that is, the salaried employees. A sample of 400 respondents was collected from the districts of southern Assam, India, based on post-stratified random sampling. After achieving good fit of the measurement model by confirmatory factor analysis, hypothesis testing was done using structural modeling to find the causal relationship between the constructs of the model. The results revealed that there is a direct positive relationship between satisfaction and WOM in e-banking among salaried employees. Evidences show that the salaried employees are maximum users of e-banking. Finding out the relationship between satisfaction and WOM among target population shall enable the banks to develop a niche-based strategy and attain feedback for increasing satisfaction.

A New Model for Player Selection in Cricket

A balanced squad in cricket contains players with different expertise like batting, bowling, all-rounder and wicket keeping. Maintaining these cricketing requirements, selecting an optimal squad is a difficult decision making problem. The selectors have chosen cricketers using their own experience and based on the recent performances of available players from all the different expertise. The paper introduces a measure that can quantify the performance of the cricketers into a single numerical value, which is a measure of the player’s cricketing efficiency. The distributional pattern of the performance measure is identified and then used to recognize the performers under different expertise. The entire exercise simplifies the job of the selectors as they now have a smaller subset to choose from. To explain the model empirically, data of the Indian Premier League (IPL), 2012 is used to identify the performers of the game under different expertise. The actual Indian team selected just after the said season of IPL is then compared with the performers of IPL, 2012 as identified by the model. It was found that several non-performers were selected in the actual squad and some performers were left out. This model can be extended for the team selection in other versions of cricket and even in other team sports.

Application of Markowitz Model for Analyzing the Performance of Cricket Teams in Indian Premier League

This study tries to identify the dominant teams of the first five seasons of IPL using Markowitz model of portfolio management. An average composite performance score (ACPS) is developed based on two prime skills of the game (i.e. batting and bowling) that can be used to quantify the performance of a cricket team. The value of ACPS is considered as the return of a team and the standard deviation of the composite performance score of the team across different matches as the risk associated with team performance. The study also tries to explore if it is the dominating team that tops the list in the tournament. As an outcome of the study, it is found that Chennai Super Kings (CSK) and Delhi Daredevils (DD) had dominated the first three seasons of IPL. The next two seasons were dominated by Deccan Chargers (DC). A dominating team is expected to be the favorite team of the tournament. Such a team is expected to get more support from the audience.