Game Of Cricket Research Articles

RunsGuard Framework: Context Aware Cricket Game Strategy for Field Placement and Score Containment

Sports analytics utilizes data analysis techniques and computational methods to gain insights, make informed decisions, and facilitate improvements in the performance of individuals and teams. Cricket is one of the most popular games and continues to evolve worldwide. The availability of ball-by-ball data demands in-depth investigation of player strategies, team dynamics, and the impact of contextual variables. Existing studies explored various aspects of cricket analytics, including detecting key events, predicting outcomes, and ranking teams. However, the literature lacks a comprehensive integrated framework that processes unstructured sports commentary, extracts actionable insights, conducts a thorough player analysis, and develops strategic plans while considering contextual factors. This work aims to propose a bowling and fielding strategy to contain a batsman. For this purpose, we developed a comprehensive context-aware framework that collects data, extracts insights from commentary, identifies player strengths and weaknesses, and proposes cricket bowling and fielding strategies according to the given context. To evaluate this work, we implemented a case study that simulated different scenarios, and our framework suggested bowling and fielding strategies. In these simulations, the proposed strategies consistently demonstrated a substantial reduction in the number of runs that were scored. On average, the framework reduces the batsman’s score rate by 33%. These findings underscore the practical effectiveness of research in optimizing field placement and effectively reducing scoring opportunities. Finally, by bridging the gap between data analytics and cricket game strategy, this methodology provides a competitive advantage to coaches, captains, and players. In the future, we aim to involve temporal patterns to understand the evolving behavior of players.

Exploring Twitter Sentiments for Predicting Match Outcomes in The Game of Cricket

In recent years, social media platforms such as Twitter have become popular among fans to discuss and share their opinions about the matches. This research aims to contribute to the growing body of knowledge on utilizing the sentiments expressed through messages on social media platforms to predict outcomes of matches in the sport of cricket. This research work provides insights into the effectiveness of sentiment analysis techniques in forecasting match outcomes, which can be beneficial to cricket fans, and cricket analysts. In this work, sentiment analysis is carried out based on models developed using various machine-learning techniques. The work also explores the impact of different features, such as the number of tweets collected, the timing of tweets, and the sentiment analysis techniques on the accuracy of the prediction. The results of this study have implications for cricket fans, sports analysts, and the broader field of predictive analytics.

Automatic Player Face Detection and Recognition for Players in Cricket Games

Automatic Player Face Detection and Recognition for Players in Cricket Games

Menstimulus Perkembangan Motorik Kasar Anak Melalui Permainan Engklek dl Kober Miftahul Fallah

Gross motor skills in children are important to train, especially in the early years of school, one way to stimulate gross motor skills in children, namely; through traditional engklek games in improving gross motor skills in early childhood descriptive research methods with a qualitative approach used in this study. The results showed that the implementation of the engklek game at Kober Miftahul Fallah Cibenda, Parigi, Pangandaran is carried out regularly once a month, the game still uses natural media in the form of an arrangement of plots with numbers and the APE used is in the form of tile fragments as gacuk. Kober Miftahul Fallah prefers traditional games in the form of cricket to modern games, they do this with the aim of reviving the traditional game of cricket so that it is more sustainable and trying to campaign or socialize that this cricket game is not only not playing but there is an element of education in children. Indirectly, besides being able to hone children's gross motor skills, this game can also train communication skills, process emotions, train body balance and empathize, so that students will have strong capital to explore and make friends in their new environment. In its implementation, the teacher makes an assessment of the development of students to see the extent of children 's gross motor skills in traditional games.

An analysis of specific batting demands in the women's The Hundred competition.

No research has investigated the shortest format of the game of cricket, The Hundred competition. Furthermore, women's cricket research is particularly limited, with most focusing on injuries and little literature investigating specific batting demands. These demands are important if training programmes are to mimic the game's movement patterns. The purpose of this study was to analyse specific batting demands and variables associated with the women's The Hundred competition. Thirty-one matches from the Women's 2021 The Hundred competition were analysed using Hudl Sportscode Elite. Variables analysed included: bowler type (seam or spin), free hits, no ball runs, reason for no ball (height/wide/front foot), run scored (0, 1, 2, 3, 4, 6), type of key event (fall of wicket, bowling referral, batting referral, umpire referral, bowling time out, rain delay, or injury) as well as time between deliveries and sets, overall and between the power play and non-power play. A total of 6073 deliveries were analysed. A significant difference (p<0.05) was observed for time between deliveries for spin bowlers (26.90±22.16 s) compared to seam bowlers(31.70±20.37 s) as well as time between sets for the power play (58.00±13.28 s) and non-power play phases (63.70±42.00 s). Additionally, in the power play, most runs were made up of "1's" and "4's". In the non-power play phase, "1's" made up the biggest contribution of runs (as a percentage). The fact that singles make up a significant portion of a typical match means that strength and conditioning coaches should incorporate high-intensity sprint-type training into training programmes to mimic these demands.

AI Cricket Score Board

Gesture Recognition pertains to recognizing meaningful expressions of motion by a human, involving the hands, arms, face, head, and/or body. It is of utmost important in designing an intelligent and efficient human–computer interface. The applications of gesture recognition are manifold, ranging from sign language through medical rehabilitation, monitoring patients or elder people, surveillance systems, sports gesture analysis, human behavior analysis etc., to virtual reality. In recent years, there has been increased interest in video summarization and automatic sports highlights generation in the game of Cricket. In Cricket, the Umpire has the authority to make important decisions about events on the field. The Umpire signals important events using unique hand on signals and gestures. The primary intention of our work is to design and develop a new robust method for Umpire Action and Non-Action Gesture Identification and Recognition based on the Umpire Segmentation and the proposed Histogram Oriented Gradient (HOG) feature Extraction oriented of Deep Features. Primarily the 80% of Umpire action and non-action images in a cricket match, about 1, 93,000 frames, the Histogram of Oriented Gradient Deep Features are calculated and trained the system having six gestures of Umpire pose using Densenet121.

ViSig

Visual body signals are designated body poses that deliver an application-specific message. Such signals are widely used for fast message communication in sports (signaling by umpires and referees), transportation (naval officers and aircraft marshallers), and construction (signaling by riggers and crane operators), to list a few examples. Automatic interpretation of such signals can help maintaining safer operations in these industries, help in record-keeping for auditing or accident investigation purposes, and function as a score-keeper in sports. When automation of these signals is desired, it is traditionally performed from a viewer's perspective by running computer vision algorithms on camera feeds. However, computer vision based approaches suffer from performance deterioration in scenarios such as lighting variations, occlusions, etc., might face resolution limitations, and can be challenging to install. Our work, ViSig, breaks with tradition by instead deploying on-body sensors for signal interpretation. Our key innovation is the fusion of ultra-wideband (UWB) sensors for capturing on-body distance measurements, inertial sensors (IMU) for capturing orientation of a few body segments, and photodiodes for finger signal recognition, enabling a robust interpretation of signals. By deploying only a small number of sensors, we show that body signals can be interpreted unambiguously in many different settings, including in games of Cricket, Baseball, and Football, and in operational safety use-cases such as crane operations and flag semaphores for maritime navigation, with &gt; 90% accuracy. Overall, we have seen substantial promise in this approach and expect a large body of future follow-on work to start using UWB and IMU fused modalities for the more general human pose estimation problems.

Application of Artificial Intelligence in Sports: A case study of cricket.

The game of cricket has developed over the years and has completely transformed. Very obviously technology has affected the game a lot. Many developments have come in the game as a concept, rules and even how teams and players look and prepare for a match. This paper looks at the various uses of Artificial Intelligence as a whole.

Data-Driven Probabilistic System for Batsman Performance Prediction in a Cricket Match

Batsmen are the backbone of any cricket team and their selection is very critical to the team’s success. A good batsman not only scores run but also provides stability to the team’s innings. The most important factor in selecting a batsman is their ability to score runs. It is a generally accepted notion that the future performance of a batsman can be predicted by observing and analyzing their past record. This hypothesis is based on the fact that a player’s batting average is generally considered to be a good indicator of their future performance. We proposed a data-driven probabilistic system for batsman performance prediction in the game of cricket. It captures the dependencies between the runs scored by a batsman in consecutive balls. The system is evaluated using a dataset extracted from the Cricinfo website. The system is based on a Hidden Markov model (HMM). HMM is used to generate the prediction model to foresee players’ upcoming performances. The first-order Markov chain assumes that the probability of a batsman scoring runs in the next ball is only dependent on how many runs he scored in the current ball. We use a data-driven approach to learn the parameters of the HMM from data. A probabilistic matrix is made that predicts what scores the batter can do on the upcoming balls. The results show that the system can accurately predict the runs scored by a batsman in a ball.

SURVEI KETERAMPILAN BATTING TIM CRICKET PUTRA KABUPATEN PANDEGLANG PADA PERSIAPAN PORPROV

This study aims to make the male cricket players of Pandeglang Regency better understand about batting skills so that in the real championship players are even better at doing batting techniques in the game of cricket. This research was conducted in Banten. Data collection was carried out at NETS or the training ground located at the South Tangerang Puspitek, on 14, 16, 19, and 21 July 2022.This research method is descriptive with survey technique. The population in this study were all male cricket players who will compete at the VI 2022 Provincial Sports Week (PORPROV) in Banten. The sample is the men's cricket team of Pandeglang Regency which will compete at the VI 2022 Provincial Sports Week (PORPROV) in Banten. Based on the problems raised and supported by theoretical descriptions and frameworks of thinking and then analyzing the data, the results of the study can be concluded that the overall results of batting skills show 69% success and 31% failure.

Analysis of Front Leg Kinematics of Cricket Bowler Using Wearable Sensors and Machine Learning

A fast bowler in the game of cricket is exposed to high-intensity actions and is more prone to lumbar stress fractures, ankle sprains, and knee, shoulder, and lower back injuries. There are different phases of bowling, from running to ball release, viz., run-up, predelivery stride (PDS), mid-bound (MB), front foot contact (FFC), ball release, and follow through. The front leg motion of the bowler plays a crucial role in delivering the ball efficiently. An improper landing after the jump causes most of the injuries as more strain is induced on the knee, ankle, and groin region. Loss of balance during the follow-through is the other most common reason for injury. A braced front leg at FFC helps the bowler transfer the momentum gained during the run-up into a fast-bowling action. For a refined understanding of the motion of the bowler and the causes of injuries, the identification of bowling phases is crucial. This article proposes the design of a miniature and economical wearable sensor unit using a Bosch BNO055 inertial measurement unit (IMU) sensor that the players can comfortably wear during the game. A novel method for calculating knee flexion of bowlers at FFC using quaternion data gathered from sensors is presented. Two wearable units were placed on the bowler’s front leg to collect motion data. Supervised machine-learning algorithms have been evaluated for classifying bowling phases using statistical features extracted from the sensor data to assist coaches and players with data-driven and evidence-based bowlers’ training.

Cricket Video Highlight Generation Methods: A Review

The key events extraction from a video for the bestrepresentation of its contents is known as video summarization.In this study, the game of cricket is specifically consideredfor extracting important events such as boundaries, sixes andwickets. The cricket video highlight generation frameworksrequire extensive key event identification. These key events canbe identified by extracting the audio, visual and textual featuresfrom any cricket video.The prediction accuracy of the cricketvideo summarization mainly depends on the game rules, player’sform, their skill, and different natural conditions. This paperprovides a complete survey of latest research in cricket videosummarization methods. It includes the quantitative evaluationof the outcomes of the existing frameworks. This extensive reviewhighly recommended developing deep learning-assisted videosummarization approaches for cricket video due to their morerepresentative feature extraction and classification capabilitythan the conventional edge, texture features, and classifiers. Thescope of this analysis also includes future visions and researchopportunities in cricket highlight generation.

SOSIALISASI OLAHRAGA CRICKET KEPADA GURU OLAHRAGA SE-KABUPATEN BOGOR

This paper describes the results of the Community Service Program on the socialization of cricket to sports teachers. The underlying problem is that there are still many sports teachers who do not know about cricket. One area that lacks knowledge about cricket is Bogor Regency. While this cricket sport has a very large opportunity to support one's achievements. Cricket is a team sport that can be played by all ages, both children, teenagers and the general public. This cricket sport is usually competed in regional and national sports events. Currently, the sport of cricket in Indonesia is in the socialization stage so that the development of cricket is important to be promoted and introduced to all circles, especially to sports teachers. Introduction to sports teachers is very important because cricket needs to be instilled in children from an early age. The purpose of this activity is to provide an overview and rules of the game of cricket to sports teachers in order to get an understanding and practice well according to the theory and rules of the game in the game of cricket.

Significant hot hand effect in the game of cricket

We investigate the predictability and persistence of individual and team performance (hot-hand effect) by analyzing the complete recorded history of international cricket. We introduce an original temporal representation of performance streaks, which is suitable to be modelled as a self-exciting point process. We confirm the presence of predictability and hot-hands across the individual performance and the absence of the same in team performance and game outcome. Thus, Cricket is a game of skill for individuals and a game of chance for the teams. Our study contributes to recent historiographical debates concerning the presence of persistence in individual and collective productivity and success. The introduction of several metrics and methods can be useful to test and exploit clustering of performance in the study of human behavior and design of algorithms for predicting success.

An efficient team prediction for one day international matches using a hybrid approach of CS-PSO and machine learning algorithms

Player classification is vital in cricket since it assists the coach and skipper in determining individual players' roles in the squad and allocating tasks appropriately. The performance statistics help to classify players as batsmen, bowlers, batting all-rounder, bowling all-rounder, and wicketkeeper. This research aims to correctly identify cricket teams in the one-day international format by categorizing players into five groups. Based on their previous and current performance, the players are rated as excellent, very good, good, satisfactory, or poor. An enhanced model for the game of cricket is presented in this study, in which an eleven-member team picked using an unbiased technique. Players should be selected based on their performance, batting average, bowling average, opposing team strength and weakness, etc. Nature-inspired algorithms are used for feature optimization to improve the accuracy of machine learning prediction models. The blending of Cuckoo Search and Particle Swarm Optimization is performed called CS-PSO, which successfully integrates the capabilities from both approaches to create reliable and suitable solutions in accomplishing global optimization efficiently. Using a hybrid of CS-PSO feature optimization and Support Vector Machine, batters, bowlers, batting all-rounders, bowling all-rounders, and wicketkeepers were picked with an accuracy of 97.14%, 97.04%, 97.28%, 97.29%, and 92.63%, respectively.

Financial and Psychosocial Entrapment in Aravind Adiga’s Selection Day

The present paper deals with Aravind Adiga’s fourth novel Selection Day based on extraordinary panorama of cricket game. Financial condition of the poor and bourgeois is responsible for their future planning, decision in studies and the way of life at the same time the struggle of middle and lower-class people ensnare them into psychosocial entrapments. Aravind Adiga’s Selection Day contains financial and psycho-social entrapment of Kumar Family. By the help of cricket game the writer aesthetically webs the themes of unexplored sexuality, unsatisfied desires and all the aspects of the struggle faced in the life of Radha and Manju. Eric Erikson has propounded the stages of psychosocial development, the protagonist of this novel endeavors to uplift his life therefore he passes throw these stages. His theory is adhered to Sigmund Freud’s theory of Psychoanalysis. Money minded father and psychologically traumatized sons are working day and night for golden future in the vast area of corrupt capitalist immoral society therefore this novel is a harsh criticism of money possessiveness of games and people’s different point of view regarding national glory.

Video Summarization Using Deep Learning for Cricket Highlights Generation

Recently, video surveillance technology has grown pervasive in many aspects of our lives. Automatic video monitoring produces massive amounts of data that need human examination at some point. The primary emphasis is on reducing storage usage by compressing or eliminating superfluous frames without sacrificing real information. The current effort seeks to close the growing gap between the amounts of real data and the volume. Searching through key events in large video collections is time-consuming and tedious. In this paper, smart surveillance for various applications by using video summarization has been presented. A method for generating highlights has presented which pre-processes extracted Video Frames. Convolutional Neural Networks are then used to evaluate these highlighted frames. The proposed technique extracts and calculates characteristics utilized to generate summary movies. For training deep neural networks, cricket datasets have been used. Experimental results show that the proposed solution attains improved results than other advanced summarization methodologies. Experimental results show that the proposed video summarization method consistently generates high-quality reviews for all types of videos. The proposed video summarization method is easy to use, and it can also help extract highlights of cricket games with high accuracy.

The effect of time of day on adolescent fast bowling performance: A pilot study

The game of cricket is played at various times of the day and no studies have investigated the time of day effects on perceptual, physical and performance measures of cricketers. Therefore, the purpose of this study was to focus on adolescent fast bowlers and their responses when bowling at different times of the day. First team, adolescent male fast bowlers (N = 5, Mean age 17.00 ± 0.55 years; stature 185.2 ± 6.5 cm and mass 86.06 ± 17.56 kg) were required to complete a fast-bowling simulation protocol whereby perceptual, physical and bowling-specific performance measures were tested at three different times of day (10:30, 14:30, 18:30). Over all the spells over one was significantly slower than all the other overs. There were no significant changes in bowling speed between the time intervals. However, there was a large increase in bowling speed at 14:30 compared to 10:30 (ES – 1.25) and a moderate increase in bowling speed (ES = 0.67) between 10:30 and 18:30. There was no significant change in accuracy at the different time intervals although it was best at 10:30 followed by 18:30 although the latter had a greater variance. In conclusion, this investigation found time of day did not significantly impact the responses, but the effects sizes show that bowling accuracy was worst at 14:30 despite the other parameters, such as speed of delivery, being best at this time, which may suggest a speed-accuracy trade-off. Additionally, both 10:30 and 18:30 were found to be times conducive to bowling performance with regards to accuracy.

PATH ANALYTIC APPROACH TOWARDS DEMYSTIFYING THE KEY TRIGGERS BEHIND LIKING DIFFERENT CRICKET FORMATS – A KOLKATA BASED STUDY

Cricket has multiple international formats. This study aims to find out if gender and age have any influences on liking any formats. It delves deep into the outcome quality of a cricket match to build a construct for understanding fans’ psyche behind fondness for any formats. The same construct is used to model overall liking for each format. The study uses Chi-square test for independence to investigate the influence of gender and age group on overall liking of a format. It uses Confirmatory Factor Analysis (CFA) to establish the dimensional construct and applies Structural Equation Model (SEM) to model overall liking based on the construct. The study finds no link between gender and liking of a format even though age group appears to influence. It establishes the construct REST comprising of Result, Excitement, Skill, Time and Money to measure overall liking for a format. Result and Skill are found to be insignificant for predicting the liking of Tests and T20 respectively whereas ODI appears to be more balanced. The findings give a clear indication to the regulators that test matches need to be made more unpredictable and result-oriented and T20 matches less restricted and more skilful. The regulators need to strategize making the younger generation interested in test and the older generation in T20. REST can be treated as a pioneering construct that can explain fan’s expectation from a game of cricket leading to liking a format.

Data Analytics in the Game of Cricket: A Novel Paradigm

Cricket, the second most popular sport in the world, has emerged as one of the most widely played international mainstream sports in the world. With the advent of newer formats such as the Twenty-twenty (T-20) over cricket, the popularity of the game has further soared, spurting out international leagues such as the Indian Premier League (IPL) and the Big Bash League (BBL), over the last one decade. Over the course of more than 450 years since the inception of this sports in south-east England, statistics have played a pivotal role in shaping the structure and format of the game. Of late, there have been considerable advancements in cricket data analytics using IoT-based cricket bat sensors, advanced video analysis using Pitch-Vision, Hawk-Eye and allied technologies. From providing trajectories of the ball, to measuring the speed and impact point of the ball hitting the bat, such stellar breakthroughs have made it possible to fathom and analyze the game in a more refined way. Internet of Things (IoT) and Data Analytics can be the proponents in learning more about the stroke play of players as well as about the myriad facets of the game. In this paper, we have endeavored to discover a novel paradigm of research in cricket analytics known as the timing index, based on a real life IoT-based implementation and case study. The timing index is based on an amalgam of different factors such as bat speed, back lift angle, max. bat speed and impact bat speed. We believe that such a study can help in analyzing a player's training sessions using IoT and data analytics, thereby accurately and holistically analyzing a player's game and going beyond traditional statistical reporting, by ushering in intriguing and insightful information.