Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
This dataset encompasses detailed ball-by-ball data and match information for various cricket matches available in cricsheet website. The data provides an in-depth analysis at the granular level, capturing every ball bowled, the runs scored, the type of dismissal, and more.
Acknowledgment: A big shoutout to Cricsheet for making such comprehensive cricket data available to the public. Their open-source initiative has empowered enthusiasts and analysts to understand the game better.
Data Extraction Process: The raw data was sourced from Cricsheet in JSON format. A systematic extraction process was followed using Python, where each file was parsed to extract ball-by-ball data and match metadata. The data was then transformed and cleaned to form structured datasets, making it easier for researchers, analysts, and cricket enthusiasts to derive insights.
Usage: This dataset is perfect for those looking to perform detailed cricket match analyses, understand patterns, player performances, or even develop predictive models. Whether you're a data scientist, a cricket enthusiast, or someone looking to delve into sports analytics, this dataset offers a plethora of opportunities.
Ball-by-Ball Dataset:
Match Info Dataset:
No description was included in this Dataset collected from the OSF
(UNCLASSIFIED) Recreation is broken down into the following types: Sports Facility, Pool, Park and Other. Sports Facilities include any field where sports are played professional or leisurely and include basketball courts, soccer stadiums and fields, tennis courts, etc. Parks include recreational areas around the cities.Development of Liberia’s recreational locations has taken a backseat in the post-war era to rehabilitation of critical infrastructure and services. Despite the resulting scarcity of parks and sports facilities throughout the country, soccer has surged in popularity and is by far the country’s most popular sport. The Liberian national team, nicknamed the Lone Stars for the Liberian flag, has seen a surge in popularity despite never having qualified for a World Cup. Semi-professional local teams have also experienced growing interest and have seen a 40 percent increase in match-attendance since 2014. An inter-county tournament is held annually for the sport’s highest award in the country, the Barclay Shield. Basketball, swimming, and squash are popular in Liberia’s urban areas, especially Monrovia, despite a lack of facilities outside of hotels and expatriate clubs. School children play soccer and kickball—typically on bare patches of earth rather than formal fields—as well as marbles (usually using dried seeds).Attribute Table Field DescriptionsISO3 - International Organization for Standardization 3-digit country code ADM0_NAME - Administration level zero identification / name ADM1_NAME - Administration level one identification / name ADM2_NAME - Administration level two identification / name NAME - Name of recreation area TYPE - Classification in the geodatabase CITY - City location available SPA_ACC - Spatial accuracy of site location (1 – high, 2 – medium, 3 – low) COMMENTS - Comments or notes regarding the recreation area SOURCE_DT - Source one creation date SOURCE - Source one SOURCE2_DT - Source two creation date SOURCE2 - Source two CollectionThis feature class was generated utilizing data from Wikimapia, OpenStreetMap, and other sources. Wikimapia is open-content mapping focused on gathering all geographical objects in the world. OpenStreetMap is a free worldwide map, created by crowd-sourcing.Consistent naming conventions for geographic locations were attempted but name variants may exist which can include historical or less widespread interpretations.The data included herein have not been derived from a registered survey and should be considered approximate unless otherwise defined. While rigorous steps have been taken to ensure the quality of each dataset, DigitalGlobe is not responsible for the accuracy and completeness of data compiled from outside sources.Metadata information was collected from an encyclopedia entry, an article published by BET, as well as a book on Liberian culture and recreation.Sources (HGIS)DigitalGlobe, “DigitalGlobe Imagery Archive.” Accessed October 03, 2014. Google, October 2014. Accessed October 03, 2014. www.google.com.OpenStreetMap, “Liberia.” October 2014. Accessed October 03, 2014. http://www.openstreetmap.org.Wikimapia, “Liberia.” October 2014. Accessed October 03, 2014. http://wikimapia.org.Sources (Metadata)Hicks, Jonathan P. “In Liberia, Soccer Is Bringing People Together: The West African nation is seeing a resurgance in the sport known as football, with attendance and sponsorships up.” BET. April 03, 2014. Accessed October 03, 2014. http://www.bet.com.Levy, Patricia and Michael Spilling. Cultures of the World: Liberia. 2010. Accessed October 03, 2014. http://books.google.com.Petterson, Donald Rahl. “Liberia: Sports and Recreation.” Encyclopedia Britannica Online. August 27, 2014. Accessed October 03, 2014. http://www.britannica.com.
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Apache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
This dataset encompasses detailed ball-by-ball data and match information for various cricket matches available in cricsheet website. The data provides an in-depth analysis at the granular level, capturing every ball bowled, the runs scored, the type of dismissal, and more.
Acknowledgment: A big shoutout to Cricsheet for making such comprehensive cricket data available to the public. Their open-source initiative has empowered enthusiasts and analysts to understand the game better.
Data Extraction Process: The raw data was sourced from Cricsheet in JSON format. A systematic extraction process was followed using Python, where each file was parsed to extract ball-by-ball data and match metadata. The data was then transformed and cleaned to form structured datasets, making it easier for researchers, analysts, and cricket enthusiasts to derive insights.
Usage: This dataset is perfect for those looking to perform detailed cricket match analyses, understand patterns, player performances, or even develop predictive models. Whether you're a data scientist, a cricket enthusiast, or someone looking to delve into sports analytics, this dataset offers a plethora of opportunities.
Ball-by-Ball Dataset:
Match Info Dataset: