https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset contains data about NCAA Basketball games, teams, and players. Game data covers play-by-play and box scores back to 2009, as well as final scores back to 1996. Additional data about wins and losses goes back to the 1894-5 season in some teams' cases.
You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.github_repos.[TABLENAME]
. Fork this kernel to get started to learn how to safely manage analyzing large BigQuery datasets.
Sportradar: Copyright Sportradar LLC. Access to data is intended solely for internal research and testing purposes, and is not to be used for any business or commercial purpose. Data are not to be exploited in any manner without express approval from Sportradar.
NCAA®: Copyright National Collegiate Athletic Association. Access to data is provided solely for internal research and testing purposes, and may not be used for any business or commercial purpose. Data are not to be exploited in any manner without express approval from the National Collegiate Athletic Association.
MIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
This Kaggle dataset comes from an output dataset that powers my March Madness Data Analysis dashboard in Domo. - Click here to view this dashboard: Dashboard Link - Click here to view this dashboard features in a Domo blog post: Hoops, Data, and Madness: Unveiling the Ultimate NCAA Dashboard
This dataset offers one the most robust resource you will find to discover key insights through data science and data analytics using historical NCAA Division 1 men's basketball data. This data, sourced from KenPom, goes as far back as 2002 and is updated with the latest 2025 data. This dataset is meticulously structured to provide every piece of information that I could pull from this site as an open-source tool for analysis for March Madness.
Key features of the dataset include: - Historical Data: Provides all historical KenPom data from 2002 to 2025 from the Efficiency, Four Factors (Offense & Defense), Point Distribution, Height/Experience, and Misc. Team Stats endpoints from KenPom's website. Please note that the Height/Experience data only goes as far back as 2007, but every other source contains data from 2002 onward. - Data Granularity: This dataset features an individual line item for every NCAA Division 1 men's basketball team in every season that contains every KenPom metric that you can possibly think of. This dataset has the ability to serve as a single source of truth for your March Madness analysis and provide you with the granularity necessary to perform any type of analysis you can think of. - 2025 Tournament Insights: Contains all seed and region information for the 2025 NCAA March Madness tournament. Please note that I will continually update this dataset with the seed and region information for previous tournaments as I continue to work on this dataset.
These datasets were created by downloading the raw CSV files for each season for the various sections on KenPom's website (Efficiency, Offense, Defense, Point Distribution, Summary, Miscellaneous Team Stats, and Height). All of these raw files were uploaded to Domo and imported into a dataflow using Domo's Magic ETL. In these dataflows, all of the column headers for each of the previous seasons are standardized to the current 2025 naming structure so all of the historical data can be viewed under the exact same field names. All of these cleaned datasets are then appended together, and some additional clean up takes place before ultimately creating the intermediate (INT) datasets that are uploaded to this Kaggle dataset. Once all of the INT datasets were created, I joined all of the tables together on the team name and season so all of these different metrics can be viewed under one single view. From there, I joined an NCAAM Conference & ESPN Team Name Mapping table to add a conference field in its full length and respective acronyms they are known by as well as the team name that ESPN currently uses. Please note that this reference table is an aggregated view of all of the different conferences a team has been a part of since 2002 and the different team names that KenPom has used historically, so this mapping table is necessary to map all of the teams properly and differentiate the historical conferences from their current conferences. From there, I join a reference table that includes all of the current NCAAM coaches and their active coaching lengths because the active current coaching length typically correlates to a team's success in the March Madness tournament. I also join another reference table to include the historical post-season tournament teams in the March Madness, NIT, CBI, and CIT tournaments, and I join another reference table to differentiate the teams who were ranked in the top 12 in the AP Top 25 during week 6 of the respective NCAA season. After some additional data clean-up, all of this cleaned data exports into the "DEV _ March Madness" file that contains the consolidated view of all of this data.
This dataset provides users with the flexibility to export data for further analysis in platforms such as Domo, Power BI, Tableau, Excel, and more. This dataset is designed for users who wish to conduct their own analysis, develop predictive models, or simply gain a deeper understanding of the intricacies that result in the excitement that Division 1 men's college basketball provides every year in March. Whether you are using this dataset for academic research, personal interest, or professional interest, I hope this dataset serves as a foundational tool for exploring the vast landscape of college basketball's most riveting and anticipated event of its season.
This dataset lists point data for all schools involved with NCAA division I women's college basketball.
This dataset provides point data for all NCAA Division 1 college men's basketball schools, as of 2008.
This dataset explores NCAA men's division two basketball by placing a point at every school that participates, as of 2008. Source: NCAA website
https://winsipedia.com/termshttps://winsipedia.com/terms
Comprehensive dataset of college football teams ranked by all time record. Includes historical data, statistics, and performance metrics for NCAA Division I FBS teams.
This data explores division III men's basketball through the NCAA. Each NCAA D3 men's basketball program is noted by a point, based on the latitude and longitude of the school. This data was complied through the NCAA website and is current as of March 2008.
The National Basketball Association has one of the highest percentages of African American players from the big four professional sports leagues in North America. In 2023, approximately **** percent of NBA players were African American. Meanwhile, ethnically white players constituted a **** percent share of all NBA players that year. After the WNBA and NBA, the National Football League had the largest share of African Americans in a professional sports league in North America. How do other roles in the NBA compare? When it comes to African American representation in the NBA, no other role in the NBA is as well represented by African Americans as players. Meanwhile, on the opposite end of the scale, less than **** percent of team governors in the NBA were African American in 2023. During the 2022/23 season, the role with the second-highest share of African Americans was head coach, with a share of ** percent. That season, the number of African American head coaches in the NBA exceeded the number of white head coaches for the first time. African Americans in the NFL In 2022, the greatest share of players by ethnicity in the NFL were African American, with more than half of all NFL players falling within this group. The representation of African Americans in American Football extended beyond the playing field, with **** percent of NFL assistant coaches being African American in 2022 as well. However, positions such as vice presidents and head coaches were less representative of the African American population, as less than ** percent of the individuals fulfilling these roles in 2022 were African American.
This dataset shows all NCAA men's basketball programs as of March 2008. This data was compiled from the NCAA website.
This data explores women's NCAA division III basketball. Each school participating in NCAA D3 women's basketball has been marked with a point at their latitude and longitude coordinates. This data was compiled from the NCAA website and is current as of March 2008.
This data shows every NCAA women's basketball program as of March 2008. This data was compiled from the NCAA website.
This data explores NCAA division II women's basketball programs in the United States as of 2008. Each school is evident by point data according to their latitude and longitude coordinates.
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https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
This dataset contains data about NCAA Basketball games, teams, and players. Game data covers play-by-play and box scores back to 2009, as well as final scores back to 1996. Additional data about wins and losses goes back to the 1894-5 season in some teams' cases.
You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.github_repos.[TABLENAME]
. Fork this kernel to get started to learn how to safely manage analyzing large BigQuery datasets.
Sportradar: Copyright Sportradar LLC. Access to data is intended solely for internal research and testing purposes, and is not to be used for any business or commercial purpose. Data are not to be exploited in any manner without express approval from Sportradar.
NCAA®: Copyright National Collegiate Athletic Association. Access to data is provided solely for internal research and testing purposes, and may not be used for any business or commercial purpose. Data are not to be exploited in any manner without express approval from the National Collegiate Athletic Association.