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.

Of the big four professional sports leagues in North America, the NFL and the NBA have the highest percentage of African American players. In 2023, **** percent of NBA players were African American, as well as half of the head coaches within the league.

A survey conducted in January 2025 in the United States revealed that over half of NBA fans were Caucasian. Meanwhile, 20.7 percent were Hispanic.

The National Basketball Association is a professional basketball league in North America. While ** percent of fans of the NBA were Black, this number varied between fans of each individual team. Approximately ** percent of Los Angeles Clippers fans were Black, while this figure stood at ** percent among supporters of the Boston Celtics.

In 2023, over ** percent of the team presidents within the NBA were white, while *** percent were African American. This was a slight increase in the share of African American team presidents from the previous year. Meanwhile, the share of female team presidents in the NBA that year was **** percent, which was a significant increase from 2022, when that figure was **** percent.

NBA Team Market Size updated 2022 - TV Market Size - Metro Population in according city/state - Team Revenue

Professional sports leagues in North America have traditionally been home to athletes from many backgrounds and ethnicities. In the 2023 season, over ** percent of the players in the National Basketball Association (NBA) were African American. In comparison, **** percent of NBA athletes were white and *** percent were Hispanic.

In the 2022/23 NBA season, there were ** African American head coaches in comparison to ** white head coaches. Going back to 2010, this was the first time that the number of African American head coaches in the NBA exceeded the number of white head coaches. Head coach of Miami Heat, Erik Spoelstra, remained the only Asian-American coach in the league.

Context

I was trying to device a statical analysis of who is winning the MVP race this year.

Content

For each player, there are approximately 45 statistical categories ranging from basic stats like rebounds, points, steals, etc, to more advanced stats like usage rate, and offensive win share. These advanced stats are usually a formulation of the basic stats, so it is extremely likely that we could remove some categories.

Acknowledgements

The data was collected from NBA-reference.com. Easily the best NBA stats website.

Inspiration

Right now it looks like a toss up between Giannis and Harden for who will win MVP. Using statistics (not the sports analyst eye-test), can we rightfully determine who is winning the race?

Major US Sports Venues Usage and Affiliations

Team, League, Conference and Population Usage Records

By Homeland Infrastructure Foundation [source]

About this dataset

This dataset provides detailed information on major sport venues, along with their usage and affiliations. It includes data related to the National Association for Stock Car Auto Racing, Indy Racing League, Major League Soccer, Major League Baseball, National Basketball Association, Women's National Basketball Association, National Hockey League, National Football League, PGA Tour, NCAA Division 1 FBS Football, NCAA Division 1 Basketball and thoroughbred horse racing.* This dataset contains columns such as USE (which describes the type of use for the venue), TEAM (the team associated with the venue), LEAGUE (the league associated with the venue) , CONFERENCE (the conference associated with the venue), DIVISION (the division associated with the venue), INST_AFFIL(the institution affiliation associatedwith the venue), TRACK_TYPE(type of track at a specific point in time or over its complete life-cycle) as well as LENGTH_MILEGE ('length of track in milege') ROOF_TYPE(The type of roof covering used at a specific point in time or over its complete life-cycle) and plenty other variables. With this astounding range and quantity of data points -- spanning countries across different continents and leagues -- explore patterns in sports games you never even thought were possible!

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How to use the dataset

The MajorUS Sports Venues Usage and Affiliations dataset includes data on major sports venues from leagues including National Association for Stock Car Auto Racing (NASCAR), Indy Racing League (IRL), Major League Soccer (MLS), Major League Baseball (MLB), National Basketball Association (NBA), Women's National Basketball Association (WNBA), National Hockey League (NHL), National Football League(NFL), PGA Tour, NCAA Division 1 FBS Football, NCAA Division 1 Basketball, and thoroughbred horse racing. The columns provided include USE_, USE_POP, TEAM, LEAGUE,CONFERENCE,DIVISION ,INST_AFFIL,TRACK_TYPE. LENGTH_MI,ROOF_TYPESTADIUM_SH,`ADDDATAE , USEWEBSITE',and'COMMENTS'.

The `USE~ column specifies the type of usage of each venue at which point can be college athletics or professional athletics. The corresponding column to this is the ‘USE~POP’ which informs you about how many people are using each venue for a particular sport at a given time. For example if there were 6 NHL games being played that day then USE~ would say “professional Athletics” while USE~POP would state “NNN” reflecting there were NNN people spectating those events collectively: The next column is TEAM which represents what team sponsors or manages each venue or what teams will be playing in them.

 Following on from TEAM is LEAGUE; here you can find out what league each team represents such as MLB, NBA etc… The next three columns CONFERENCE/DIVISION/INST ~ AFFIL provide more specific details as they blur into collegiate level as well where CONFERENCE indicates which conference they belong within their respective division: while INST ~ AFFIL states its affiliated school body e.g.: Southeastern Conference > University of Arkansas Razorbacks . Rounding up our overview these last three columns TRACK ~ TYPE/LENGTH

Research Ideas

• Analyzing the affiliations and usage of different sports venues to determine which teams or leagues have the most presence across a certain geographic area.
• Comparing different stadiums within a given conference in terms of their roof type, track length, and stadium shape for optimal design features for new construction projects.
• Placing sponsorships or advertisements within each sporting arena based on audience size, league popularity, and team affiliation within a given conference or division

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contribut...

This dataset contains all the data of the players listed in the NBA 2K25 games developed by 2K. The dataset is made out of three big parts, the biodata of the player, the attributes, and the badges. At this moment, there is no more missing data that is due to the connection issue of the web scraper as I added the validation process algorithm on my code. Soon I will be adding the data for the hot zones of every player.

Please kindly upvote this dataset! 😉

I do not own any part of the data, the data is scraped from https://www.2kratings.com/. So hopefully this dataset can you help you in some way especially in learning about data science or statistics.

If you have any question or suggestion, please let me know. Thanks a lot!

Columns explanation: 1. name : Player's full name (suffix included). 2. nationality_1 : Player's main nationality. 3. nationality_2 : Player's second nationality for player's with multiple nationality. 4. team : Player's current NBA team. 5. jersey : Player's current jersey number. 6. position_1 : Player's main position on the team lineup. 7. position_2 : Player's secondary position on the team lineup. 8. archetype : Player's type/characteristics of gameplay in a game. 9. height_feet : Player's height in feet and inch (separated by ' and "). 10. height_cm : Player's height in centimeters. 11. weight_lbs : Player's weight in pounds. 12. weight_kg : Player's weight in kilograms. 13. wingspan_feet : Player's wingspan in feet and inch (separated by ' and "). 14. wingspan_cm : Player's wingspan in centimeters. 15. season_salary : Player's salary in a season (numerical value). 16. years_in_the_nba : Player's professional years in the NBA. 17. birthdate : Player's birthdate (format : "Month dd, Year"). 18. hometown : Player's hometown (format : "City, State/Country"). 19. prior_to_nba : Player's prior to NBA (city, state, Uni, or country).

In 2023, over ** percent of players in the Women's National Basketball Association (WNBA) were black or African American. Meanwhile, just *** percent of players in the league identified as Asian.

This dataset, named "state_trends.csv," contains information about different U.S. states. Let's break down the attributes and understand what each column represents:

1. state: The name of the U.S. state.
2. state_code: The two-letter postal code abbreviation for the state.
3. population: The population of the state.
4. sq_miles: The total land area of the state in square miles.
5. pop_density: Population density, which is the number of people per square mile.
6. region: The geographical region of the United States to which the state belongs (e.g., South, West).
7. psych_region: A description of the psychological region based on personality traits.
8. psy_reg: A shortened version of the psychological region.
9. extraversion: A measure of the state's population tendency toward extraversion.
10. agreeableness: A measure of the state's population tendency toward agreeableness.
11. conscientiousness: A measure of the state's population tendency toward conscientiousness.
12. neuroticism: A measure of the state's population tendency toward neuroticism.
13. openness: A measure of the state's population tendency toward openness.
14. data_science: A score related to the state's interest or proficiency in the field of data science.
15. artificial_intelligence: A score related to the state's interest or proficiency in artificial intelligence.
16. machine_learning: A score related to the state's interest or proficiency in machine learning.
17. data_analysis: A score related to the state's interest or proficiency in data analysis.
18. business_intelligence: A score related to the state's interest or proficiency in business intelligence.
19. spreadsheet: A score related to the state's interest or proficiency in spreadsheet usage.
20. statistics: A score related to the state's interest or proficiency in statistics.
21. art: A score related to the state's interest or involvement in the field of art.
22. dance: A score related to the state's interest or involvement in dance.
23. museum: A score related to the state's interest or presence of museums.
24. basketball: A score related to the state's interest or involvement in basketball.
25. football: A score related to the state's interest or involvement in football.
26. baseball: A score related to the state's interest or involvement in baseball.
27. soccer: A score related to the state's interest or involvement in soccer.
28. hockey: A score related to the state's interest or involvement in hockey.
29. has_nba: Indicates whether the state has a National Basketball Association (NBA) team (Yes/No).
30. has_nfl: Indicates whether the state has a National Football League (NFL) team (Yes/No).
31. has_mlb: Indicates whether the state has a Major League Baseball (MLB) team (Yes/No).
32. has_mls: Indicates whether the state has a Major League Soccer (MLS) team (Yes/No).
33. has_nhl: Indicates whether the state has a National Hockey League (NHL) team (Yes/No).
34. has_any: Indicates whether the state has any of the mentioned professional sports teams (Yes/No).

In summary, this dataset provides a variety of information about U.S. states, including demographic data, geographical region, psychological region, personality traits, and scores related to interests or proficiencies in various fields such as data science, art, and sports.

The National Basketball Association is a professional basketball league for men with ** teams competing against each other in the United States and Canada. During a 2020 survey in the United States, ** percent of NBA fans were Hispanic.

The number of piglets born alive (NBA) per litter is one of the most important traits in pig breeding due to its influence on production efficiency. It is difficult to improve NBA because the heritability of the trait is low and it is governed by a high number of loci with low to moderate effects. To clarify the biological and genetic background of NBA, genome-wide association studies (GWAS) were performed using 4,012 Large White and Landrace pigs from herdbook and commercial breeding companies in Germany (3), Austria (1) and Switzerland (1). The animals were genotyped with the Illumina PorcineSNP60 BeadChip. Because of population stratifications within and between breeds, clusters were formed using the genetic distances between the populations. Five clusters for each breed were formed and analysed by GWAS approaches. In total, 17 different significant markers affecting NBA were found in regions with known effects on female reproduction. No overlapping significant chromosome areas or QTL between Large White and Landrace breed were detected.

Basketball is a commonly watched sport both in the United States and worldwide. The survey depicts the level of interest in the sport in the United States and it shows that 38 percent of African American respondents were casual fans of NBA as of May 2020.

NCAA men's basketball is the college level of basketball played in the United States and is seen as the final step up before the NBA. In a survey conducted in March 2023, around ** percent of Hispanic respondents stated that they were avid fans of NCAA men's college basketball in the United States.

This graph shows the average minutes of NBA viewed on television during the ********* in the United States, by ethnicity. According to the source, Asian-Americans watched an average of *** minutes of NBA games during the ********* season.

During the 2024/25 NBA season, just under ** percent of players were from overseas. This was a slight increase over the previous season, however, remained the level recorded in 2022/23, when it stood at ***** percent. During that season, over *** players featured in at least one NBA game, while *** players appeared in 2024/25.

As of 2024, the largest luxury tax bill footed by a team in the NBA came in the 2023/24 season, when the Golden State Warriors were taxed 176.9 million U.S. dollars by the league. The Warriors also held the other top-three spots, bringing their overall luxury tax payments from 2021/22 to 2023/24 to 510.9 million U.S. dollars.