5 datasets found
  1. Super Bowl Game Records

    • kaggle.com
    Updated Dec 10, 2023
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    The Devastator (2023). Super Bowl Game Records [Dataset]. https://www.kaggle.com/datasets/thedevastator/super-bowl-game-records
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 10, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    The Devastator
    Description

    Super Bowl Game Records

    2019 Super Bowl Game Records

    By Throwback Thursday [source]

    About this dataset

    This dataset provides comprehensive information about Super Bowl games that took place in 2019, including game details such as the winning team, losing team, venue, city, attendance, network that broadcasted the game, average number of viewers in the United States who watched the game, rating (representing the percentage of households with televisions that were tuned into the game), share (representing the percentage of households with televisions in use that were tuned into the game), and cost per 30-second advertisement. Additionally, this dataset includes specific details about each Super Bowl game such as the final score (in terms of winning team points minus losing team points), conference affiliations of both winning and losing teams, and any additional notes or information about each respective Super Bowl. All of these data points collectively provide a comprehensive overview of each recorded Super Bowl game from 2019

    How to use the dataset

    • Game details: The 'Game' column represents the number or identifier of the Super Bowl game. For example, '1' indicates it is the first Super Bowl game.

    • Winning team: The 'Winning team' column lists the name of the team that won the Super Bowl game. For example, 'New England Patriots'.

    • Winning Team Points: The 'Winning Team Points' column shows the number of points scored by the winning team in that particular game.

    • Winning Team Conference: The 'Winning Team Conference' column indicates which conference (e.g., AFC or NFC) the winning team belongs to.

    • Score: The 'Score' column displays a summary of the final score in each game, showcasing how many points were scored by both teams in this format - Winning Team Points - Losing Team Points.

    • Losing team: Similar to winning teams, losing teams are listed under the 'Losing team' column.

    • Losing Team Conference: This column represents which conference (e.g., AFC or NFC)the losing team belongs to.

    • Venue and city: The columns 'Venue' and 'City' show where each Super Bowl game was played, respectively.

    • Attendance : This column shows numbers associated with how many people attended a particular super bowl event

    • Network : Indicates Television network for broadcasted super bowl

    11.Average U.S viewers : It denotes average number of viewers in United States who watched a specific super bowl

    12.Rating & Share : These represent data associated with watching percentage (Rating)and households televisions percanton tuned into a particular event(Share).

    13.Cost Per 30s Ad: The 'Cost Per 30s Ad' column specifies the cost of a 30-second advertisement during the Super Bowl game in dollars.

    14.Notes: The 'Notes' column includes additional notes or information about each Super Bowl game.

    This dataset provides a comprehensive record of every Super Bowl game that took place in 2019. By analyzing these attributes, you can gain insights into team performance, viewer interest, and commercial aspects of the games. Use this guide to explore and analyze the dataset effectively for your analysis or research purposes

    Research Ideas

    • Analyzing the popularity and reach of the Super Bowl: With data on average U.S. viewers, rating, share, and cost per 30-second ad, this dataset can be used to analyze the Super Bowl's popularity and reach. By comparing these metrics across different games, one can assess how the viewership and interest in the Super Bowl has changed over time.
    • Evaluating advertising effectiveness during the Super Bowl: The dataset includes information on the cost per 30-second ad during each Super Bowl game. This data can be used to analyze whether there is a correlation between ad costs and viewer ratings or share. It can also help marketers and advertisers understand how effective their advertisements were in reaching a wide audience during past Super Bowls.
    • Studying game attendance trends: The dataset provides information on attendance at each Super Bowl game. By analyzing this data, one can identify trends in game attendance over the years and evaluate factors that may impact ticket sales such as venue location or teams competing in the game. This analysis could be useful for event organizers and stadium operators looking to optimize future hosting decisions for large-scale events like sports championships or music festivals

    Acknowledgements

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

    License

    See the dataset descrip...

  2. Likelihood of watching the Super Bowl in the U.S. 2007-2025

    • statista.com
    Updated Feb 14, 2025
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    Christina Gough (2025). Likelihood of watching the Super Bowl in the U.S. 2007-2025 [Dataset]. https://www.statista.com/topics/1264/super-bowl/
    Explore at:
    Dataset updated
    Feb 14, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Christina Gough
    Description

    The Super Bowl is the highlight of the NFL season, watched by millions in the United States and many more across the world. During a 2025 survey in the United States, around 78 percent of respondents stated that they planned to watch Super Bowl LIX between the Kansas City Chiefs and the San Francisco 49ers.

  3. Super Bowl most anticipated parts in the U.S. 2025

    • statista.com
    Updated Feb 14, 2025
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    Christina Gough (2025). Super Bowl most anticipated parts in the U.S. 2025 [Dataset]. https://www.statista.com/topics/1264/super-bowl/
    Explore at:
    Dataset updated
    Feb 14, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Christina Gough
    Description

    The Super Bowl is one of the highlights of the sporting calendar, but many viewers tune in for more than just the game itself. During a January 2025 survey in the United States, almost 35 percent of respondents stated that the famous Super Bowl commercials were one of the parts of the event they were looking forward to.

  4. Madden 21 Weekly Player Ratings (Top 800 Players)

    • kaggle.com
    Updated Feb 23, 2021
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    Ryan Goodwin (2021). Madden 21 Weekly Player Ratings (Top 800 Players) [Dataset]. https://www.kaggle.com/datasets/ryangoodwin/madden-21-weekly-player-ratings-top-800-players
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Feb 23, 2021
    Dataset provided by
    Kaggle
    Authors
    Ryan Goodwin
    Description

    Context

    I originally wanted to see how NFL an player's game stats impact their Madden rating. I could not find a comprehensive Database of Madden Ratings and updates anywhere, so I created my own.

    Content

    The dataset contains weekly rating updates in Madden 21 for the top ~800 players. It includes overall ratings as well as ratings for each player attribute that Madden scores.

    Acknowledgements

    I'd like to acknowledge EA sports for posting ratings updates every week on their website ea.com.

    Inspiration

    Feel free to explore the ratings and see what players made big jumps or took big falls, and what may have contributed to these changes in rating.

  5. Events Tickets Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Events Tickets Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/event-tickets-market
    Explore at:
    csv, pdf, pptxAvailable download formats
    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Events Tickets Market Outlook



    The global events tickets market size was valued at approximately USD 68.5 billion in 2023 and is projected to reach USD 110.3 billion by 2032, growing at a CAGR of 5.4% during the forecast period. This significant growth is driven by the increasing popularity of live events, advancements in digital ticketing platforms, and the rising disposable incomes of consumers worldwide.



    The burgeoning growth of the events tickets market is primarily fueled by the relentless rise in live entertainment and sports events, which have become a vital part of social and cultural life. The proliferation of music festivals, concerts, theatrical performances, and sporting events has created a robust demand for event tickets. Additionally, the growing trend of experiential spending, where consumers prioritize spending on experiences over material goods, further propels the market. Technological advancements, particularly in mobile ticketing and blockchain technology, enhance the convenience and security of purchasing tickets, thus driving market growth.



    Another significant growth factor is the increasing integration of advanced technologies such as artificial intelligence and machine learning into ticketing platforms. These technologies optimize customer experiences by providing personalized recommendations and dynamic pricing models. Furthermore, the implementation of augmented reality (AR) and virtual reality (VR) in events offers immersive experiences, thus attracting a broader audience and boosting ticket sales. The widespread adoption of mobile payments and digital wallets also facilitates seamless transactions, contributing to market expansion.



    The shift of ticket sales from traditional offline methods to online platforms has revolutionized the events tickets market. Online ticketing platforms offer several advantages, including ease of access, a wide range of options, and secure payment gateways, which enhance user satisfaction. The convenience of purchasing tickets from anywhere at any time, coupled with the ability to compare prices and read reviews, has led to a substantial increase in online ticket sales. Moreover, social media marketing and influencer endorsements play a pivotal role in promoting events and driving ticket sales, particularly among younger demographics.



    Live Entertainment Platforms have become a cornerstone in the events tickets market, transforming the way audiences engage with performances. These platforms provide a seamless interface for users to discover and access a wide array of live events, from concerts and theater productions to sports and festivals. By leveraging advanced technologies, live entertainment platforms offer personalized recommendations and real-time updates, enhancing the overall user experience. The integration of social media features allows users to share their experiences and connect with fellow enthusiasts, further amplifying the reach and popularity of events. As consumer preferences shift towards digital solutions, live entertainment platforms are poised to play a pivotal role in driving ticket sales and expanding market reach.



    Regionally, North America holds a substantial share of the events tickets market, attributed to the high number of live events, robust digital infrastructure, and the presence of major market players. Europe follows closely, driven by a rich cultural heritage and a high disposable income. The Asia Pacific region is expected to witness the highest growth rate during the forecast period, fueled by rapid urbanization, increasing internet penetration, and a burgeoning middle class with a growing appetite for entertainment. Latin America and the Middle East & Africa regions are also anticipated to experience significant growth, supported by a rising number of events and improving economic conditions.



    Type Analysis



    The events tickets market is segmented by type into sports, concerts, theater, festivals, and others. Each segment caters to a unique audience and contributes differently to the overall market dynamics. Sports events dominate the market, driven by the global popularity of various sports such as football, basketball, and cricket. Major sports leagues and events like the FIFA World Cup, the Olympics, and the Super Bowl attract millions of spectators, both in-person and online, creating a substantial demand for tickets. Sponsorships, media rights, and merchandise sales further amplify the revenue generated from sports events.

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Click to copy link
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The Devastator (2023). Super Bowl Game Records [Dataset]. https://www.kaggle.com/datasets/thedevastator/super-bowl-game-records
Organization logo

Super Bowl Game Records

2019 Super Bowl Game Records

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Dec 10, 2023
Dataset provided by
Kagglehttp://kaggle.com/
Authors
The Devastator
Description

Super Bowl Game Records

2019 Super Bowl Game Records

By Throwback Thursday [source]

About this dataset

This dataset provides comprehensive information about Super Bowl games that took place in 2019, including game details such as the winning team, losing team, venue, city, attendance, network that broadcasted the game, average number of viewers in the United States who watched the game, rating (representing the percentage of households with televisions that were tuned into the game), share (representing the percentage of households with televisions in use that were tuned into the game), and cost per 30-second advertisement. Additionally, this dataset includes specific details about each Super Bowl game such as the final score (in terms of winning team points minus losing team points), conference affiliations of both winning and losing teams, and any additional notes or information about each respective Super Bowl. All of these data points collectively provide a comprehensive overview of each recorded Super Bowl game from 2019

How to use the dataset

  • Game details: The 'Game' column represents the number or identifier of the Super Bowl game. For example, '1' indicates it is the first Super Bowl game.

  • Winning team: The 'Winning team' column lists the name of the team that won the Super Bowl game. For example, 'New England Patriots'.

  • Winning Team Points: The 'Winning Team Points' column shows the number of points scored by the winning team in that particular game.

  • Winning Team Conference: The 'Winning Team Conference' column indicates which conference (e.g., AFC or NFC) the winning team belongs to.

  • Score: The 'Score' column displays a summary of the final score in each game, showcasing how many points were scored by both teams in this format - Winning Team Points - Losing Team Points.

  • Losing team: Similar to winning teams, losing teams are listed under the 'Losing team' column.

  • Losing Team Conference: This column represents which conference (e.g., AFC or NFC)the losing team belongs to.

  • Venue and city: The columns 'Venue' and 'City' show where each Super Bowl game was played, respectively.

  • Attendance : This column shows numbers associated with how many people attended a particular super bowl event

  • Network : Indicates Television network for broadcasted super bowl

11.Average U.S viewers : It denotes average number of viewers in United States who watched a specific super bowl

12.Rating & Share : These represent data associated with watching percentage (Rating)and households televisions percanton tuned into a particular event(Share).

13.Cost Per 30s Ad: The 'Cost Per 30s Ad' column specifies the cost of a 30-second advertisement during the Super Bowl game in dollars.

14.Notes: The 'Notes' column includes additional notes or information about each Super Bowl game.

This dataset provides a comprehensive record of every Super Bowl game that took place in 2019. By analyzing these attributes, you can gain insights into team performance, viewer interest, and commercial aspects of the games. Use this guide to explore and analyze the dataset effectively for your analysis or research purposes

Research Ideas

  • Analyzing the popularity and reach of the Super Bowl: With data on average U.S. viewers, rating, share, and cost per 30-second ad, this dataset can be used to analyze the Super Bowl's popularity and reach. By comparing these metrics across different games, one can assess how the viewership and interest in the Super Bowl has changed over time.
  • Evaluating advertising effectiveness during the Super Bowl: The dataset includes information on the cost per 30-second ad during each Super Bowl game. This data can be used to analyze whether there is a correlation between ad costs and viewer ratings or share. It can also help marketers and advertisers understand how effective their advertisements were in reaching a wide audience during past Super Bowls.
  • Studying game attendance trends: The dataset provides information on attendance at each Super Bowl game. By analyzing this data, one can identify trends in game attendance over the years and evaluate factors that may impact ticket sales such as venue location or teams competing in the game. This analysis could be useful for event organizers and stadium operators looking to optimize future hosting decisions for large-scale events like sports championships or music festivals

Acknowledgements

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

License

See the dataset descrip...

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