This dataset contains a list of video games with sales greater than 100,000 copies. It was generated by a scrape of vgchartz.com.

Fields include

• Rank - Ranking of overall sales

• Name - The games name

• Platform - Platform of the games release (i.e. PC,PS4, etc.)

• Year - Year of the game's release

• Genre - Genre of the game

• Publisher - Publisher of the game

• NA_Sales - Sales in North America (in millions)

• EU_Sales - Sales in Europe (in millions)

• JP_Sales - Sales in Japan (in millions)

• Other_Sales - Sales in the rest of the world (in millions)

• Global_Sales - Total worldwide sales.

The script to scrape the data is available at https://github.com/GregorUT/vgchartzScrape. It is based on BeautifulSoup using Python. There are 16,598 records. 2 records were dropped due to incomplete information.

Video gaming is a popular way for gamers to connect with friends and family, and many gamers have formed relationships through video games. During a February 2025 survey, 78 percent of responding gamers in the United States agreed that playing games can introduce people to new friends.

Introduction

Video Game Statistics: The video game industry has evolved from a niche hobby into a global entertainment giant, impacting technology, culture, and economics. With millions of players across the globe and a market worth billions, understanding video game statistics is vital for developers, investors, marketers, and enthusiasts.

These statistics offer valuable insights into player behavior, market trends, sales performance, and emerging technologies, enabling the identification of patterns, forecasting growth, and shaping strategies within the industry. This statistics will delve into the latest trends in video game sales, platform popularity, gamer engagement, and industry innovations, providing a data-driven overview of the gaming landscape today and in the future.

Description:

This dataset offers a detailed overview of video games across various platforms. It encompasses a broad range of information, making it a valuable resource for understanding the evolution, popularity, and thematic diversity of video games. Ideal for analysis of gaming trends, player preferences, and platform-specific dynamics, this dataset is a key tool for researchers, game developers, and market analysts.

Features:

• name: The title of the video game.
• platform: The gaming platform on which the game is available (e.g., PlayStation, Xbox).
• release_date: The date when the game was released.
• summary: A brief description or summary of the game's storyline or key features.
• user_review: User review rating, indicating the game's reception and popularity.

Use Case:

This dataset is instrumental for various analyses, including: - Trend analysis in the gaming industry. - Comparative studies of games across different platforms. - Understanding the correlation between game features and user ratings. - Market analysis for predicting future gaming trends and preferences.

Note:

• The dataset provides an extensive view of the gaming world, helping to gauge shifts in gaming culture and technology over time.
• It can be used to analyze the impact of narrative, gameplay, and platform choice on the success of video games.

Video gaming is no longer just a hobby of teenagers - thanks to developments in gaming technology and the accessibility of many games, the activity has become very popular among both genders and young and old alike. During a June 2021 survey in the United States, 89 percent of respondents stated that they had made friends through playing video games.

Discovering Hidden Trends in Global Video Games Sales

Platforms, Genres, and Profitable Regions

By Andy Bramwell [source]

About this dataset

This dataset contains sales data for video games from all around the world, across different platforms, genres and regions. From the thought-provoking latest release of RPGs to the thrilling adventures of racing games, this database provides an insight into what constitutes as a hit game in today’s gaming industry. Armed with this data and analysis, future developers can better understand what types of gameplay and mechanics resonate more with players to create a new gaming experience. Through its comprehensive analysis on various game titles, genres and platforms this dataset displays detailed insights into how video games can achieve global success as well as providing a wonderful window into the ever-changing trends of gaming culture

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How to use the dataset

This dataset can be used to uncover hidden trends in Global Video Games Sales. To make the most of this data, it is important to understand the different columns and their respective values.

The 'Rank' column identifies each game's ranking according to its global sales (highest to lowest). This can help you identify which games are most popular globally. The 'Game Title' column contains the name of each video game, which allows you to easily discern one entry from another. The 'Platform' column lists the type of platform on which each game was released, e.g., PlayStation 4 or Xbox One, so that you can make comparisons between platforms as well as specific games for each platform. The 'Year' column provides an additional way of making year-on-year comparisons and tracking changes over time in global video game sales.
In addition, this dataset also contains metadata such as genre ('Genre'), publisher ('Publisher'), and review score ('Review') that add context when considering a particular title's performance in terms of global sales rankings. For example, it might be more compelling to compare two similar genres than two disparate ones when analyzing how successful a select set of titles have been at generating revenue in comparison with others released globally within that timeline. Lastly but no less important are the three variables dedicated exclusively for geographic breakdowns: North America ('North America'), Europe (Europe), Japan (Japan), Rest of World (Rest of World), and Global (Global). This allows us to see how certain regions contribute individually or collectively towards a given title's overall sales figures; by comparing these metrics regionally or collectively an interesting picture arises -- from which inferences about consumer preferences and supplier priorities emerge!

Overall this powerful dataset allows researchers and marketers alike a deep dive into market performance for those persistent questions about demand patterns across demographics around the world!

Research Ideas

• Analyzing the effects of genre and platform on a game's success - By comparing different genres and platforms, one can get a better understanding of what type of games have the highest sales in different regions across the globe. This could help developers decide which type of gaming content to create in order to maximize their profits.
• Tracking changes in global video games trends over time - This dataset could be used to analyze how various elements such as genre or platform affect success over various years, allowing developers an inside look into what kind of videos are being favored at any given moment across the world.
• Identifying highly successful games and their key elements- Developers could look at this data to find any common factors such as publisher or platform shared by successful titles to uncover characteristics that lead to a high rate-of-return when creating video games or other forms media entertainment

Acknowledgements

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

License

See the dataset description for more information.

Columns

File: Video Games Sales.csv | Column name | Description | |:------------------|:------------------------------------------------------------| | Rank | The ranking of the game in terms of global sales. (Integer) | | Game Title | The title of the game. (String) | | Platform | The platform the game was released on. (String) ...

In 2024, total U.S. consumer spending on video game content amounted to **** billion U.S. dollars, a significant increase from ***** billion U.S. dollars in the preceding year. Video game spending surged in 2021 due to the COVID-19 pandemic.

**To see detailed metadata see the PDF file on the right **

This dataset contains data on 64 videogames releases between 2012 and 2022. The games have been selected for being best-selling or top-rating games of their year. There are at least 5 games per year and information on the most relevant characters in the storyline.

The relationship between tables is as follows

Games.Game_ID = Characters.Game Characters.Id = Sexualization.Id

Version Update 10/11/22: - A misspelling on the games dataset column Release has been corrected - The abbreviations used to define the relevance of a character in Characters/Relevance have changed for clarity purposes · MC is now PA for protagonist · DA and SK stay the same · CR is now MC for main character · OR is now SC for secondary character · MV is now MA for main antagonist - A PDF file with detailed metadata has been added

Video gaming is no longer a hobby exclusively enjoyed by the young. As generations have grown up with video games a normal part of life, the age of the average gamer also increases. During a 2023 survey, 25 percent of video game players still come from the 27 to 42 years age demographic, and 19 percent are 59 years and older. Time spent gaming In 2023, Americans aged between 15 to 19 years spent 98.4 minutes on gaming or leisurely computer use during an average day. The age demographic which devoted the least amount of time to gaming was the 55 to 64 years category. Members of this age demographic spent an average of just 17.4 minutes playing on the computer during an average day.

The Amazon and Google video game datasets contain metadata and user interaction data for video games on each respective platform. They provide essential features like game title, genre, platform, release date,images links and user reviews. These datasets are used in experiments to reproduce results from prior research on video game recommendation systems, enabling the evaluation and comparison of recommendation accuracy across platforms. By analyzing features unique to each dataset, this approach aids in validating the robustness of recommendation models and optimizing their accuracy for personalized game recommendations

Includes 24 hour recall data that children were instructed to fill-out describing the previous day’s activities at baseline, weeks 2 and 4 of the intervention, after the intervention (6 weeks), and after washout (10 weeks). Includes accelerometer data using an ActiGraph to assess usual physical and sedentary activity at baseline, 6 weeks, and 10 weeks. Includes demographic data such as weight, height, gender, race, ethnicity, and birth year. Includes relative reinforcing value data showing how children rated how much they would want to perform both physical and sedentary activities on a scale of 1-10 at baseline, week 6, and week 10. Includes questionnaire data regarding exercise self-efficacy using the Children’s Self-Perceptions of Adequacy in and Predilection of Physical Activity Scale (CSAPPA), motivation for physical activity using the Behavioral Regulations in Exercise Questionnaire, 2nd edition (BREQ-2), motivation for active video games using modified questions from the BREQ-2 so that the question refers to motivation towards active video games rather than physical activity, motivation for sedentary video games using modified questions from the BREQ-2 so that the question refers to motivation towards sedentary video games behavior rather than physical activity, and physical activity-related parenting behaviors using The Activity Support Scale for Multiple Groups (ACTS-MG). Resources in this dataset:Resource Title: 24 Hour Recall Data. File Name: 24 hour recalldata.xlsxResource Description: Children were instructed to fill out questions describing the previous day's activities at baseline, week 2, and week 4 of the intervention, after the intervention (6 weeks), and after washout (10 weeks).Resource Title: Actigraph activity data. File Name: actigraph activity data.xlsxResource Description: Accelerometer data using an ActiGraph to assess usual physical and sedentary activity at baseline, 6 weeks, and 10 weeks.Resource Title: Liking Data. File Name: liking data.xlsxResource Description: Relative reinforcing value data showing how children rated how much they would want to perform both physical and sedentary activities on a scale of 1-10 at baseline, week 6, and week 10.Resource Title: Demographics. File Name: Demographics (Birthdate-Year).xlsxResource Description: Includes demographic data such as weight, height, gender, race, ethnicity, and year of birth.Resource Title: Questionnaires. File Name: questionnaires.xlsxResource Description: Questionnaire data regarding exercise self-efficacy using the Children's Self-Perceptions of Adequacy in and Predilection of Physical Activity Scale (CSAPPA), motivation for physical activity using the Behavioral Regulations in Exercise Questionnaire, 2nd edition (BREQ-2), motivation for active video games using modified questions from the BREQ-2 so that the question refers to motivation towards active video games rather than physical activity, motivation for sedentary video games using modified questions from the BREQ-2 so that the question refers to motivation towards sedentary video games behavior rather than physical activity, and physical activity-related parenting behaviors using The Activity Support Scale for Multiple Groups (ACTS-MG).

Violent Video Games and their relationship with Aggressive Behaviour 🎮

This data was collected from students to find out, how much time they spend playing video games, especially violent video games, and whether this affects their behavior.

The dataset is already depersonalized, which means sensitive information, (PII) is taken out to protect privacy.

The columns which are our concern are "How much time do you play "violent" video games specifically?" which we will set as the independent variable and the other 29 Questions (columns 11 till 40, 0 being the first column 'Timestamp').

These are 29 questions from the Buss-Perry Aggression Scale, set on the Likert Scale. They can be coded as:

'Strongly disagree': 1, 'Disagree': 2, 'Neither agree nor disagree': 3, 'Agree': 4, 'Strongly agree': 5

By default the dataset does not have these codes, rather we have to replace them. Then we will add all these columns to check the overall aggression level.

Minimum total can possibly be 1 x 29 = 29 (least aggressive) Maximum total can possibly be 5 x 29 = 145 (most aggressive)

After coding, we will make a column of the sum of the total codes. We will call this column 'BPAQ (Buss-Perry Aggression Questionnaire) Score', and consider it as the dependent variable.

We are trying to establish a relationship between The Time of Violent Video Gameplay and the Level of Aggression, for which the indicators are discussed above, and see if it is significant.

but we have to see whether ANOVA suits it or Linear Regression, You can visit the code section and follow my notebook, or find your own insights.

Video gaming is a popular way for gamers to connect with friends and family. A February 2025 survey found that 72 percent of gamers in the United States played with others online or in person, up from 65 percent of U.S. gamers who did so in 2020. According to U.S. gamers, friends are the most popular group of people to play online with.

According to a survey conducted in March 2024, 76 percent of adults in the United States played video games on at least one platform. In comparison, 24 percent of U.S. adults did not play video games at all.

Comprehensive YouTube channel statistics for Video Games Evolution, featuring 298,000 subscribers and 88,723,488 total views. This dataset includes detailed performance metrics such as subscriber growth, video views, engagement rates, and estimated revenue. The channel operates in the Gaming category and is based in US. Track 379 videos with daily and monthly performance data, including view counts, subscriber changes, and earnings estimates. Analyze growth trends, engagement patterns, and compare performance against similar channels in the same category.

Global Video Game Sales and Reviews

Global Video Game Performance: Sales, Reviews, and Rankings

By Andy Bramwell [source]

About this dataset

The elements covered in this well-curated dataset include: The ranking of the game based on global sales under the column 'Rank'. This metric provides perspective on how popular or successful a particular game has been across countries in comparison to others during its time. Noting that video games' popularity could vary greatly from one geography to another due to factors like cultural nuances, gamer preferences, etc., regional sales have been marked separately for North America (North America), Europe (Europe), Japan (Japan) as well as for other parts of the World excluding these three regions under the column 'Rest of World'.

For easy identification among massive chunks of data, we've included each game's title (Game Title) along with additional categorization based on their genre (Genre). From action-packed adventures to strategic board-like scenarios or enchanted magic realms - classifications cover it all! In addition, detailed information about publishers can be found under 'Publisher', which grants insights about leading companies dominating market shares.

Further details expand into mentioning platforms such as PS4, Xbox, PC where these games can be played under 'Platform'. A unique attribute covered in this database is ‘Review’. Given that critique ratings play an influential role in engaging new players into trying out a particular video game or boosting existing user morale regarding their choice; this numeric representation ranging typically from 1-10 vividly captures public opinion about them.

Lastly, just for keeping tabs on ever-evolving gaming technology standards where newer versions often outshine predecessors irrespective of actual gameplay quality itself; having release years mentioned ('Year') proves beneficial for categorizing them chronologically. This helps correlate whether higher sales figures can sometimes merely be indicative of more people having access to necessary high-end gaming hardware during later periods.

In essence, this dataset titled ‘Video Games Sales.csv’ holds immense potential for informative deep-dives into the Video Game industry's trends and paradigms, forming a solid foundation for market research, academic purposes or personal projects

How to use the dataset

This dataset provides extensive information about various video game titles, their sales performance across multiple regions, publisher details and game reviews. Follow the steps outlined below to make the most out of this remarkable dataset!

1. Game Research & Evaluation:

With columns such as 'Game Title', 'Genre' and 'Review', you can research on particular games or genres that interest you. You can evaluate a game based on its review scores, delving into what makes a top-rated game.

2. Publisher Analysis:

The 'Publisher' column lets you track which publishers are behind the most successful games in terms of sales and reviews. This analysis could be useful for people interested in business trends in gaming industry or trying to identify potential innovative publishers.

3. Regional Market Trend Identification:

You can use data from columns like ‘North America’, ‘Europe’, ‘Japan’ and ‘Rest of World’ to study regional market trends for certain genres or platforms; it might enable one to recognize patterns over time or cultural preferences with regard to video games.

4. Global Sales Analysis:

Using the 'Global' column, you could observe which games have been globally successful, going beyond regional preferences by genre or platform.

5. Platform Insight:

The platform on which a particular game is available is another significant factor (e.g., PC, PS4, Xbox). By utilizing the data contained in this dataset regarding platforms, one may learn how platform choice impacts global sales as well as discern any correlation between preferred platform types among specific regions.

Remember that every statistical analysis begins with knowing your data - dive deep into each variable; explore patterns within variables before looking at correlations between different fields.

Don't forget - when engaged with comprehensive datasets like these - creativity is your only limit! Happy analyzing!

Research Ideas

• Trend Analysis: This dataset can be used to analyze the trends in video game preferences over the years based on genre, publisher, platform and region. It can provide interesting insights into how consumer tastes have evolved with time and which game genres are becoming more popular.
• Sales Forecasting: U...

Level up your understanding of the video game market with this comprehensive dataset of 1.7GB Amazon reviews. Housed in a readily accessible JSON format, this collection grants you exclusive access to the unfiltered voices of millions of gamers. Analyze preferences, identify emerging genres, and gain a competitive edge in a dynamic industry.

Forget simplistic star ratings! This 1.7GB dataset of Amazon video game reviews, presented in a convenient JSON format, unlocks a treasure trove of qualitative player feedback. Extract the essence of gamer opinions, understand motivations and concerns, and gain a comprehensive picture of what truly matters to the gaming community.

This colossal dataset, bursting with 1.7GB of Amazon video game reviews in JSON format, grants you exclusive access to the unfiltered voices of millions of gamers. Packed with star ratings, verified purchase flags, timestamps, unique IDs, and most importantly, the full gamut of review text and concise summaries, it unlocks a goldmine of possibilities for researchers, developers, and gaming enthusiasts alike.

Applications for this dataset:

Unleash the Power of Sentiment Analysis:

Dive deep into the hearts and minds of gamers. Analyze the emotional undercurrents of their words, identify key trends in satisfaction and frustration, and predict future preferences. This dataset is your passport to understanding what truly resonates with the gaming community.

Beyond Sentiment:

This treasure trove extends far beyond sentiment analysis. Train topic models to uncover hidden trends and emerging genres. Predict future review ratings with NLP techniques. Craft personalized game recommendations based on player feedback. The possibilities are endless!

Level Up Your Gaming Insights:

Whether you're a researcher unlocking the secrets of player psychology, a developer crafting the next immersive masterpiece, or a passionate gamer seeking a deeper understanding of your peers, this dataset is your key to unlocking valuable insights. With 1.7GB of rich player data at your fingertips, prepare to take your understanding of the video game landscape to the next level.

File Information: - Format: JSON - Size: 1.7GB - Content: Amazon video game reviews - Source: Amazon - Date created: December 17, 2023

Data Format: JSON

Features:

• overall: Integer rating of the game
• verified: Boolean flag indicating whether the review is from a verified purchaser
• reviewTime: String representation of the review date (format might need further investigation)
• reviewerID: Unique identifier for the reviewer
• asin: Amazon Standard Identification Number for the game
• reviewerName: Name of the reviewer
• reviewText: The actual text of the review
• summary: One-line summary of the review
• unixReviewTime: Unix timestamp of the review date (potentially derived from reviewTime)

Additional Notes: - You might need to parse the reviewTime string to extract the date in a consistent format for further analysis. - Consider providing details about the target variable you want to use for modeling (e.g., predicting rating based on review text). - Knowing the number of reviews will be helpful for understanding the dataset size.

Video gaming is no longer just a hobby of teenagers - thanks to developments in gaming technology and the accessibility of many games, the activity has become very popular among both genders and young and old alike. Despite its popularity, the anonymous nature of online gaming leaves some gamers open to harassment and negative experiences. During an August 2023 survey in the United States, 67 percent of respondents stated that they had been called offensive names while playing video games. Overall, 76 percent of responding gamers had encountered online harassment, down from 83 percent two years prior.

Introduction

Gaming Monetization Statistics: The gaming sector has undergone considerable transformation, moving away from its conventional model of selling games as independent units.

Instead, it has embraced a diverse ecosystem where various strategies are utilized to produce revenue. Gaming monetization pertains to the practices and tactics employed by game developers and publishers to derive earnings from their creations.

This multifaceted methodology holds immense importance in maintaining the industry's expansion, facilitating game development, and furnishing players with captivating interactions. The dynamic gaming monetization landscape is characterized by its ability to adapt to changing market dynamics, emerging player preferences, and technological advancements.

This adaptability will remain essential in sustaining the industry's growth while ensuring that players continue to receive captivating gaming experiences.

This dataset offers a curated historical overview of first-person shooter (FPS) video games, capturing key details such as game titles, developers, supported platforms, and release dates. It is designed to support data exploration, trend analysis, and game industry research.

The collection spans several decades of FPS game development, showcasing both iconic titles and lesser-known releases. Whether you're a data scientist analyzing genre trends, a developer studying platform distribution, or a gaming enthusiast curious about FPS evolution, this dataset provides a solid foundation.

Column Descriptions:

Title – The name of the FPS video game, including both well-known and obscure entries across various gaming eras.

Developer – The studio(s) or individual(s) responsible for creating the game. Some entries list multiple developers for collaborative or cross-platform projects.

Platform – The gaming systems the game was released on, such as PS2, Xbox, GCN, WIN (Windows), GBA, and more. Multiple platforms are comma-separated.

Release_Date – The game's initial release date, shown in YYYY-MM-DD format. This generally reflects the earliest official release across any platform or region.