Sea of Thieves player activity dataset from MMO Populations, combining monthly enhanced players and 30-day daily estimates generated from public signals.

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...

Video Games Sales Dataset

About Dataset

This Dataset provides up-to-date information on the sales performance and popularity of various video games worldwide. The data includes the name, platform, year of release, genre, publisher, and sales in North America, Europe, Japan, and other regions. It also features scores and ratings from both critics and users, including average critic score, number of critics reviewed, average user score, number of users reviewed, developer, and rating. This comprehensive and essential dataset offers valuable insights into the global video game market and is a must-have tool for gamers, industry professionals, and market researchers. by source

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Columns

Column Name	Description
Name	The name of the video game.
Platform	The platform on which the game was released, such as PlayStation, Xbox, Nintendo, etc.
Year of Release	The year in which the game was released.
Genre	The genre of the video game, such as action, adventure, sports, etc.
Publisher	The company responsible for publishing the game.
NA Sales	The sales of the game in North America.
EU Sales	The sales of the game in Europe.
JP Sales	The sales of the game in Japan.
Other Sales	The sales of the game in other regions.
Global Sales	The total sales of the game across the world.
Critic Score	The average score given to the game by professional critics.
Critic Count	The number of critics who reviewed the game.
User Score	The average score given to the game by users.
User Count	The number of users who reviewed the game.
Developer	The company responsible for developing the game.
Rating	The rating assigned to the game by organizations such as the ESRB or PEGI.

Research Ideas / Data Use

• Market Analysis: The video game sales data can be used to analyze market trends and identify popular genres, platforms, and publishers. This can be useful for industry professionals to make informed decisions about game development and marketing strategies.
• Sales Forecasting: The sales data can be used to forecast future trends and predict the success of upcoming games.
• Consumer Insights: The data can be analyzed to gain insights into consumer preferences and buying habits, which can be used to tailor marketing strategies and improve customer satisfaction.
• Comparison of Competitors: The data can be used to compare the sales performance of competing video games and identify market leaders.
• Gaming Industry Performance: The data can be used to evaluate the overall performance of the gaming industry and track its growth over time.
• Gaming Popularity by Region: The data can be analyzed to determine which regions are the largest markets for video games and which genres are most popular in each region.
• Impact of Reviews: The data can be used to study the impact of critic and user reviews on sales and the relationship between scores and sales performance.
• Gaming Trends over Time: The data can be used to identify trends in the gaming industry over time and to track the evolution of the market.
• Gaming Demographics: The data can be used to analyze the demographic makeup of the gaming audience, including age, gender, and income.
• Impact of Gaming Industry on the Economy: The data can be used to evaluate the impact of the gaming industry on the economy and to assess its contribution to job creation and economic growth.

Acknowledgements

if this dataset was used in your work or studies, please credit the original source Please Credit ↑ ⠀⠀⠀

Wizard101 player activity dataset from MMO Populations, combining monthly enhanced players and 30-day daily estimates generated from public signals.

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) ...

Destiny 2 player activity dataset from MMO Populations, combining monthly enhanced players and 30-day daily estimates generated from public signals.

Elite Dangerous player activity dataset from MMO Populations, combining monthly enhanced players and 30-day daily estimates generated from public signals.

(1) Introduction

In this work, we want to collect network telemetry data related to Cloud Gaming applications. The objective is that the data collected can be analyzed, compared and useful to create solutions to improve the QoE of this type of service.

(2) Content

This dataset currently contain network telemetry data related to 3 different games played with the Xbox Cloud Gaming service. The games are: - Fortnite (Zero Build game mode) - Forza Horizon 5 - Mortal Kombat 11 (Offline mode)

For each game, many experiments of 15 minutes of gameplay were done, with 1 or 2 players connected. It was collected Packet Captures (PCAP).

Dataset is divided by type of connection (5G and wired), by games, and by number of players (1 or 2).

(3) Methodology

Games were played using laptops with Chrome browser. To collect the data, it was used a Raspberry Pi with P4Pi platform installed on it. P4Pi system is a Linux like, and can run tshark, so we used it to collect PCAPs in every experiment. Experiments were made using two different connections: 5G and wired. Data was collected on Centro Universitário Facens (for 5G connection) and Federal University of São Carlos - Sorocaba campus (for wired connection). In the following figure is represented our setup.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F18694461%2Fcc611fa6106a88e1640042b279ed5e04%2FUntitled%20presentation.png?generation=1711490000766201&alt=media" alt="">

(4) Data catalog

Experiement	Game	Connection	Number of Players
Ex35	Fortnite	5G	1 Player
Ex39	Fortnite	5G	2 Players
Ex37	Forza Horizon 5	5G	1 Player
Ex40	Forza Horizon 5	5G	2 Players
Ex38	Mortal Kombat 11	5G	1 Player
Ex7	Fortnite	Wired	1 Player
Ex19	Fortnite	Wired	1 Player
Ex20	Fortnite	Wired	1 Player
Ex21	Fortnite	Wired	2 Players
Ex22	Fortnite	Wired	2 Players
Ex23	Fortnite	Wired	2 Players
Ex8	Forza Horizon 5	Wired	1 Player
Ex10	Forza Horizon 5	Wired	1 Player
Ex11	Forza Horizon 5	Wired	1 Player
Ex29	Forza Horizon 5	Wired	1 Player
Ex15	Forza Horizon 5	Wired	2 Players
Ex16	Forza Horizon 5	Wired	2 Players
Ex17	Forza Horizon 5	Wired	2 Players
Ex12	Mortal Kombat 11	Wired	1 Player
Ex13	Mortal Kombat 11	Wired	1 Player
Ex14	Mortal Kombat 11	Wired	1 Player
Ex24	Mortal Kombat 11	Wired	1 Player
Ex25	Mortal Kombat 11	Wired	1 Player
Ex30	Mortal Kombat 11	Wired	1 Player
Ex32	Mortal Kombat 11	Wired	2 Players
Ex33	Mortal Kombat 11	Wired	2 Players
Ex34	Mortal Kombat 11	Wired	2 Players

Conan Exiles player activity dataset from MMO Populations, combining monthly enhanced players and 30-day daily estimates generated from public signals.

FIFA 23 is a football simulation video game published by Electronic Arts. It is the 30th and final installment in the FIFA series that is developed by EA Sports, and released worldwide on 30 September 2022 for PC, Nintendo Switch, PlayStation 4, PlayStation 5, Xbox One, Xbox Series X/S and Google Stadia.

The role of performance analysis within football is more important than ever. Whether it’s the opposition, potential transfer targets or last weekend’s fixture, analysing performances and data can be the difference between success and failure.

Trove player activity dataset from MMO Populations, combining monthly enhanced players and 30-day daily estimates generated from public signals.

Overwatch is a team-based multiplayer first-person shooter video game developed and published by Blizzard Entertainment, which released on May 24, 2016 for PlayStation 4, Xbox One, and Windows. Described as a "hero shooter", Overwatch assigns players into two teams of six, with each player selecting from a roster of nearly 30 characters, known as "heroes", each with a unique style of play whose roles are divided into three general categories that fit their role: Offense, Defense, Tank, and Support. Players on a team work together to secure and defend control points on a map or escort a payload across the map in a limited amount of time.

I discovered this dataset on the Overwatch Subreddit here: https://www.reddit.com/r/Overwatch/comments/7o8hmg/my_friend_has_recorded_every_game_hes_played/

and there is sort of same dataset here: https://www.kaggle.com/mylesoneill/overwatch-game-records/home

Data was messy, so I try to clean it and make better and easier for visualising and analysing.

Columns as: time, result, map, team_role, character_1, character_2, character_3 and psychological_condition were transformed (clustered) into easy to use format.

Thanks to JustWingIt for collecting this amazing data!

And Myles O'Neill for bringing this data to Kaggle!

Overwatch is a team-based multiplayer online first-person shooter video game developed and published by Blizzard Entertainment. It was released in May 2016 for Windows, PlayStation 4, and Xbox One. Overwatch assigns players into two teams of six, with each player selecting from a roster of over 20 characters, known in-game as "heroes", each with a unique style of play, whose roles are divided into four general categories: Offense, Defense, Tank, and Support. Players on a team work together to secure and defend control points on a map or escort a payload across the map in a limited amount of time.

I discovered this dataset on the Overwatch Subreddit here: https://www.reddit.com/r/Overwatch/comments/7o8hmg/my_friend_has_recorded_every_game_hes_played/

It represents a ridiculous amount of effort in terms of manually recording game results. This data, whilst in some places incomplete, gives an unprecedented view into the experience of a single overwatch player over the course of years of gameplay. From it you can track the ups and downs, shifts in hero preference and all sorts of other exciting in game trends.

Thanks to JustWingIt for their amazing collecting this data.

I cleaned the data a little and put it into a single CSV.

DC Universe Online player activity dataset from MMO Populations, combining monthly enhanced players and 30-day daily estimates generated from public signals.

Star Trek Online player activity dataset from MMO Populations, combining monthly enhanced players and 30-day daily estimates generated from public signals.

War Thunder

War Thunder is a comprehensive, free-to-play multiplayer vehicular combat game developed by Gaijin Entertainment. Released in 2012, the game spans multiple platforms including PC, PlayStation, and Xbox. War Thunder offers players a rich and immersive experience by allowing them to engage in realistic, historically accurate battles using a wide array of vehicles from World War II and the Cold War era. The game features aircraft, ground vehicles, and naval units, providing a diverse and extensive selection for players to master. With detailed vehicle models, accurate physics, and extensive maps, War Thunder delivers a highly engaging and dynamic combat experience.

Overview

The War Thunder vehicle stats dataset on Kaggle is a comprehensive collection of information about the various vehicles available in the game. This dataset includes detailed statistics and attributes for a variety of vehicles, such as tanks, aircraft, and naval units.

The unofficial War Thunder API was used for generating this dataset.

Please check the authors work on his github.

Data

• general_vehicles: Summaries general statistics about the vehicles
• specific_vehicles: Holds detailed stats about a vehicle

Acknowlegement

Foto von Kevin Schmid auf Unsplash

New World player activity dataset from MMO Populations, combining monthly enhanced players and 30-day daily estimates generated from public signals.

History’s greatest warriors brawl to prove who’s the best in an epic test of strength and skill. These slugfests are salted with powerful weapons and gadgets. Every weapon you pick up changes your style of play

Brawlhalla is a free 2D platform fighting game that supports up to 8 local or online players with full cross-play for PC, Xbox One, Xbox Series X, PS5, PS4, iOS, and Android.

About FIFA 22

FIFA 22 will be a football simulation video game published by Electronic Arts as part of the FIFA series. It will be the 29th installment in the FIFA series, and will be released 1 October 2021 for Microsoft Windows, Nintendo Switch, PlayStation 4 and Xbox One consoles. Enhanced versions for the PlayStation 5, Xbox Series X/S and Google Stadia were released later.

A beta version was released in August 13, 2021 in the United States, Canada and South Korea, August 14 in Brazil and Portugal, August 15 in Turkey and August 16 in the rest of the world, for the PS4, PS5 and Windows. The Nintendo Switch version is releasing on August 19 in the US and Canada and on August 20 in the West.

About this dataset

This dataset is scraped on www.fifplay.com website using R programming language. According to their announcement on the website, these ratings are updated right after officially announced by Electronic Arts. This dataset contains 307 pages of fifplay.com website where dataset has built on. Due to this dataset is not final release and official, please follow official announcements published from Electronic Arts.

All rights reserved by Electronic Arts Games. - Electronic Arts Official Website for FIFA 22

This dataset is gathered from Metacritic.com using a web scraper. It includes 18 csv files for six gaming platforms (PC, Xbox One, Xbox Series X, PlayStation 4, PlayStation 5, and Nintendo Switch) each platform having three csv files for Details, Scores, and Reviews.

• 01_[platform]_details.csv columns:

Name: Name of the game

Link: The link of the game on Metacritic.com

Distributer: The distributer of the game

Developer: The developer of the game

Release Date: When the game released.

Also On: If available on other platform.

Summary: A description of the game.

Metascore: The overall score from critics.

Meta Status: The status of the Metascore.

# of Critic Reviews: Number of critics who gave the game a score.

Critic Positive: Number of positive critic reviews.

Critic Mixed: Number of mixed critic reviews.

Critic Negative: Number of negative critic reviews.

Userscore: The overall score from users.

Userscore Status: The status of the Userscore.

# of User Reviews: Number of users who gave the game a score.

User Positive: Number of positive user reviews.

User Mixed: Number of mixed user reviews.

User Negative: Number of negative user reviews.

Genres: The genre(s) of the game.

# Of Players: Maximum number of players.

Rating: The age restrictions.

Awards: The awards concerning the rankings of the game on metacritic.com

• 02_[platform]_scores.csv: This file includes the scores from each critic.
• 03_[platform]_reviews.csv: This file includes the reviews (just the short ones on Metacritic.com) from each critic.