A survey conducted in the third quarter of 2024 found that over 92 percent of female internet users aged 16 to 24 years worldwide played video games on any kind of device. During the survey period, 93 percent of male respondents in the same age group stated that they played video games. Worldwide, over 83 percent of internet users were gamers.

Context: Valorant, developed by Riot Games, has quickly become one of the most popular tactical first-person shooter games since its release. The game emphasizes strategic team play, individual skills, and tactical execution, making it a fascinating subject for performance analysis. Understanding the various metrics that contribute to player success can offer insights into effective strategies and gameplay techniques. This dataset was created to help players, coaches, and analysts delve into the detailed aspects of player performance and identify key areas for improvement.

Sources: The data for this dataset was collected from various online sources, including:

In-Game Statistics: Aggregated from player profiles and match histories available within the game client. Third-Party Valorant Trackers: Websites and tools that track player statistics and match performance, such as Tracker.gg and Blitz.gg. Community Contributions: Insights and data shared by the Valorant community, including professional players, streamers, and analysts, who often provide detailed breakdowns of their gameplay. Inspiration: The inspiration for compiling this dataset stems from several key areas:

Performance Analysis: In competitive gaming, understanding the granular details of player performance is crucial for improvement. Metrics like win rate, damage per round, and headshot percentage provide actionable insights. Strategic Development: By analyzing this data, players and teams can develop better strategies, identify strengths and weaknesses, and tailor their training regimes accordingly. Predictive Modeling: The dataset serves as a foundation for building predictive models to forecast future performance, which can be useful for coaching, match preparation, and scouting new talent. Community Engagement: Providing this dataset to the wider Valorant community fosters engagement and encourages collaborative analysis. It allows enthusiasts to test hypotheses, share findings, and contribute to a deeper understanding of the game. Educational Purposes: For educators and students in data science, sports analytics, and game design, this dataset offers a real-world application of data analysis techniques and methodologies. Future Directions: The dataset can be expanded by including additional metrics such as agent pick rates, map-specific performance, and team composition analysis. Incorporating more granular data over longer periods can also enhance the depth of analysis and provide a more comprehensive view of player performance trends.

By sharing this dataset, we aim to empower the Valorant community with data-driven insights that can elevate gameplay, inform strategic decisions, and contribute to the overall growth of the esports ecosystem.

In July 2025, total video games sales in the United States amounted to **** billion U.S. dollars, representing a five percent year-over-year increase. Generally speaking, the video game industry has its most important months in November and December, as video game software and hardware make very popular Christmas gifts. In December 2024, total U.S. video game sales surpassed **** billion U.S. dollars. Birth of the video game industry Although the largest regional market in terms of sales, as well as number of gamers, is Asia Pacific, the United States is also an important player within the global video games industry. In fact, many consider the United States as the birthplace of gaming as we know it today, fueled by the arcade game fever in the ’60s and the introduction of the first personal computers and home gaming consoles in the ‘70s. Furthermore, the children of those eras are the game developers and game players of today, the ones who have driven the movement for better software solutions, better graphics, better sound and more advanced interaction not only for video games, but also for computers and communication technologies of today. An ever-changing market However, the video game industry in the United States is not only growing, it is also changing in many ways. Due to increased internet accessibility and development of technologies, more and more players are switching from single-player console or PC video games towards multiplayer games, as well as social networking games and last, but not least, mobile games, which are gaining tremendous popularity around the world. This can be evidenced in the fact that mobile games accounted for ** percent of the revenue of the games market worldwide, ahead of both console games and downloaded or boxed PC games.

Definition: The percentage of students who play video/computer games and use the internet for a specified number of hours per day on an average school day

Data Source: Student Health Survey, Office of Student Support Services, New Jersey Department of Education

History: MAR 2017 - Chart and table titles corrected to read as "More Than 3 Hours Per Day." They were erroneously labeled previously as "2 or Less Hours Per Day." - All 2010-2014 data were updated for total population and all racial/ethnic groups - 2020 targets modified to reflect a 10% improvement over the 2010 baseline for total population and all racial/ethnic groups

A global consumer survey conducted in March 2024 found that 18 percent of respondents were more likely to buy a video game if it was advertised as a collector or limited edition. However, 45 percent of respondents stated that they were not interested in limited edition releases.

League of Legends Professional Game season 12 statistics from Gol.gg. The website data would have semi-colon [;] breaks so I recommend using some find-and-replace tool to replace everything with commas [,].

There aren't any percentages so if you would like to convert picks and bans into percentages you would need to calculate the total games from: (Picks + Bans)/Presence Then you can divide the picks and bans by the total games to get the values in percentages for easier analysis.

Percentage of Canadians' time spent online and using video streaming services and video gaming services, in a typical week.

Hi, Kagglers!🔥

This dataset captures the ****Top 20 best-selling games**** on Steam for the week of March 11, 2025, to March 18, 2025, directly extracted via Steam's internal API using SteamKit2. Each entry includes the game's rank, app ID, title, release date, total user review counts, and the overall user recommendation rating.

🍥**rank**: Weekly rank based on Steam sales 🍥**app_id**: Unique identifier of the game on Steam 🍥**title**: Official title of the game 🍥**release_date**: Date the game was released on Steam 🍥**user_review_percentage**: Percentage of positive user reviews 🍥**user_recommendation**: Steam user sentiment rating along with positive review percentage 🍥**all_time_peak**: The highest number of concurrent players 🍥**price**: The current price of the game

Have a great day, everyone!🔥

Note: Feel free to explore, analyze, and use this dataset. Check back weekly for updates and keep track of the gaming market's latest movements!

(While exploring our dataset, you'll notice that there are missing values in the some columns. This is because Assassin’s Creed Shadows has not been released yet.)

Here are a few use cases for this project:

1. Sports Analysis: The "Shot Tracking" model could be used by basketball teams or analysts to track a player's made-basket percentage during actual games or during practice sessions. Data can be utilized to enhance player's shooting skills, determining their most efficient areas on the court, and tracking progress over time.

2. Game Highlights: Media companies or sports broadcasters could use the model to automatically generate game highlights, focusing on successful shots. This could streamline the video editing process and make it easier to deliver exciting content to audiences quickly.

3. Virtual Coaching: In a virtual training scenario, this model can be used to provide real-time feedback to players practicing their shots. This could help players understand their strong and weak shooting zones and improve accordingly.

4. Betting & Fantasy Leagues: The model could be utilized by sports betting companies and those involved in running basketball fantasy leagues to have access to real-time data on player shooting successes. It can also help users make informed decisions.

5. Sports Equipment Manufacturing: This model can be used in the development of interactive sports equipment (e.g., smart hoops that track shooting accuracy), helping users practice and improve their shooting skills.

European Recorded Media, Films and Video Games Exports Share by Country (Thousand Euros), 2023 Discover more data with ReportLinker!

I have created this dataset for people interested in League of Legends who want to approach the game from a more analytical side.

Most of the data was acquired from Games of Legends (https://gol.gg/tournament/tournament-stats/LEC%20Winter%202025/) and also from official account of the League of Legends EMEA Championship (https://www.youtube.com/c/LEC)

Dataset Contents:

• Player: Name of the player.
• Role: Role of the player (e.g., TOP, JUNGLE, MID, ADC, SUPPORT)
• Team: Name of the player's team
• Opponent_Team: Name of the opposing team
• Opponent_Player: Name of the opposing player
• Date: Date of the match
• Round: Round of the tournament
• Day: Specific day of the tournament
• Patch: Version of the game patch during the match
• Stage: Stage of the tournament
• No_Game: Game number in the series
• all_Games: Total number of games in the series
• Format: Format of the match (e.g., Best of 1, Best of 3)
• Game_of_day: Number of the game that day
• Side: Side of the map the team started on (Blue/Red)
• Time: Duration of the match

Team Performance Metrics:

• Kills_Team: Total kills by the team
• Turrets_Team: Total turrets destroyed by the team
• Dragon_Team: Total dragons killed by the team
• Baron_Team: Total barons killed by the team

Player Performance Metrics:

• Level: Final level of the player
• Kills: Number of kills by the player
• Deaths: Number of deaths of the player
• Assists: Number of assists by the player
• KDA: Kill/Death/Assist ratio
• CS: Creep Score (minions killed)
• CS in Team's Jungle: Creep Score in the team's jungle
• CS_in_Enemy_Jungle: Creep Score in the enemy's jungle
• CSM: Creep Score per Minute
• Golds: Total gold earned
• GPM: Gold Per Minute
• GOLD%: Percentage of team's total gold earned by the player

Vision and Warding:

• Vision_Score: Total vision score
• Wards_placed: Number of wards placed
• Wards_destroyed: Number of wards destroyed
• Control_Wards_Purchased: Number of control wards purchased
• Detector_Wards_Placed: Number of detector wards placed
• VSPM: Vision Score Per Minute
• WPM: Wards Placed per Minute
• VWPM: Vision Wards Placed per Minute
• WCPM: Wards Cleared per Minute
• VS%: Vision Score percentage

Damage Metrics:

• Total_damage_to_Champion: Total damage dealt to champions
• Physical_Damage: Total physical damage dealt
• Magic_Damage: Total magic damage dealt
• True_Damage: Total true damage dealt
• DPM: Damage Per Minute
• DMG%: Percentage of team’s total damage dealt by the player

Combat Metrics

• K+A_Per_Minute: Kills and Assists per Minute
• KP%: Kill Participation percentage
• Solo_kills: Number of solo kills
• Double_kills: Number of double kills
• Triple_kills: Number of triple kills
• Quadra_kills: Number of quadra kills
• Penta_kills: Number of pentakills

Early Game Metrics

• GD@15: Gold Difference at 15 minutes
• CSD@15: Creep Score Difference at 15 minutes
• XPD@15: Experience Difference at 15 minutes
• LVLD@15: Level Difference at 15 minutes

Objective Control:

• Objectives_Stolen: Number of objectives stolen
• Damage_dealt_to_turrets: Total damage dealt to turrets
• Damage_dealt_to_buildings: Total damage dealt to buildings

Healing and Mitigation:

• Total_heal: Total healing done
• Total_Heals_On_Teammates: Total healing done on teammates
• Damage_self_mitigated: Total damage self-mitigated
• Total_Damage_Shielded_On_Teammates: Total damage shielded on teammates

Crowd Control Metrics:

• Time_ccing_others: Time spent crowd controlling others
• Total_Time_CC_Dealt: Total crowd control time dealt

Survival and Economy:

• Total_damage_taken: Total damage taken
• Total_Time_Spent_Dead: Total time spent dead
• Consumables_purchased: Number of consumables purchased
• Items_Purchased: Number of items purchased
• Shutdown_bounty_collected: Total shutdown bounty collected
• Shutdown_bounty_lost: Total shutdown bounty lost

In the first quarter of the fiscal year 2026, game publisher Electronic Arts (EA) generated over 1.08 billion U.S. dollars in net bookings via live services. Full game sales generated 214 million U.S. dollars in net bookings during the same period. Net bookings are defined as the net number of products and services sold digitally or sold-in physically in the period. Net bookings are calculated by adding total net revenue to the change in deferred net revenue for online-enabled games. Live services are EA’s revenue generator Gaming companies have pivoted to monetizing their titles beyond the initial purchase and are constantly working on keeping online players engaged via new characters, battle seasons and other in-game content. EA’s portfolio of live service games includes sports franchises EA Sports FC, and Madden NFL, as well as Battle Royale title Apex Legends, first-person shooter Battlefield V, and life simulation the Sims. All these titles are long-running series with new installments and downloadable content (DLC) being released regularly. On the flip side, the focus on live-service games means fewer big new releases, leading to a stagnation of the market in regard to new IPs (IP is short for intellectual property and a new IP refers to a new game which is not a spin-off or sequel of an existing game). Sports gamers are likely to spend money EA is constantly seeking to expand its EA Sports portfolio. In July 2025, EA released its first College Football video game after an eleven-year break since NCAA Football 14. This strategic decision is driven by several factors. First, sports gaming audiences are highly engaged and willing to spend money on additional gaming content. Second, any college football game will include rosters without names, images or likenesses or real college players to adhere to NCAA rules, which works in EA’s favor as the company as this keeps licensing costs low. And last, college football is a major pastime in EA’s biggest single market, the United States. All the pieces are lining up for EA to have another major moneymaker on their hands. This strategy paid off, as EA Sports College Football 25 became one of the top-selling video games in the United States in 2024.