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Board Game Statistics: ​Board games have experienced a notable resurgence, becoming a preferred pastime for diverse demographics. In the United States, 43% of board game enthusiasts engage in gameplay several times per week, while 25% play weekly. Demographically, 47% of board game players are aged between 18 and 34, with individuals aged 55 and above comprising 18% of the player base. Gender representation is balanced, with women accounting for 51% and men 49% of board game enthusiasts. Regarding game collections, 43% of gamers own more than 25 board and/or card games.
The average playing time for most board games ranges from one to two hours, though this can vary significantly depending on the game's complexity. These statistics underscore the enduring appeal and diverse engagement within the board gaming community.​
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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.
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.
A team's mean seasons statistics can be used as predictors for their performance in future games. However, these statistics gain additional meaning when placed in the context of their opponents' (and opponents' opponents') performance. This dataset provides this context for each team. Furthermore, predicting games based on post-season stats causes data leakage, which from experience can be significant in this context (15-20% loss in accuracy). Thus, this dataset provides each of these statistics prior to each game of the regular season, preventing any source of data leakage.
All data is derived from the March Madness competition data. Each original column was renamed to "A" and "B" instead of "W" and "L," and the mirrored to represent both orderings of opponents. Each team's mean stats are computed (both their stats, and the mean "allowed" or "forced" statistics by their opponents). To compute the mean opponents' stats, we analyze the games played by each opponent (excluding games played against the team in question), and compute the mean statistics for those games. We then compute the mean of these mean statistics, weighted by the number of times the team in question played each opponent. The opponents' opponent's stats are computed as a weighted average of the opponents' average. This results in statistics similar to those used to compute strength of schedule or RPI, just that they go beyond win percentages (See: https://en.wikipedia.org/wiki/Rating_percentage_index)
The per game statistics are computed by pretending we don't have any of the data on or after the day in question.
Currently, the data isn't computed particularly efficiently. Computing the per game averages for every day of the season is necessary to compute fully accurate opponents' opponents' average, but takes about 90 minutes to obtain. It is probably possible to parallelize this, and the per-game averages involve a lot of repeated computation (basically computing the final averages over and over again for each day). Speeding this up will make it more convenient to make changes to the dataset.
I would like to transform these statistics to be per-possession, add shooting percentages, pace, and number of games played (to give an idea of the amount uncertainty that exists in the per-game averages). Some of these can be approximated with the given data (but the results won't be exact), while others will need to be computed from scratch.
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The author is in the process of creating a blockbreaker-like game, in which the jumping-off point is the "Block Breaker" section of the Udemy course, Complete C# Unity Developer 2D: Learn to Code Making Games
After making lots of levels, the author needed to sort them by difficulty. How does one measure the difficulty of a level? A first-cut solution is to make an auto-play bot that is not perfect, and see how well the bot does on each level, using thousands of trials.
Here is a video of the game in auto-play action.
A global game developer survey in 2024 found that ** percent of respondents used AI tools in game development for **********************, up from ** percent of responding game devs in the previous year. ************************* saw the biggest increase in AI tool usage, while **************************** had the biggest drop in AI tool usage when compared to the previous year.
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As a massive League of Legends fan for 10+ years, I realized that there weren't any datasets that helped us stay updated with Worlds 2021, thus this dataset was born!
All data was acquired from lolesports.com which shows all in-depth statistics available for each match that others can use to find correlations between in-game statistics and wins.
I would love to see this data used to answer how vision (ward interactions) and gold distribution (how a team's gold is divided among it's positions) correlate with win percentage.
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This dataset provides comprehensive performance statistics for NBA players throughout the 2024/2025 season. It includes both advanced and traditional stats, making it ideal for player performance analysis, efficiency assessments, and exploring game patterns and trends. Data was collected from reliable sources, ensuring quality and consistency across each record.
23.5
= 23 minutes and 30 seconds).YYYY-MM-DD
format.This dataset is perfectly suited for: - Statistical analysis: Gain insights into player and team performance trends. - Machine learning projects: Build predictive models using detailed player stats. - Performance prediction: Forecast player outcomes or team results. - Player comparisons: Analyze players across various metrics and categories. - Efficiency analysis: Evaluate player and team efficiency, comparing statistics across games. - Game trend exploration: Investigate patterns within the season, identifying shifts in strategies and performance.
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License information was derived automatically
Our data sheds light on the distribution of Games stores across different online platforms. WooCommerce leads with a substantial number of stores, holding 21.18K stores, which accounts for 33.25% of the total in this category. Shopify follows with 18.08K stores, making up 28.38% of the Games market. Meanwhile, Custom Cart offers a significant presence as well, with 7.51K stores, or 11.79% of the total. This chart gives a clear picture of how stores within the Games sector are spread across these key platforms.
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The global sports game data software market size was valued at approximately USD 1.2 billion in 2023 and is projected to reach USD 3.8 billion by 2032, exhibiting a CAGR of 13.2% during the forecast period. This robust growth can be attributed to the increasing digitization of sports, the expanding adoption of data analytics in sports management, and the rising demand for enhanced fan engagement solutions.
One of the primary growth factors driving the sports game data software market is the increasing reliance on data analytics to optimize team performance and strategy. Sports organizations and teams are increasingly using complex algorithms and data analytics tools to assess player performance, develop game strategies, and enhance overall team efficiency. Integrating data analytics enables teams to make informed decisions, reducing the margin for error and contributing to better performance outcomes. This transition to data-driven sports management is significantly boosting the demand for sports game data software.
Furthermore, the rising popularity of sports globally and the consequent increase in sports viewership are contributing to the expanding market for sports game data software. With more people engaging with sports events, there is a growing need for advanced software solutions that can enhance fan engagement by providing real-time data and interactive experiences. This trend is particularly prominent in regions such as North America and Europe, where sports events attract massive viewership, necessitating sophisticated fan engagement platforms to maintain and expand audience interest.
The developments in artificial intelligence (AI) and machine learning (ML) technologies are also pivotal in propelling the sports game data software market forward. These technologies enable the creation of advanced data analytics tools that can process vast amounts of data quickly and accurately. The integration of AI and ML in sports analytics not only helps in predicting player performance and game outcomes but also in developing personalized fan experiences. With continuous advancements in these technologies, the sports game data software market is poised for significant growth.
Cricket Analysis Software has emerged as a vital tool in the realm of sports analytics, particularly for cricket teams seeking to enhance their performance. This software leverages advanced data analytics to provide insights into player performance, game strategies, and opposition analysis. By analyzing historical data and real-time match statistics, cricket teams can develop more effective game plans and make informed decisions on the field. The integration of Cricket Analysis Software into team management processes not only aids in optimizing performance but also in identifying areas for improvement, thus contributing to the overall growth of the sports game data software market.
Regionally, North America currently holds the largest share of the market, driven by the presence of major sports leagues and the high adoption rate of advanced technologies in sports management. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period, attributed to the rising popularity of various sports, increasing investments in sports infrastructure, and the growing adoption of digital solutions. This regional growth is further supported by government initiatives promoting sports as a means to enhance health and fitness among the population.
The sports game data software market can be segmented by component into software and services. The software segment dominates the market due to the rising demand for advanced analytics tools that can process and interpret large volumes of data. These software solutions provide critical insights that help sports teams and organizations make data-driven decisions. The software segment includes a variety of applications such as performance analysis tools, strategy development platforms, and fan engagement solutions, which are all essential for modern sports management.
In contrast, the services segment is also experiencing substantial growth, driven by the increasing need for professional services that support the implementation and maintenance of sports game data software. These services include consulting, training, and support services, which are crucial for ensuring the optimal use of data analy
Our NFL Data product offers extensive access to historic and current National Football League statistics and results, available in multiple formats. Whether you're a sports analyst, data scientist, fantasy football enthusiast, or a developer building sports-related apps, this dataset provides everything you need to dive deep into NFL performance insights.
Key Benefits:
Comprehensive Coverage: Includes historic and real-time data on NFL stats, game results, team performance, player metrics, and more.
Multiple Formats: Datasets are available in various formats (CSV, JSON, XML) for easy integration into your tools and applications.
User-Friendly Access: Whether you are an advanced analyst or a beginner, you can easily access and manipulate data to suit your needs.
Free Trial: Explore the full range of data with our free trial before committing, ensuring the product meets your expectations.
Customizable: Filter and download only the data you need, tailored to specific seasons, teams, or players.
API Access: Developers can integrate real-time NFL data into their apps with API support, allowing seamless updates and user engagement.
Use Cases:
Fantasy Football Players: Use the data to analyze player performance, helping to draft winning teams and make better game-day decisions.
Sports Analysts: Dive deep into historical and current NFL stats for research, articles, and game predictions.
Developers: Build custom sports apps and dashboards by integrating NFL data directly through API access.
Betting & Prediction Models: Use data to create accurate predictions for NFL games, helping sportsbooks and bettors alike.
Media Outlets: Enhance game previews, post-game analysis, and highlight reels with accurate, detailed NFL stats.
Our NFL Data product ensures you have the most reliable, up-to-date information to drive your projects, whether it's enhancing user experiences, creating predictive models, or simply enjoying in-depth football analysis.
As the name suggests, free-to-play video games give players access to content free of charge, although sometimes payment is required to enhance in-game features. The global free-to-play mobile gaming market is estimated to reach ***** billion U.S. dollars in 2024, up from ***** billion U.S. dollars in 2023.
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).
Comprehensive NFL game statistics and predictions for Carolina Panthers at Seattle Seahawks, including scores, spreads, over/under, and advanced analytics.
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The Tabletop Role-Playing Game (TTRPG) market has evolved dramatically over the past few decades, emerging as a vibrant community of storytellers and strategists engaging in immersive gameplay experiences. Initially characterized by traditional pen-and-paper formats, the industry has diversified to include a plethor
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Key Mobile Game Demographics StatisticsMobile Game Age Demographics by CategoryGame Gender Demographics by CategoryGames are the most popular app category on both app stores, accounting for about 59...
Comprehensive NFL game statistics and predictions for New England Patriots at Dallas Cowboys, including scores, spreads, over/under, and advanced analytics.
Comprehensive NFL game statistics and predictions for Los Angeles Rams at Dallas Cowboys, including scores, spreads, over/under, and advanced analytics.
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Cloud Gaming Statistics: Cloud gaming, or gaming-as-a-service, enables users to play video games over the internet without needing a high-definition gaming console or a gaming personal computer. Here, the use of cloud servers means that processing power is provided offsite, allowing easy gaming on different devices like smartphones, tablets, and smart TVs.
In 2025, cloud gaming statistics will still dominate the gaming sector as a fundamental tool, owing to the state of the art and the availability of the Internet.
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Casino drop and win data is provided voluntarily by all casinos licensed in Great Britain and shows the amount of money exchanged for chips in a casino (drop) and the amount retained by the casino (win). Drop and win information is provided through regulatory returns monthly and is based on casino games only (not gaming machines). The data is not split into the types of game played as information is considered to be commercially sensitive.
The latest data is published on the final Thursday of every month and is based on an updated rolling year average, showing figures for the previous 12 months.
The information published within the drop and win report is aimed primarily at those within the casino industry although it may also be of interest to international regulators, journalists, academic researchers, financial institutions, statisticians and local authorities.
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Board Game Statistics: ​Board games have experienced a notable resurgence, becoming a preferred pastime for diverse demographics. In the United States, 43% of board game enthusiasts engage in gameplay several times per week, while 25% play weekly. Demographically, 47% of board game players are aged between 18 and 34, with individuals aged 55 and above comprising 18% of the player base. Gender representation is balanced, with women accounting for 51% and men 49% of board game enthusiasts. Regarding game collections, 43% of gamers own more than 25 board and/or card games.
The average playing time for most board games ranges from one to two hours, though this can vary significantly depending on the game's complexity. These statistics underscore the enduring appeal and diverse engagement within the board gaming community.​