The Popularity Rise of Board Games: Quantitative Analysis of Rating Activity
The hobby of playing board games has experienced constant growth for several years. It has now arrived in society at large. An increasing number of games are being published, and more and more people are playing them.
About the dataset
The used dataset is based on ratings that were submitted for games on BoardGameGeek before Sept. 1, 2025.
It includes all ratings given to games with at least 2,000 ratings.
This criterion was met by 2,373 games (excluding expansions).
A total of 20,902,835 ratings were collected for these games, resulting in an average rating of 7.11.
The reason for introducing the minimum rating number restriction is to reduce potential bias,
but also to increase statistical relevance and focus on well-established titles with a large number of users.
Introduction
The world of board games has undergone a remarkable digital transformation over the past few decades.
Founded in 2001, BoardGameGeek (BGG) has established itself as the go-to place for board game fans
worldwide. What began as an online database has grown into the largest and most influential platform
for board games, connecting millions of users worldwide and listing over 130,000 games in its database.
A core feature of BoardGameGeek is its extensive rating system, where users can rate games on a scale of 1
to 10 and write detailed reviews. These ratings are not only valuable to other users when making purchasing
decisions, but also form a unique database that reflects the opinions and preferences of the global board
game community.
In the following analysis, we look at the evolution of reviews on BoardGameGeek over time. We look at
different time perspectives: the total number of ratings since the platform's inception, the monthly
fluctuations in rating activity, and the average daily rating frequency for each year. This analysis allows
us to identify trends and patterns in user activity and draw conclusions about the growth of the platform.
Cumulative Ratings Over Time
For 24 years, it has been possible to submit ratings on BoardGameGeek. Since then, 20,902,835 ratings have been submitted for games that meet the conditions for inclusion in the database. The development of the number of ratings is shown in Figure 1.
Historical growth of total board game ratings on BoardGameGeek from 2001 to present. The blue bars show actual cumulative ratings, while the red dashed line represents a mathematical approximation function that models the growth pattern based on the tenfold increases.
The cumulative rating curve resembles cubic growth.
Starting from 1,000 ratings, the time required to increase the number of ratings tenfold approximately doubles compared to the previous tenfold increase period.
The first 1,000 ratings were submitted after three months.
10,000 ratings are reached after 17 months, 100,000 ratings after 46 months.
One million was reached after 104 months and ten million after 227 months.
The intervals are 14 months, 2 x 14 + 1 months, 4 x 14 + 2 months and 8 x 14 + 11 months.
If you calculate an approximation function with the given values, you get almost a cubic function.
With this function, 100 million ratings would be reached after approximately 496 months.
If the current trend continues, this milestone would be reached in September 2042.
However, a slowdown in the growth rate is already apparent. Figure 4 in particular shows a flattening of the daily ratings.
The values from Figure 1 are alternatively also depicted in Table 1.
Detailed monthly breakdown of cumulative board game ratings. Each cell shows the total number of ratings up to that month.
| Month |
|---|
Ratings per Month and Seasonal Patterns
Although the cumulative ratings over time show absolute values, they make it difficult to gain accurate insights.
For this purpose, it is helpful to look at the ratings submitted for each individual month.
Figure 2 shows all months since the ratings were introduced.
Each month is represented by a bar whose length is proportional to the number of ratings submitted in that month.
Monthly rating activity showing seasonal patterns and long-term growth trends. Chart is zoomable for detailed analysis.
Figure 2 clearly shows that the average number of reviews per month has increased significantly over time.
However, there are very large differences in the number of reviews between individual months.
Due to the high number of reviews, it seems, especially in recent years, that there are very large differences within a year.
However, these differences have existed since the beginning of the reviews, which can also be seen when zooming in on the reviews.
If you compare the months of a year in terms of the number of reviews, you can rank them in order – from the month with the most reviews to the month with the fewest reviews.
If you combine all the years in this way, you can create a heat map that reveals seasonal patterns.
This is shown in Figure 3.
Visual heatmap representation of monthly rating activity. Darker blue indicates higher rating volume, making seasonal patterns and year-over-year trends easily visible.
Looking at the individual months, it can be seen that the middle months of the year tend to have lighter cells, i.e. there are fewer reviews.
The months around the turn of the year, on the other hand, tend to be darker, i.e. there are more reviews.
Therefore, the heat map shows clear seasonal trends.
Since the majority of reviews come from the northern hemisphere, the months with the highest number of reviews fall during the cold season there. The months with the highest average number of reviews are November, December and January.
December has been particularly consistent since reviews began in the peak months of each year. In recent years, January has been the month with the most reviews. This can also be clearly seen in Figure 2.
The months with the fewest reviews are mainly months in spring and summer in the northern hemisphere.
June is usually the weakest month, followed by July, April and May.
Assuming that submitting reviews correlates with playing board games, it becomes clear that people mainly play during the cold season.
As soon as the weather improves and becomes warmer, activities shift outdoors, where board games are played significantly less.
The seasonal patterns identified are not as pronounced in the early years as they are in subsequent years.
This is probably related to the growth of the platform. In the early days, the growth rates of the rating numbers were significantly higher than in later years.
This can also be seen in Figure 4, which analyses the average number of ratings per day.
These high growth rates probably influenced the seasonal patterns in the early years.
In the first few years, the months of the first half of the year in particular had lower review numbers.
At that time, the growth of the platform had a greater influence on the number of reviews than the season.
As the percentage growth slowed, the seasonal patterns became more visible.
Average Ratings per Day by Year
The analysis so far has focused primarily on the growth in valuation figures. But what exactly does this growth look like, and is it consistent? Figure 4 provides some insight into this.
Year-over-year comparison of daily rating activity showing growth trends and patterns.
In general, growth over time can be observed, as has often been mentioned. However, the analysis shows that there are also years without growth and even with a decline in the number of reviews.
The first year in which there were fewer ratings per day than in the previous year was 2010. After that, there was constant growth until 2024, when negative growth was recorded again. It is also clear that the growth rates were very high in the early years, up to 2009.
This was already suspected when looking at the heat map in Figure 3, as it outshone the seasonal patterns. Since 2010, the growth figures have been significantly lower or even negative.
Overall, it can be said that growth continues to decline over time.
