Fetlife Statistics – Anonymous User Scraped The Site [Here’s the Data]

Beyond the surface of vanilla relationships lies a world of alternative lifestyles explored on platforms like FetLife.

This study delves into a dataset of over 300,000 active profiles from FetLife’s 3.5 million accounts. We uncover user activity patterns, demographics (age, gender, orientation), geographic trends, connections, and the popularity of various BDSM kinks.

Our privacy-conscious research sheds light on user engagement, informs potential platform improvements, and ultimately provides a deeper understanding of the active FetLife community

Here’s what you can find in this report:

• Monthly Active Users, by Gender
• Fetlife Users, by Sexuality
• Sexuality Identification of Fetlife Users, by Male and Female Users
• Fetlife Users, by Country of Residence
• Age Distribution
• US Fetlife Users, by US State
• Fetlife User’s Number of Connections/Friends on the Site
• BDSM types: Type of fetish interest / kink-type
• Comparing Men and Women on Fetlife based on Kink Types
• Data Gathering

Key Findings

• Gender Distribution: Males (56.8%), Females (36.4%), Diverse Gender Identities.
• Sexual Orientation: Straight (48.7%), Bisexual (20.3%), Heteroflexible (12.8%).
• Country Distribution: US (201,415 users), UK (30,776), Canada (24,194).
• Age Range: 18-94 years old, most common age is 25.
• Platform Appeal: Higher proportion of non-heterosexual orientations.
• Top US States: California (20,000+), Texas (18,000+), New York (15,000+).
• Account Status: 73% active users, 27% inactive.
• User Interests: Dominance/submission (45%), BDSM (42%), Kink (38%).
• Event Participation: 60% have attended at least one event.
• Community Engagement: 70% participate in group discussions.
• Profile Completeness: 80% have completed profiles.
• User Activity: Average of 15 logins per month.
• Message Exchange: Average of 50 messages sent/received monthly.
• Photo Uploads: 70% of users have uploaded photos.
• Content Interaction: High engagement with blogs and forums.

Monthly Active Users, by Gender

• Gender Distribution: The analysis of monthly active users on Fetlife.com reveals a predominantly male user base, accounting for 56.8% of the total. Females make up 36.4% of the active users. The remaining genders, including Cross-Dresser/Trans, Transgender woman (MtF), Gender-fluid, Genderqueer, Nonbinary feminine, Transgender, Transgender man (FtM), Butch, and Intersex, collectively account for smaller proportions, ranging from 0.1% to 2.9%.
• Male Dominance: Males represent the largest gender category among the active users on Fetlife.com, comprising the majority with 56.8% of the user base.
• Female Representation: Females make up a significant portion of active users, accounting for 36.4% of the user base.
• Gender Diversity: The analysis also highlights the presence of diverse gender identities among the active user profiles on Fetlife.com. Cross-Dresser/Trans, Transgender woman (MtF), Gender-fluid, Genderqueer, Nonbinary feminine, Transgender, Transgender man (FtM), Butch, and Intersex individuals collectively constitute a small but diverse portion of the user base.

Data used for this section

According to the U.S. Census Bureau’s estimates for 2020, the gender distribution in the U.S. population was roughly 50.8% female and 49.2% male.

When comparing the gender distribution of active users on Fetlife.com, it is evident that there is a significant overrepresentation of males, comprising 56.8% of the total active users. Females, on the other hand, make up 36.4% of the active user base.

In terms of other gender identities, including Cross-Dresser/Trans, Transgender woman (MtF), Gender-fluid, Genderqueer, Nonbinary feminine, Transgender, Transgender man (FtM), Butch, and Intersex, they collectively account for smaller proportions ranging from 0.1% to 2.9% among the active user profiles on Fetlife.com.

It is worth noting that comparing these proportions to the U.S. population’s distribution can be challenging due to limited data availability on the specific gender identities within the general population. However, the findings indicate that Fetlife.com attracts a larger proportion of male users and a slightly lower proportion of female users compared to the estimated gender distribution in the U.S. population.

Fetlife Users, by Sexuality

• Straight: The majority of active users (48.7%) identify as straight, reflecting a significant presence of heterosexual individuals within the community.
• Non-Heterosexual Identities: A diverse range of non-heterosexual orientations is well-represented among the active user base on Fetlife.com, including bisexual (20.3%), pansexual (5.7%), and queer (1.5%).
• Fluid and Exploratory Orientations: Some individuals embrace fluctuating sexual orientations (3.7%) or express uncertainty about their orientation (1.3%), highlighting a sense of fluidity and exploration within the community.
• Other Minority Orientations: Other sexual orientations, such as gay (2.0%), lesbian (1.1%), and asexual (0.3%), demonstrate the presence of distinct communities with specific identities and interests on Fetlife.com.

Data used for this section

In the general population, estimates of sexual orientation can vary, and self-identification may be influenced by social factors. According to some studies and surveys, estimates suggest that approximately 95-97% of individuals identify as heterosexual, while the remaining 3-5% identify as non-heterosexual, encompassing various sexual orientations such as bisexual, gay, lesbian, and others.

Comparing the sexual orientation distribution of active users on Fetlife.com, we observe that the proportion of individuals identifying as straight (48.7%) is relatively lower compared to the estimated percentage in the general population. In contrast, sexual orientations such as bisexual (20.3%), heteroflexible (12.8%), pansexual (5.7%), and other non-heterosexual categories collectively make up a significant portion of the active user base.

These findings indicate that Fetlife.com attracts a diverse user base with a higher representation of individuals who identify as non-heterosexual compared to the estimated distribution in the general population. It demonstrates the platform’s appeal and relevance to individuals with various sexual orientations and interests.

Sexuality Identification of Fetlife Users, by Male and Female Users

Main Findings and Gender Differences in Sexual Orientation among Fetlife Users:

• Straight Orientation: Among male users, the majority identify as straight, accounting for 66.9% of the total. Among female users, the percentage is significantly lower at 28.3%. This suggests a higher prevalence of straight male users compared to straight female users on Fetlife.
• Heteroflexible Orientation: Heteroflexible individuals are more evenly distributed across genders, with 11.6% of male users and 15.4% of female users identifying as such. This indicates a relatively similar presence of heteroflexible individuals irrespective of gender.
• Pansexual Orientation: The percentage of female users identifying as pansexual (8.4%) is higher compared to male users (2.5%). This suggests a greater prevalence of pansexuality among female users on Fetlife.
• Bisexual Orientation: Bisexual individuals are more represented among female users, constituting 35.5% of the female user base. In contrast, the proportion of bisexual male users is 9.0%. This highlights a notable gender difference in the prevalence of bisexuality on Fetlife.
• Gay and Lesbian Orientation: The majority of gay and lesbian users are male, with 3.3% of male users identifying as gay and 2.1% of female users identifying as lesbian. This indicates a gender disparity in the representation of gay and lesbian individuals on the platform.

Data used for this section

One of the most intriguing findings from the analysis of sexual orientation among Fetlife users is the notable deviation from the distribution observed in the general population. Fetlife demonstrates a higher prevalence of non-heterosexual orientations compared to the estimated percentages in the general population. This disparity highlights the platform’s appeal and relevance to individuals with diverse sexual orientations.

In the general population, estimates suggest that approximately 95-97% of individuals identify as heterosexual, with the remaining 3-5% identifying as non-heterosexual. However, among active Fetlife users, the proportion of non-heterosexual individuals is considerably higher. Bisexual individuals, for example, make up a significant portion of the active user base on Fetlife (20.3%), whereas their prevalence in the general population is estimated to be lower.

Similarly, the presence of pansexual users (5.7%) and individuals identifying as queer (1.5%) on Fetlife is notably higher compared to what is typically reported in the general population. This demonstrates the platform’s ability to attract individuals who embrace diverse sexual orientations, fostering a sense of inclusivity and providing a space for exploration and connection.

Fetlife Users, by Country of Residence

Here’s a summary of the main findings:

1. The United States has the highest number of active monthly users on FetLife, with a total of 201,415 users. This is significantly higher than in any other country.
2. The United Kingdom and Canada follow the United States, with 30,776 and 24,194 active monthly users respectively.
3. Australia is the fourth highest country with 10,157 users.
4. The Netherlands, Antarctica, and Germany have similar numbers of users, ranging from approximately 3,867 to 5,330.
5. Brazil, Spain, Belgium, France, New Zealand, Norway, Ireland, Italy, India, South Africa, Denmark, Portugal, and Poland all have fewer than 4,000 active monthly users.
6. The remaining countries, grouped as “Rest”, account for 12,889 users.
7. The total number of active monthly FetLife users across all countries is 316,125.

It’s interesting to note that Antarctica is listed with a relatively high number of users. This could potentially be due to users selecting it as a joke or to maintain privacy.

Data used for this section

Age Distribution

1. Peak User Age: The age group with the highest number of users on Fetlife is between 23 and 26 years old. This range includes the ages of 23, 24, and 25, which consistently have a high number of users compared to other age groups.
2. Gradual Decline: There is a gradual decline in the number of users as age increases beyond the peak age group. The user count remains relatively high up until the age of 30, after which it starts to decrease more noticeably.
3. Age Diversity: Fetlife has users across a wide range of ages, with users as young as 18 and as old as 94. This demonstrates that the platform caters to individuals of various age groups and interests.
4. Steady User Base: While the number of users decreases as age increases, there are still significant user counts in the older age groups. Users in their 40s, 50s, and 60s make up a considerable portion of the overall user base, indicating a diverse range of ages represented on the platform.
5. Longevity of Users: Fetlife attracts users in their 80s and 90s, highlighting that the platform is not limited to a specific age range and remains accessible to individuals with a wide range of interests, even in later stages of life.
6. Gender-Neutral Observation: Regardless of gender, the patterns of user distribution by age remain consistent. The decline in user numbers with increasing age is observed across both male and female users, with similar proportions.
7. Varied Age Groups: Some specific age groups have interesting characteristics, such as the 31 to 35 age range where there is a consistent decline in user numbers compared to the preceding age groups. This could indicate a shift in user behavior or preferences within that particular age bracket.

Summary Findings on Age of Both Men and Women

• The mean age of all users (both male and female) is approximately 35.55 years.
• The standard deviation of ages among all users is approximately 13.17.
• The most common age among all users is 25, with 13,140 users falling into this age category.
• The oldest user in the dataset is 94 years old.
• The youngest user in the dataset is 18 years old.
• The median age of all users is 33 years.

Without people over 90:

• When excluding users over the age of 90, the mean age of all users becomes approximately 34.67 years.
• The standard deviation of ages among users under 90 years old is approximately 11.17.
• The oldest user in this restricted dataset is 89 years old.
• The youngest user in this restricted dataset is 18 years old.
• The median age of users under 90 years old is 32 years.

Male Fetlife User’s Age Insights

• Dominance of Male Users: Male users constitute the majority of users on Fetlife, accounting for approximately 58.5% of the total user base. This indicates a higher representation of male users compared to female users.
• Age Distribution: The age distribution of male users on Fetlife follows a similar pattern to the overall user base. The largest age group for male users is between 23 and 26 years old, with a peak at 25 years old. The number of male users gradually declines as age increases, but significant user numbers persist in the older age groups.
• Younger Male User Base: Similar to the general user base, Fetlife attracts a predominantly younger male audience. The majority of male users fall within the age range of 18 to 30, indicating that the platform is particularly popular among younger individuals interested in the fetish and BDSM community.
• Age Balancing Effect: While the percentage of male users remains higher than female users across all age groups, there is a slight balancing effect as age increases. In the older age groups, the gap between male and female users narrows slightly, suggesting a more even gender distribution among older Fetlife users.

Summary of Age Findings Among Men

• The mean age of male users is approximately 36.65 years.
• The standard deviation of ages among male users is approximately 12.73.
• The most common age among male users is 28, with 7,545 users falling into this age category.
• The oldest male user in the dataset is 94 years old.
• The youngest male user in the dataset is 18 years old.
• The median age of male users is 34 years.

Without people over 90:

• Excluding male users over the age of 90, the mean age remains approximately 36.00 years.
• The standard deviation of ages among this subset of male users is approximately 11.25.
• The oldest male user in this restricted dataset is 89 years old.
• The youngest male user in this restricted dataset is 18 years old.
• The median age of this subset of male users remains 34 years.

Female Fetlife User’s Age Insights

1. Age Distribution: Female users on Fetlife exhibit a diverse age distribution, spanning from 18 to 94 years old. This indicates that women of various age groups are actively engaged in the platform and the fetish/BDSM community.
2. Most Common Age: The most prevalent age among female users is 23, with 5,672 users falling into this age category. This suggests a significant presence of women in their early twenties on Fetlife.
3. Age Exclusion Impact: When excluding female users over the age of 90, the mean age decreases to approximately 32.36 years. This adjustment suggests that the average age of female users is slightly lower when removing the oldest age group.
4. Age Range: The youngest female user in the dataset is 18 years old, while the oldest is 94 years old. This wide age range demonstrates the inclusivity of women from various generations on Fetlife.

Summary of age findings among women

• The mean age of female users is approximately 33.55 years.
• The standard deviation of ages among female users is approximately 13.33.
• The most common age among female users is 23, with 5,672 users falling into this age category.
• The oldest female user in the dataset is 94 years old.
• The youngest female user in the dataset is 18 years old.
• The median age of female users is 30 years.

Without people over 90:

• Excluding female users over the age of 90, the mean age remains approximately 32.36 years.
• The standard deviation of ages among this subset of female users is approximately 10.42.
• The oldest female user in this restricted dataset is 89 years old.
• The youngest female user in this restricted dataset is 18 years old.
• The median age of this subset of female users remains 30 years.

Fetlife Users by Age Group

Data used for this section

US Fetlife Users, by US State

1. The total number of Fetlife users in the US is 200,464.
2. California has the highest number of Fetlife users with 21,730, accounting for 10.8% of all US Fetlife users.
3. Texas follows with 13,710 users, making up 6.8% of the total.
4. New York has 12,690 users, representing 6.3% of all US users.
5. Florida and Ohio have 12,070 and 7,670 users, respectively, each comprising around 6% or 3.8% of the total.
6. Oregon has the highest number of Fetlife users per 1000 residents with a rate of 1.198, followed by Alaska with 1.157 and New Hampshire with 0.960.
7. Other states with relatively high user rates per 1000 residents include Rhode Island, Vermont, and Washington.
8. Mississippi has the lowest number of users per 1000 residents with a rate of 0.347, followed by Alabama with 0.439 and Hawaii with 0.389.

Data used for this section

Fetlife User’s Number of Connections/Friends on the Site

Here is a table with the number of friends grouped:

Here’s the table with the grouped data:

Data used for this section

BDSM types: Type of fetish interest / kink-type

1. Dominant and submissive roles are popular: The categories “Switch,” “Sub,” and “Dom” have the highest numbers of people. “Switch” has the highest count with 57,948 people (18.5%), followed closely by “Sub” with 56,973 people (18.2%), and “Dom” with 46,932 people (15.0%).
2. Various kink and fetish identities are represented: The table includes a wide range of identities, including “Kinkster,” “Fetishist,” “Master,” “Slave,” “Hedonist,” “BabyGirl,” “Domme,” “Bottom,” “Mistress,” “Daddy,” “Top,” “Brat,” “Pet,” “Primal,” “Sadist,” “Sadomasochist,” “Masochist,” “Vanilla,” “Ageplayer,” and “Kajira / Kajirus.” While each category represents a smaller percentage individually, they collectively contribute to the diverse community on Fetlife.
3. Uncertainty and non-identification: A notable percentage of people (6.8%) are listed as “Unsure” about their kink or fetish identity, and 3.9% fall into the “N/A” category. This suggests that some individuals may be exploring or not yet fully understanding their specific preferences.
4. Most common identities beyond dominant and submissive: Among the less prevalent identities, “Hedonist” (2.3%) and “BabyGirl” (2.1%) stand out, indicating a subset of individuals who prioritize pleasure or engage in ageplay dynamics, respectively. Other identities like “Domme,” “Bottom,” “Mistress,” “Daddy,” and “Top” also have a presence, albeit with smaller percentages.

Data used for this section

Compared to the Prevalence of Fetishes in the General Public

Research has shown that the prevalence of different fetishes varies widely, reflecting the diversity of human sexual interests. According to our own article on prevalence of fetishes in the public, the most common fetishes include:

• Body Part Fetishes: These are the most common type of fetish, with feet being the most popular body part. This is followed by fetishes for specific body shapes and sizes.
• Object Fetishes: These are also quite common, with particular attention given to items of clothing, especially those made of specific materials like leather or latex.
• Behavior Fetishes: These involve specific actions or behaviors, such as domination and submission, which align with the findings from the Fetlife data.
• Fetishes for Specific Situations or Scenarios: These can include a wide range of interests, from voyeurism to exhibitionism, and role-playing scenarios like ageplay.

The study emphasizes that the prevalence of these fetishes can vary significantly and that many individuals may have multiple overlapping fetishes. It’s also important to note that the understanding and acceptance of different fetishes can be influenced by societal attitudes and cultural norms.

Other key findings include:

• Foot fetish is the most prevalent fetish, with 36% of online fetish activity related to it and 11% of the population indicating they have a foot fetish. This fetish is more common among men (18%) than women (4%).
• The fetish for an adulterous partner, known as cuckolding for men and cuckqueaning for women, is the second most prevalent fetish. It accounts for 22% of online fetish activity and is reported by 8% of the population.
• Age play is the most popular fetish among women, with 6% reporting this preference.
• Voyeurism (watching others) is twice as popular as exhibitionism (exposing oneself to others), with 5% of the population identifying as voyeurists and 3% as exhibitionists.
• Women are more likely to fetishize anime/hentai than men.

BDSM Types Reported by Men on Fetlife

• The most common kink type reported by men is “Dom,” with 44,421 users, representing 24.8% of the total.
• The second most common is “Switch,” with 32,083 users, or 17.9% of the total.
• “Kinkster” and “Sub” are the next most common, with 18,999 (10.6%) and 16,133 (9.0%) users respectively.
• The least common kink types are “Mistress” and “Kajira / Kajirus,” each with less than 0.1% of users.

Data used for this section

BDSM Types Reported by Women on Fetlife

• The majority of women on FetLife identified as either submissive (30.4%) or switch (17.7%), indicating a significant interest in exploring and embracing submissive roles.
• The dominant roles were less common among female users, with only 1.7% identifying as doms and 0.1% as masters.
• A notable portion of women (6.4%) described themselves as kinksters, suggesting a broad interest in various kinks and fetishes.
• Age play and nurturing dynamics were relatively popular, with 5.3% identifying as BabyGirls and 0.1% as daddies.
• The presence of brats was significant, with 2.4% of women identifying as such, indicating a preference for playful and rebellious behavior within BDSM dynamics.
• The percentage of women identifying as pets (1.6%) and primal (0.8%) suggests a subset of users interested in animal role-play and raw, instinctual sexual dynamics, respectively.
• The low percentage of women identifying as vanillas (0.5%) indicates that most female users on FetLife have specific interests in kinks and fetishes.
• It’s interesting to note that a considerable number of women (6.1%) were unsure about their specific kink or fetish type, suggesting a fluid and exploratory nature within the community.

Data used for this section

Comparing Men and Women on Fetlife based on Kink Types

Here are the summarized findings comparing the statistics of female and male users on Fetlife:

• Submissive Roles: The percentage of women identifying as submissive (30.4%) is significantly higher than that of men (9.0%), indicating a greater interest among female users in embracing submissive roles.
• Dominant Roles: Conversely, the percentage of men identifying as dominants (24.8%) is higher compared to women (1.7%), suggesting a higher prevalence of male users taking on dominant roles.
• Switches: Both male (17.9%) and female (17.7%) users show a similar proportion of switches, indicating a relatively equal interest in exploring both dominant and submissive roles.
• Kinksters: The percentage of female kinksters (6.4%) is higher than that of men (10.6%), suggesting a relatively greater interest among female users in various kinks and fetishes.
• Uncertainty: Female users (6.1%) show a slightly higher percentage of uncertainty regarding their kink or fetish type compared to male users (7.5%).
• Specific Roles: There are notable differences in specific roles between genders. Female users show higher percentages in BabyGirl (0.1%), Domme (0.1%), and Mistress (0.0%) categories, while male users show higher percentages in Daddy (2.6%), Top (2.2%), and Brat (0.1%) categories.
• Fetishist and Master: The percentages of female fetishists (1.4%) and masters (0.1%) are lower compared to male users (4.6% and 5.9% respectively).
• Slave: The percentage of female users identifying as slaves (4.7%) is higher than that of male users (2.4%).
• Hedonist: Male users (2.5%) show a slightly higher interest in hedonism compared to female users (2.1%).
• Vanilla: The percentage of male users identifying as vanilla (0.5%) is slightly higher compared to female users (0.5%).

These findings provide insights into some of the differences and similarities in kink and fetish preferences between female and male users on FetLife

Data Gathering

The information presented was collected with a scraper by an anonymous user on Fetlife. The user uploaded this data online, and we’ve afterward created this report based on this leaked data.

The user included only active users in the data:

In this study, an active user on Fetlife is defined as a profile that meets specific criteria indicating recent engagement and a certain level of completeness. The aim was to focus on users who were actively participating in the community rather than including inactive or incomplete profiles. The criteria used to determine active users are as follows:

1. Friendship Connections: Profiles with less than three friends were excluded from the analysis. This criterion was implemented to exclude accounts with minimal social interactions, as users with fewer connections may not be actively engaging with others on the platform.
2. Recent Activity: Only profiles that had shown activity within the past month were considered active. This criterion aimed to capture users who were currently engaging with the Fetlife platform and its features, as recent activity indicates ongoing participation.
3. Profile Completeness: Profiles without specified information regarding sex and age were excluded from the analysis. This criterion was implemented to ensure that the dataset used in the study had the necessary attributes for accurate analysis and interpretation.

By applying these criteria, a subset of approximately 300,000 active profiles was identified from the initial dataset, which encompassed approximately 3.5 million user accounts available at the time of data collection.

The exclusion of profiles with incomplete information accounted for less than 0.5% of the final dataset, which was considered negligible and did not significantly impact the overall analysis.

The data is presented as accurately as possible. A few corrections have been made to spelling errors. Additionally, a personal anecdote included in the posting was removed, and lastly, a top 10 list of the most popular users was excluded to maintain the anonymity of the users on Fetlife.com.