Estimating The Mating Pool Size. Part 2: Female Profiles


Female mating skew 2: Supported by online dating experiment

In this first test, conducted on the dating site Badoo, I published the results of a subset of dummy profiles. I begin by reviewing contact and reciprocation parameters. I tested what is the relationship between the attractiveness of initiators and recipients of the initial messages and reply behaviors. How the reply probability of a message correlates with attractiveness of the sender and receiver. And how the reply probability depends on the extent to which the sender’s physical attributes match the receiver’s stated preferences. These variables allowed me to measure the mating skew that quantifies the degree of unequal partitioning of mating output among individuals, the female mating biases that generate higher mating success for a subset of males. And I could partially quantify the set of mating options.

Quantification of dating pools through an online dating system.

In this quick second experiment conducted on the dating site OKCupid, my purpose was to test a new study to assess the mating pool of some dummy profiles estimated through compilation of incoming messages and potential matches’ offers. This matching feature works as a unimodal or binary “like” function (“yes”/”no” rating) and it’s a depth and single dimension for defining mating choice decisions.

Estimating the mating pool size. Part 1: male profiles

In this third study, my task was to provide a broader topography using a wide-ranging variety of dummy profiles. I have omitted the compilation of incoming messages and I focused on the quantification of the dating pool just through the matching system feature. In this experiment, I’ve inserted a wide range of profiles on the dating site Lovoo. The first part of this study was already published. Now is the turn to analyze the data from female profiles.


I will collect and analyze the same variables studied in the male case. The dummy female profiles will be introduced on the same mating system, the dating site Lovoo, over the same 1-week period. They were placed into the same geographical place, a big-sized city.

Although additional variables are clearly relevant to assess the mating pools, such as the quality of potential mates within them, my goal is going to focused in measurement of the size of the mating pool. As I explained in the previous post, it was not possible to develop a index of quality of the mating pool, because I could infer social desirability on the basis of the evaluations of other users in the dating site (ratings).

On the other hand, the thumbnails photo galleries are not going to be submitted on this post, because of a logistical problem. As readers will see below, the huge number of male members composing each mating pool makes infeasible this task. So I apologize for not being able to provide the thumbnails galleries for the second part of this test.

Initially I thought of dividing the attractiveness scale into 5 equal categories:high (8-10), medium-high (6-8), medium (4-6), med-low (2-4), and low (<2).  But I finally decided  to merging the last two categories into a single range labeled as low-attractiveness (<4).

Dummy profiles:

According our previous poll,  we have 2 girls , A(8.2) and F (8.8), sorted into the high category of attractiveness (ranging from 8 to 10 on a 10 points scale). And 4 girls, B (7.18), C(6.82), D (7.40) and E(7.74) sorted into the medium-high category.

a) High-attractiveness dummy profiles (>8 points on a 1-10 scale):

Girl A (rating: 8.2 points):

Female partner A

Female partner A

Girl F (rating: 8.8 points):

Female F

I will introduce into the system 2  control profiles within the “high”category, increasing my confidence in the measures reliability. I tried to get homemade pictures (taken from Facebook) of anonymous girls who had modeled occasionally,  so they could be objectively classified within the top-tier of the “high”category. These are the 2 control female profiles:

Girl Z:


Girl Y:


2) Medium-high attractiveness dummy profiles:

Girl B (rating: 7.18):

Female partner B

Female partner B

Girl C (rating: 6.82):

Female C

Female C

Girl D (rating 7.40):

Female partner D

Female partner D

Girl E (rating 7.74):


Female E

Since in my listing of mismatched couples had no girl rated below 6, I had to choose two new women that may be in the medium and low category.

3) Medium-attractiveness dummy profile (4-6). :

Female M

Female M

d) Low-attractiveness female (<4 points):

Female L

Female L


1) High-attractiveness dummy profiles:

Girl A:


Girl F:


Girl control Z:


Girl control Y:


2) Medium-high girls:

Girl B:


Girl C:


Girl D:


Girl E:


3) Medium-attractive girl:


4) Low-attractive girl:



Table of results:

Results for female profiles:


Results for male profiles (see first part of the study):



Mating inequality between sexes:

Bateman’s principles explain sex roles and sexual dimorphism through sex-specific variance in mating success, reproductive success and their relationships within sexes (Bateman gradients).

Different decision rules for determining mating preferences often lead to different mating options for the actively searching and the choosy sex (females). Sexual selection often leads to radical sexual dimorphisms, or dissimilarities between males and females, in appearance, behaviour, and reproductive role.

•The female dating size (1864.7 guys) outnumbered the men’s (35.68 girls) in 52 to 1.

•The most ranked women had a mating pool almost 16 times more larger than the most ranked men.

• The medium-high women had a mating pool almost 223 times larger than the medium-high men.

•The female medium category had a mating size almost 434 times larger than the male medium group.

• The low-attractive man had no potential mate, while low-attractive woman got a mating pool of 940 men.

• The low-attractive girl had a mating size (940) 7 times larger than the dating size for best-looking guys (130).

These huge inter-sex differences in pools of available mates perhaps reflect a lower proportion of women entering into the matching tool for searching mates.

This supports that females are more selective, given that mate search frequency is a corollary of selectivity. Other data sets also prove that women are much pickier in their communications, due to the relative rarity of a women initiating contact with men on the dating sites. Males send out more messages but receive fewer messages. And females are more likely to be contacted but less likely to reply to male messages.

That works as a feedback process in mating Leks, since that male searchers become less choosy over time because most of them are unsuccessful at finding mates whereas women, who are much more discriminating than men. And this wide availability of male potential mates (huge dating pools), counter-selects females to evolve more resistance to (i.e., decreased attraction) and increasing their mate thresholds. So cyclic antagonistic co-evolution ensues.

Measuring the Mating Skew:

Mating skew is a index for quantifying the degree of unequal partitioning of mating output among individuals of the same sex.  This empirical test show that, the mating pool were much more variable in males than in females, resulting in a steeper male Bateman gradient, consistent with Bateman’s principles.

1) Mating skew for males:

• The most attractive men (dating pool mean=130 girls) received 91% of all mating options (dating pool mean for male group=142.7).

• The medium-high group got 6.3 % of the mating options.

• The medium group had 2.6 % of the mating optiones.

• The low category had 0%.

2) Mating skew for females:

• First, note that the pool size for the high category is only 1.01 times larger than the high-medium category, 1.24 larger than the medium niche, and 2.1 larger than the low category.

• The most attractive women (dating pool mean=2025 men) received 30.7% of all mating options (dating pool mean for male group=6588.5).

• The medium-high group got 30.3% of the mating options.

• The medium category had 29.7 % of the mating options.

•The low category had 14.2% of the mating options.

In this study we can see how sexes differ greatly in the distribution of mating options among same-sexed individuals. In men, highly attractive individuals of the group monopolizes the vast majority of mating output (mating skew is high), whereas mating pool is much more equally distributed in women (mating skew is low).

This supports the observation that, unlike female preferences, male ‘preferences’ are inclusive of a broad range in female variance. While females are the reproductively limiting sex, male preferences are so much more inclusive of female variance, women shows a higher requisite stimulatory threshold to induce her mating response. Females have an optimum mating rate that is lower than the males, with high-rate fitness optima, and correspondingly high male optimal mating rate).


About Sir Tyrion Lannister

I am not associated with any institution (which seems still necesary for get invitations to participate in writing review papers) but I am doing some theoretical unpaid research on my own. I want to work/publish some Paper but I am not affiliated with an Institution and I have not heard anything about selling research (paper) outcomes to an institution.
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15 Responses to Estimating The Mating Pool Size. Part 2: Female Profiles

  1. thegreatshebang says:

    As you know, I appreciate all of the work of these studies. I think the large number skews support the prima fascia argument that your results are preliminary valid and would hold up under meta-analysis, thus overcoming the small flaws in generating profiles.

    I found it interesting that the control profiles for women had 10 times as many kisses as women without professional photos.

    • sirtyrionlannister says:

      Good point regarding the number of followers & kisses received for female control profiles. I’d say that on very binary terms (number or likes/yeses), male users tend to assess the attractiveness degree in similar proportions for all high and medium-high girls. But it’s true that some attentional bias is performing in a subset of men.

      Some users can send kisses (winks) in order to draw the attention of other users. Moreover is required spend credits for sending kisses. So perhaps that is showing the extent to which attention bias becomes more stuck on some particular visual stimuli. Therefore this suggests that females Z and Y have gained greater biases in attentional adhesion. And since these two girls would be on the top tier of high range, their higher attractiveness degree can lead to higher biases in attention adhesion on some men.

      • thegreatshebang says:

        Always a lot of info in your analysis, I’ll chew on it.

        You may consider contacting Stardusk, the video blogger on YouTube. He switched his channel from Stardusk and now posts under Thinking Ape. He is very interested in all of this data and wants to promote it. He does the best he can and always wants more scientific info. He recently has said he may consider going back to school to get a PhD and specifically tailor his career to provide info like that which you generate. I sent him a link to your blog a while back and if you haven’t heard from him then you may consider getting in contact with him via PM.

        • sirtyrionlannister says:

          Thank you, friend. That guy has not contacted me. Anyway I’ll check out his channel, so maybe I could exchange some thoughts with him.

          • thegreatshebang says:

            NP. He has so many videos. If you don’t easily find the ones on evo-psych, let me know and I’ll do a search for 5 or 6 of the better ones.

  2. sirtyrionlannister says:

    Yeah thanks, I’d appreciate if you point out which are the best ones. Anyway it appears to be just audios, without video tracking. It’s like listening to podcasts.

    • thegreatshebang says:

      Yes, many of his videos are podcasts. Here is one that has five data charts:

      South Korea’s Suicide Epidemic

      But most are audio only podcasts. Here are some of the best recent ones:

      An Overview of Common Logical Fallacies

      Mgtow Talks: The Terrifying Science of the Human

      Neo-Confucianism and Decline of Marriage in the Far East

      Thought, Language, and Change

      Here are some older ones that are very good:

      Briffault’s Law: The Most Important Thing you can know as a Man

      Neotony, Hypoagency, and the Nefarious Consequence and Solipsism

      Fisherian Runaway: The Tale of the Irish Elk and the Human Male

      Here are a couple of interviews with Karen Straughan, aka “Girl Writes What”:

      GirlWritesWhat and Stardusk: Evo-Psych, MRM, Autopilot, “Love”, and more

      MGTOW Talks: GirlWritesWhat On Traditionalism, MGTOW and Society

      You also will want to check out her channel.

  3. Macgyver says:

    Reblogged this on The Mating Mind.

  4. Anonymous says:

    Brilliant post, just stumbled across your blog. I’d just be careful directly comparing the absolutes of males vs females unless you checked that the registration numbers are roughly like real life. Males might outnumber females on the platform, at least to an extent.

    • sirtyrionlannister says:

      Yes I agree, the operational sex ratio (OSR) is a important factor in the choice biases. Unfortunately this dating site (Lovoo) does not display number of registered users for each sex. Some dating sites allow to view this proportion, but it’s not very useful since there are a lot of ghost profiles. We can not know how many users are functional and active. Also the large number of fake profiles (mainly females) on lovoo is another problem.

      However, keep in mind that in real life (offline) also occurs usually a great imbalance occurs in mating environments such as bars and nightclubs, where men outnumber women by far.

  5. I am enjoying your articles. I see you have not created an article in a while. I may offer a suggestion out of personal interest.

    Women frequently deny that they place a substantial amount of importance on physical attractiveness, as I am sure you are aware. They can do this in interesting ways. Often they’ll say physical attractiveness is significantly subjective. That people don’t agree on what’s attractive. If people don’t agree on what’s attractive, then this should mean that there is a partner for what could be deemed an objectively ugly man. I have my doubts that physical attractiveness is actually significantly subjective. It would seem unlikely that physical attractiveness is both very important, and significantly subjective. It would not make sense from an evolutionary perspective.

    If you were to make an article addressing subjectivity in assessments of physical attractiveness, that would be interesting.

    • sirtyrionlannister says:

      Thank you for your suggestion, I’ll bear that in mind. I stopped writing for a few month on here but I plan an upcoming back. I’m already working on some new online dating studies. But also I’d want to write other more theoretical articles about mate choice, to avoid monothematic saturation.

  6. LOLMAN says:

    Use a girl that looks about 14 and see how much interest she gets.

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