Can your "market value" be measured?
Not as a single number, no. Search "how attractive am I" or "SMV calculator" and you'll find quizzes that hand you a score out of 10. The research on attraction points somewhere less tidy: people agree on some things, disagree on a lot, and much of the disagreement depends on the specific pair of people. What you can measure well is smaller and more useful: what you do and what happens next.
What the calculators claim
SMV stands for "sexual market value," a term that, per the Wikipedia article on sexual capital, began on pickup artist forums, and is defined in UN Women's 2026 glossary of the manosphere as a ranking of people's worth by physical appearance and status. Calculators turn that idea into a form.
One example, checked in October 2026, asks men for height, a facial attractiveness rating out of 10, a body and fitness rating out of 10, annual income, a social status rating and age. It returns a score from 0 to 10. The page calls its formula "research-backed" and says scores are within about 0.7 points, but it names no studies, gives no validation data and doesn't publish how the inputs are weighted (it also has a separate version for women). Its own fine print says the tool is "for entertainment and self-development only," that scores don't guarantee dating outcomes, and that results depend on location, culture and chemistry.
Notice what the inputs are. Most are your own ratings of your face, body and status, and the weights aren't published. The output looks like a measurement, but it's built from self-ratings.
What research says about shared taste
Attraction isn't pure chaos, and it isn't a single scale either. Two bodies of work seem to point in opposite directions, and both are real.
Some agreement. A 2000 review in Psychological Bulletin by Langlois and colleagues ran 11 meta-analyses and reported that raters agree about who is and isn't attractive, within cultures and across them. They also found that attractive children and adults were judged and treated more positively than unattractive ones. This is about ratings of faces and people in studies, not about who anyone chooses to date.
A lot of private taste. In 2006, Hönekopp ran three experiments on facial attractiveness judgments and reported that private taste is about as powerful as shared taste. His argument was that earlier researchers had overstated how much standards are shared.
Even more private once people meet. In 2014, Eastwick and Hunt had classmates rate each other at the start and end of a semester, and studied long-term acquaintances in a third study. They found more variation tied to the specific pairing than to the person being rated. Agreement was higher for traits like attractiveness than for how good a partner someone would be, and agreement fell as people got to know each other. They reported that romantic evaluations were more likely to be unique to a particular person than shared.
Put together: strangers' snap ratings share a fair amount. As people interact, the shared part shrinks and the pair-specific part grows. A number computed before anyone talks can't capture the pair-specific part.
What mate-preference research can and can't say
The preference research is often cited to justify scores, so here are the limits.
- A 2014 meta-analysis of 97 studies (Eastwick, Luchies, Finkel and Hunt) found physical attractiveness predicted romantic evaluations at about r = .40 and earning prospects at about r = .10, for both sexes. An r of .40 is a moderate link. Square it and attractiveness accounts for roughly 16 percent of the variation in how people rated others, leaving most of it unexplained.
- In a 2008 speed-dating study, Eastwick and Finkel found that what people said they wanted beforehand didn't predict who they were drawn to at the event.
- A 2020 study of 14,399 people in 45 countries (Walter and colleagues) found group-level differences in stated preferences, such as men rating attractiveness and youth higher on average and women rating partner age and financial prospects higher on average. These are averages across large groups from questionnaires, the same kind of data summarized in what people look for in a partner. They say little about which individual a given person will like.
None of this was designed to score one person. Averages describe populations. A calculator takes an average and applies it to you, which is a step the studies themselves don't take.
What you can actually measure
Your own actions are countable, and they respond to changes you make.
- Approaches and asks. How many conversations you started this week.
- Replies. How many people texted back, and how quickly.
- Dates. How many turned into a meeting, and how many into a second one.
- Notes. What you tried, and what happened.
In Run Game you log each approach as Success or Rejected with an optional note, and your success rate is successes divided by successes plus rejections. Stats also shows an outcome funnel: got number, texted, date set, went on a date, dating.
Two cautions. Small numbers are noisy: 1 success in 10 approaches and 3 in 10 can come from the same person on different days, so look at trends over several weeks rather than single sessions. And outcomes depend on the place, the time and the other person's day, so they measure how that conversation went, not what you're worth.
If you want to work on the visible parts, how to be more attractive separates what you can change from what you can't. For the research on where the language of status comes from, see status and value in dating, and stop needing approval if the number has started to matter too much. If a low score left you feeling like everyone else is ahead, dating when you feel behind is aimed at exactly that.
What to do next
- Skip the calculators, or treat them as a toy. If you try one, note what it can't know about you.
- Pick three numbers you control. For example: 10 conversations a week, 3 numbers or handles asked for, 1 date planned.
- Log every approach for four weeks. Write one line of notes each time on where you were and what you said. Tracking your approaches shows a simple setup.
- Review weekly, not daily. Once a week, look at counts first, then read the notes for patterns.
- Change one thing at a time. A new opener, a different place, a different time of day. Run it for two weeks before judging.
- Ask for a second opinion from a person. Ask a friend who's seen you in social settings what you do well. One real answer beats a decimal.
Sources
- UN Women, Glossary: The manosphere (SMV definition)
- Wikipedia, Sexual capital (origin of the term SMV)
- TotalCalcHub SMV calculator, checked October 2026 (inputs, scale and disclaimers)
- Langlois et al. (2000), Psychological Bulletin, "Maxims or myths of beauty?" (PubMed)
- Hönekopp (2006), Journal of Experimental Psychology: Human Perception and Performance, private and shared taste (PubMed)
- Eastwick and Hunt (2014), Journal of Personality and Social Psychology, relational mate value (PubMed)
- Eastwick, Luchies, Finkel and Hunt (2014), Psychological Bulletin, ideal partner preferences meta-analysis (PubMed)
- Eastwick and Finkel (2008), Journal of Personality and Social Psychology, speed dating (PubMed)
- Walter et al. (2020), Psychological Science, 45 countries (PubMed)