I actually put this together back in February, with an accompanying Twitter thread about how I built the kink negotiation spreadsheet and going through the maths. I fully intended to do this write up and share the spreadsheet I made back then but I errr … kinda forgot about it. Yeah the evidence that I might have ADHD is getting pretty conclusive xD
If you just want to get the spreadsheet then here it is! You’re welcome to have it for your own kink negotiations and share with fellow kinksters across the world. I only ask that if anyone asks you credit me for creating it. If you want to know a little more about this then read on!
This came about when I was doing a kink negotiation and thought a checklist would be useful. This is based off of Bex Caputo’s version. I love that it differentiates between ‘yes i’m into that’ and ‘yes I’ll do that if you’ll enjoy it’. It also has options to mark favourites. There’s always more you could add to a kink list but this one is pretty comprehensive. He also covers language and emotions in his consent checklist, which I also included. This basically reformats his work into a spreadsheet, you can check the original here.
Because I’m a big old nerd (and also quite autistic) I set it up as a spreadsheet. This allows you and a partner to compare kinks with a visual system as shown in the screenshot below. If you’re really interested you can see how I built it in the original Twitter thread.
How To Use It In A Kink Negotiation
So the honest answer is that you should use it however you want. It’s a tool to aid a discussion of shared kinks and build a connection grounded in Risk Aware Consensual Kink. How exactly you go about a kink negotiation is personal. If you’re new to this and unsure then there are some useful resources out there, but ultimately it’s about whatever helps this conversation with your partner or partners.
The way I’ve found it useful was as a starting point for conversations. For me that’s what a kink negotiation is all about, not simply comparing kinks but using it to open up conversations about what you have in common and start bouncing ideas back and forth. As part of this you also start to understand what makes each other tick. Going through different kinks and comparing answers with a partner works for me. Also, I’m extremely prone to getting distracted. A list means we’re less likely to miss out something important in our kink negotiation while excited by the potential to play together.
Kink Compatibility Index – The Maths
I’ve used a simple approach to assign quantitative values to answers. It assumes the difference between maybe and no is the same as the difference between willing and into. It takes not answering as no, consent is opt-in not opt-out.
And now we start on the notation, this is horrible in word processors so I’ve done it as handwritten notes. Basically this just means that T_x1 refers to the topping preference of partner 1 for kink x. So if topping for x is a favourite it’s a 4, whereas maybe is a 1
We are interested in the difference between one partners topping preference and another partners bottoming preference. We don’t care about whether the top is more into it or the bottom so we take the absolute value (which ignores whether this value is positive or negative.)
Adding in the other side of this (how much partner 2 likes to top for kink x and how much partner 1 likes to bottom for it) and we have our overall differential for kink x for partners 1 and 2 given as KD_x1:2. This measures how different 2 partners preferences for kink x are.
Once you have the formula you repeat it and add together all the results for all the kinks/sex acts covered in the negotiation spreadsheets (the number of kinks is represented here by n). In mathematical notation that’s expressed by the formula next to the arrow
And we end up with … a number. Which on it’s own doesn’t mean much. To work out what this means we need to look at mathematical limits. Any kink differential has a maximum value of 8 (one partners favourite and for the other it’s a no for both combinations of top and bottom) and a minimum of 0 (you and your partner are in perfect agreement in both combinations of topping and bottoming).
So the theoretical maximum of the sum of kink differentials for n kinks is 8n. Divide the sum of the results by that and we get a number between 0 and 1. With 1 being perfect incompatibility (everything is a favourite or a no and they never line up) and 0 being perfect agreement.
That’s counterintuitive, so to switch it around we subtract that number from 1. And there we have it. The kink compatability index for partners 1 and 2. I’m aware I’m probably in a minority but I think it’s beautiful. A complicated idea expressed in 26 characters.
We can repeat this with the data from the language and emotion questions (the only real difference is the different scoring system for emotion) and calculate a language compatability index (LC_1:2) and an emotion compatability index (EC_1:2) for partners 1 and 2. Add them altogether and divide by 3 and we get a combined fetish compatability index for partners 1 and 2 (FC_1:2). A value between 0 and 1 which expresses how neatly two people’s horny interests line up.
Kink Compatibility Index – Data
We know the mathematical limit of the kink compatibility index (KCI), it is impossible for it to return values below 0 or above 1. But what if you calculate that you and your partner have a kink compatibility of 0.6? Is that high, low, amazing, disappointing? I don’t know, nobody can really know at this point because we don’t know what the typical range of scores are.
A more useful measurement tool might be percentile rankings, e.g. this is higher than 80% of KCIs, that would give some context of how closely matched the two kink profiles are. But to do that we need data.
First off lets talk about how this data could be distributed. I’m going to assume it follows the normal distribution because (as the name suggests) that’s what normally happens. It’s possible it could be a skewed dataset (as shown in the picture below), but that still doesn’t change things too much . I’m not going to go too much into the normal distribution here because it gets complicated – but here’s a good video if you do want to know more.
An important thing to note is that the closer you are to the average value (the middle of the normal distribution) the more a change in the KCI effects your percentile ranking. As you get further from the centre of the distribution the data gets a lot more spread out. For example, lets assume that the average KCI is 0.5, with a standard distribution of 0.1. A value of 0.5 would put you above 50% of matches. Increase that to 0.55 and your percentile ranking rises 19% to 69%. But if it increases by the same amount again to 0.6 your percentile ranking only increases by 15% this time, to 84%.
So how much data would we need to make this work? With statistics it’s kind of the case that more is better – the law of large numbers dictates that the larger your sample size is the more closely your results should reflect the parameters of the whole population. We would also have a fair amount of selection bias if the data was collected from people who choose to fill this out for personal use – people who spend their free time using kink negotiation tools are probably going to have more kinks than the general population and that’s potentially going to affect the distribution of KCIs.
Crucially the data we are looking for to formulate our probability distribution is not the people filling out the kink profiles, but the KCIs we can generate by comparing any two kink profiles. So we also need to look at the relationship between the number of kink profiles and the number of potential kink negotiations we can generate a KCI for. As you increase the number of people in the system the number of connections increases as illustrated below.
In mathematics this sequence is known as Triangle Numbers. The value of each triangle number increases as described in the mathematical formulations below. With these formulae we can calculate how many KCIs can be calculated from any given number of kink profiles.
Lets say we decide on 1000 datapoints as a nice round number to start with. 1000 matches to generate the probability distribution which we can then get our percentile rankings from. How many people do we need to get that information? Its actually fairly straightforward, we just need to rearrange the equation as shown below and plug it into the quadratic equation. There are two possible roots, for our purposes we obviously need the positive one. So that’s 44.22, rounded up to 45. We need 45 people to collect the 1000 datapoints we wanted (with 35 to spare).
So why can’t I do this? 45 people isn’t that many, I just need to have an exceptionally slutty weekend (note to self, that would be a good way to celebrate my 30th …) But while we only need 45 completed kink profiles to generate the 1000 data points, the calculations still need to be run 1000 times. To my knowledge there’s no simple way to automate a process that complicated, at least not one I’d want to rely on. What you would really want is a database designed to automatically run these calculations as new users are added, updating the distribution of KCIs as you go. I’m sure there are ways to do this but a) I’m a data analyst not a programmer and b) this is starting to sound like a “setting up a tech startup” level of effort rather than my normal level of hyperfixation.
Kink Compatibility Index – Why It’s Not In Here
Besides the technical issues detailed above, there’s another reason it isn’t in this version of the spreadsheet. I’m worried about how the data could be misused or misunderstood.
The Kink Compatibility Index does exactly what it says, it measures on a technical level how well two people’s kinks align. Obviously it can’t tell you whether or not you’ll get along with a person. A kink negotiation checklist should only ever be tool – a starting point rather than the be all and end all. The beginning of an honest conversation about what you want and a continuous learning practice between partners. And I worry that if I put this out there then it could be misinterpreted as measuring how good a match people are (i.e. what every dating website does), and I really don’t want to do that.
As much as I love the maths, numbers can’t express the complexities of souls entwined. The feeling of seeing and being seen – losing yourself in lust and love and exquisite ecstasy. Great writers can barely scratch the surface of that sensation, simple numbers can’t even get close.