There's been a whole lot of talk going around here lately about points costs and the coming adjustment. I've done my fair share of speculating and campaigning for my favorite adjustments as well, but yesterday I got curious about what the actual data says by itself. I constructed a mathematical model to interpret all the data from Meta Wing that's been collected since Wave III dropped. It was a tad ambitious and it's taken me a lot more time than expected, but I've finally come up with some results that I'm happy with, though a few particulars surprise me.
TL;DR: I applied an algorithm to ListFortress data to propose new points for every pilot and upgrade in the game. They can be found in this Google Sheet:
https://docs.google.com/spreadsheets/d/1fZqj7rroGGcAPio285FJ7qOnluaUtixxs508FJq1pwQ/edit?usp=sharing
The basic idea for generating a mathematical formula would be that:
a) Cost adjustment based on performance is a function of mean percentile
b) Sample size sets the absolute maximum by which a pilot's cost can be adjusted based on performance
c) Pilots with a very small sample size get a cost decrease to bring them more into the meta
Basically this yields a formula of:
[New Cost] = [Old Cost] + { [Old Cost] x [Max Correction] x [Adjustment] } + { [Old Cost] + [Scarcity Bonus] }
Of course, I couldn't allow the maximum correction to be directly linear based on sample size or that could lead to some extreme overreactions. On the other hand, I'm not really a statistician and I can't plot crazy bell curves and do tons of stuff with standard deviations; the purpose of this exercise is to be fairly approximate anyway. I did want to use a horizontally-asymptotal function to set a hard limit on maximum correction size. The simplest horizontally asymptotal function I could think of was a basic Harmonic function (1/x) Inverted and offset to make the absolute maximum performance-based adjustment possible (assuming an infinitely ubiquitous ship averaged the 99th percentile) of 20%, though of course none of the adjustments in my model approach that level of change.
This is the graph of the Maximum Correction function, where Y is maximum correction percent and X is sample size:
- 10 / (0.01x + 0.5) + 20

I then took the data from ListFortress and found the mean pilot's percentile at 26.41. To bring all pilots in line with that performance level, I took the difference of their mean percentile and 26.41, then dividing by the mean to give a performance ratio between -1 and +1. I could have used this linearly, but it hardly led to any changes except to the most abusive ships, so once again I used a harmonic function (had to use absolute values and sign correction) to make sure that those even closer to the power curve were brought in line.
This is the graph of the Adjustment function, where Y the correction to be made (as a fraction of Maximum Correction and X is sample size:
± 1 / (5x + 1) ± 1
(The signs were corrected in the spreadsheet with the SIGN function)

So now we have corrections made based on performance level with a maximum change as a function of sample size. Great! Except it doesn't do anything for the poor ships like Leebo and Rebel Fenn Rau that didn't show up in the data at all, and it will hardly do anything to help the pilots that have only been used 1-25 times in OP since Wave III.
For these, I use another harmonic function starting at -5% and approaching 0 as the ship becomes more common. It has less than half a percent effect on ships with 100 or more uses but should drop prices on unused ships by an amount too small to wreck the meta but hopefully enough to incentivize bringing them more often. Time will tell.
This is the graph of the Scarcity Bonus function, where Y is the correction percent and X is sample size:
- 5 / (0.05x + 1)

It was a pretty interesting exercise and the results are... kind of surprising. No matter how I change the coefficients or even use constant functions, the data insists that Guri's price needs to go down and that Kylo needs a substantial increase (both of which I wasn't expecting and don't expect from the devs, but hey, statistics!). Rebel Han is poised as one of the biggest subjects for a nerf, while Dash gets the biggest buff. Now possible are:
• 4x naked TIE Silencers
• 6x Special Forces TIE
• 5x naked Cavern Angels Zealot
• 6x Planetary Sentinel
• 6x Alpha Squadron Pilot
• 5x Crack Sabers
But why keep on talking? Here's the new data so you can have your fun speculating on how grateful we are that this isn't the way the Devs do this:
https://docs.google.com/spreadsheets/d/1fZqj7rroGGcAPio285FJ7qOnluaUtixxs508FJq1pwQ/edit?usp=sharing
EDIT:
Added sheet for upgrades. Method was similar but data is much more sensitive since point values are significantly lower and changes up to 100% are quite common at those values. Further information downthread.
EDIT 2: UPDATED for Season 2 2019. All data since July 31 goes into the S2 projections. The final projection comes from averaging Season 1 and Season 2 projections, giving double weight to the more recent one. I expect to continue with this algorithm in the future.
Edited by ClassicalMoser


