Vining Gallery · The Invitational
Sell-Through Gauge
Set a painting's dimensions and asking price. This checks that price-per-square-inch against 668 works and 291 sales from six years of the Invitational (2020–2025) to estimate its odds of selling during the show.
A note on pricing
As a rough benchmark, 8x10ish – 9x12ish work sells at scale in the Invitational at around $4–6 a square inch. The smaller the work goes, the higher the square inch price can go. The larger the work, the average price per square inch needs to fall. Price your work however you want and I will support it. My hope is that this tool can help provide some understanding of where I historically sell at in my gallery.
It's worth keeping in mind that even a 40–50% shot on this scale is actually a good target percentage. This isn't an exact science and sales are always unpredictable, but this is how I have priced my own shows to sell through at scale for the last 15 years. It is also worth noting, every year, a handful of small works go for $1,000+; those are the exceptions, not the rule. Sometimes we know we have an A+ painting and price it accordingly, every year I sell paintings that fall well outside of the range I typically sell at. I use this data to inform, not control my decisions.
The Painting
The Estimate
estimated chance this piece sells during the run of the show
Six years, size and price
See where your painting falls within the data
- Sold
- Not sold
- This painting
Both axes are log-scaled. The dashed diagonals mark constant price-per-square-inch — every painting along one line carries the same ratio, only larger or smaller.
How this estimate is calculated
Every sale sheet from the Invitational's first six years (2020–2025) was combined into one dataset: artist, size, asking price, and whether the piece sold. Of 688 works with a recorded price, 668 also had usable width and height — that set is what powers this tool.
A logistic regression was fit on log(price) and log(area) against sold/unsold. Both mattered on their own — a $500 piece and a $500-priced ratio behave differently depending on how large the canvas is — and together they're mathematically equivalent to modeling price-per-square-inch directly, while staying easy to check against real dimensions. Checked in 8 probability bins, the model's predicted rate tracked the actual sold rate closely at every bin, from 17% predicted / 11% actual at the low end to 74% predicted / 74% actual at the high end.
The red / yellow / green cutoffs (25% and 45%) aren't arbitrary — they're where the historical outcomes actually separate. Sorting all 668 works into those same three bands by their predicted odds, the pieces landing in the red band sold 17% of the time, yellow sold 36% of the time, and green sold 58% of the time — a clean split either side of the show's 43.6% overall average.
The "similar pieces" note beneath the estimate is a second, independent check: it searches the 668 real works for ones near this painting's actual size and price-per-inch and reports how often those sold, widening the search only if too few comparables exist nearby.
This is a read on historical pricing patterns, not a guarantee — it has no way to see the painting itself. Subject, quality, framing, an artist's following, and where a piece hangs in the show all move the real odds, sometimes by a lot.