Size Ratios for Activewear: How Brands Plan XS to 3XL Runs

Ask a brand what decided their season and they will name a style. Ask their warehouse and it names a ratio. The legging that sold out in medium while extra-small sat folded into the next year was not a design failure; it was an arithmetic failure, decided on the order sheet. Size ratios are the least glamorous decision in an activewear order and the one with the most money riding on it, because every unit placed in the wrong size is a unit bought, shipped, stored and discounted.

This guide explains how demand actually distributes across an XS to 3XL run, how to read your own sales history into a ratio, and how ratios differ by garment, following the planning we apply to our leggings and sports bra programs.

Why Size Ratios Decide Sell-Through More Than Style Does

Sell-through is measured across the order, but customers shop one size at a time. A style can be a hit and still post a poor season if the hit lived in three sizes and the stock sat in seven. The reverse is also true: a modest style with a disciplined ratio quietly sells its full depth and reorders, while the exciting style with the careless curve is still being discounted when its reorder should have shipped.

Ratios also compound across colour. Every colourway multiplies the size grid, so a ratio error is never one mistake; it is the same mistake in black, navy and the seasonal colour, each with its tail. Brands feel ratios as margin: the difference between selling ninety percent at full price and seventy is rarely the product. It is the curve.

Ratio planning is a skill with data behind it. Demand across sizes follows patterns stable enough to plan against, and forgiving enough that a considered first curve beats a copied one every season.

The Bell Curve and Where Activewear Demand Really Sits

Apparel demand across sizes always forms a bell: light at the extremes, heavy in the middle. In women’s activewear the weight concentrates in medium and large, with small close behind, extra-small and the plus sizes forming the tails. Men’s curves centre on medium and large with a stronger extra-large shoulder. The shape shifts by market, age profile and garment, but the bell is universal, and any flat ratio, equal units in every size, fights it directly.

Across a seven-size women’s run, a starting curve might place a tenth in XS, a sixth in S, a quarter each in M and L, a sixth in XL and the remainder split across 2XL and 3XL. Treat those proportions as a sketch to correct with your data, never as a standard to copy, because the brand selling in one market and the brand selling athleisure in another are drawing different bells from the same sizes.

Two forces bend the curve over time. Populations in markets are gradually shifting the bell rightward, growing the plus tail; and a brand’s audience self-selects, so a label known for extended sizing draws demand its early ratios never predicted. Reviewing the curve annually is not bureaucracy, it is how the ratio stays married to the customers arriving.

XS and 3XL: The Ends of the Range and Their Economics

The ends of the run carry a strategic question disguised as a quantity question. XS and 3XL units sell slower per size, cost the same to make, and occupy the same grid, so a commercial reading trims them. But the ends are where inclusion is proven: the customer who finds her size at the edge of your range becomes the customer who trusts the middle of it.

The answer is depth discipline rather than deletion: carry the ends, in every core colour, at shallower depth, and let reorder speed rather than opening stock serve their spikes. A size that stocks out at the tail costs less than a size that never stocks out because it never sells.

Pattern economics support the ends more than buyers expect: once grading is done, the marginal cost of including an end size in a run is the fabric and make of its units alone. The expensive decision is the fit work plus sizes deserve, covered below, and it is a one-time pattern investment, not a per-order tax.

Reading Your Own Data: Returns, Sell-Outs and Waiting Lists

Your sales history is the only ratio data that is yours, and three signals in it matter. Sell-out speed by size is the headline: the size that empties in week two was under-bought whatever the totals say, and the size still full in week ten was over-bought even if it eventually cleared on markdown. Speed, not totals, is the curve speaking.

Returns data is the second signal, and it needs reading by reason: a size returned for fit at high rates may indicate a grading fault rather than weak demand, and cutting its ratio would treat a pattern problem as a popularity problem. Waiting lists, pre-orders and size-alert signups are the third, the demand you never stocked, invisible in sales totals and often concentrated at the ends buyers are tempted to trim.

First-season brands without history borrow curves in order of honesty: the manufacturer’s experience with ranges, the norms of their market and channel, and a plan to overweight the middle and learn fast. Our MOQ and production structure supports that learning, because ratios can be tuned per colour and style inside an order rather than locked across the buy.

Ratios by Garment: Leggings, Bras, Tops and Shorts Differ

One curve across a collection is a convenience, not a plan, because garments draw different bells. Leggings centre hard on M and L with a meaningful S, their fit forgiveness letting customers size within the middle. Sports bras skew smaller and wider at once, band sizes spreading demand, which is why the construction logic in our sports bra support guide pairs with a broader, flatter curve than a brand’s tops.

Tops follow the bell most obediently. Shorts skew larger than tops in the same range, as customers size for comfort and movement, and men’s bottoms run a stronger XL shoulder than men’s tops. These are tendencies to test against your data, offered because a per-garment adjustment of even one step, moving a few points of the order from XS to XL on shorts, is the kind of arithmetic that rescues a season’s tail.

Colour interacts: core black carries the full curve at full depth, fashion colours can run a narrowed curve centred on the proven sizes, and the newest colour in the range is the worst place to gamble on the tails.

Grading Across the Curve: Fit Changes, Not Just Measurements

A ratio plan assumes every size in it fits, and across XS to 3XL that assumption needs work behind it. Standard grading grows a pattern by fixed steps, which serves the middle and the ends approximately: rise, waist placement, strap position and support needs all change character at the plus end, and a 3XL produced by arithmetic alone fits like a rumour of the medium.

Extended ranges fit-test at the ends, on bodies from the ends, and adjust the grade rules where the tests demand. The cost lands once, in pattern development, and the return is that the tail sizes earn reviews as good as the middle, which is the only sustainable way to keep those customers season after season.

Buyers should ask any manufacturer how their plus sizes were developed and tested, and listen for fit models and adjusted grades rather than assurances. The claim is easy, the photographs and the pattern history are the proof.

Splitting the Order: Core Ratio, Test Sizes and Reorder Speed

The mature structure splits the buy into three intentions. The core ratio carries the centre of the curve at full depth in core colours: this is the stock the season is built on. Test quantities at the ends and in new colours run shallow, priced as information, their sell-out speed the data next season’s curve is built from. And the reorder plan, sizes and styles flagged for fast replenishment, is agreed before the first order ships, because the best ratio correction is a quick one.

Reorder speed changes what the opening ratio must achieve. With a replenishment route, the opening buy can centre tighter, knowing the winning sizes refill; without one, the opening curve must guess the season in advance, and its tails should carry insurance depth accordingly. Brands should negotiate the reorder terms alongside the first order, not after the first sell-out.

Across seasons the system compounds: each season’s speed data sharpens the curve, the ends get their depth, and the warehouse stops being where margin goes to be folded. Ratio planning is unglamorous in exactly the way profit is.

What an Activewear Manufacturer in Bangladesh Needs in Your Ratio Plan

Send the ratio as a grid, sizes across, styles and colours down, quantities in the cells, rather than as a total with instructions to spread it. Flag which sizes are core, which are tests, and which styles carry reorder priority, and state the fit evidence behind your plus sizes or ask for the development work to be quoted. A manufacturer reading a grid quotes accurately, cuts economically and packs by size as your warehouse wants to receive it.

Quantities follow the standard structure, 1,200 pieces per style in up to two colours, and the ratio lives comfortably inside it: the MOQ governs the style total, while the curve governs how the total divides. Brands planning a first run can send us last season’s sell-through by size, and the first curve we propose will be standing on your data.

Frequently Asked Questions