How the figures are built
From an observed fee to a percentile you can quote in a negotiation — the full pipeline in plain English: every source and its weight, the rules that keep junk out, what n really counts, and the honest limits of the data. Free to cite under CC BY 4.0.
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Last updated: 31 July 2026
What the Index measures
UK live music only. Every figure is what the performer takes home, in pounds — tickets, door splits, gear hire and travel never enter the dataset.
Coverage and definitions
A published cell is the meeting point of three axes: where (a canonical city, one of twelve UK regions, or the national baseline), what kind of gig (seven types, weddings to theatre/pit), and how many musicians (solo, duo, 3–4 piece, 5+). Each cell carries four percentiles — p25/p50/p75/p90 — never an average.
How to read a rate cell
Averages lie in a market where a Mayfair gala and a Tuesday pub slot share a spreadsheet. So every figure here is four: p25 the budget end, p50 the typical fee (half pay less, half more), p75 a strong booking, p90 the premium tier. Find your quote on that curve and you know where you stand.
Where the data comes from
Money that provably changed hands says more than a listings-page price — so every source class is capped at a maximum share of any published figure.
The source classes and their quotas
Every observation lands tagged with source, gig type, band size, venue type and location, through a single ingest funnel with documented provenance. Each source class then owns at most a fixed share of any published cell — the caps below sum to 1.00. A class that grows by collection cadence rather than by market activity therefore cannot buy influence with volume: scanning more rate cards sharpens the rate-card estimate within its ceiling. A class reaches its cap only as it accumulates evidence (credibility n ÷ (n + 50)), so a handful of rows cannot spend a large quota on noise.
Honest limit: a quota binds only while another class has evidence to absorb the remainder. Where a cell is served by one source, that source carries the figure whatever its cap. Classes with no observations yet — currently confirmed bookings and venue gig budgets — hold quota that cannot be claimed.
| Source | Max share | Why it counts this much |
|---|---|---|
| Anonymous public submission | 0.20 | A gig someone actually played, self-reported |
| Post-event verified submission | 0.18 | Artist-reported, matched to a real event |
| Confirmed GigXchange booking | 0.15 | A cleared transaction — the strongest signal per row |
| Artist profile asking rate | 0.13 | Stated rates from real acts on the platform |
| MU / Equity recommended rate | 0.10 | The union floor — authoritative, not market-clearing |
| Industry published rate card | 0.10 | Asking price, commission stripped at ingest |
| Venue gig budget | 0.09 | The buyer’s pre-negotiation spend plan |
| Web-extracted rate | 0.05 | Public-page extractions, human-reviewed |
| Ticket-derived club estimate | 0.00 | Room-economics model — shadow mode, excluded from published cells |
- Public submission 0.20 36
- Verified submission 0.18 39
- Confirmed booking 0.15 none yet
- Artist profile rate 0.13 335
- MU / Equity minimum 0.10 143
- Industry rate card 0.10 3,471
- Venue gig budget 0.09 none yet
- Web-extracted rate 0.05 173
- Ticket-derived (shadow) 0.00 none yet
Caps sum to 1.00. Confirmed bookings and venue budgets hold quota no one can claim yet — that unclaimed share passes to whoever does have evidence.
Re-scanning rate cards every Monday sharpens the rate-card estimate. It cannot enlarge the rate-card vote.
What is flowing now — and what is wired, awaiting volume
Flowing routinely: weekly re-scans of published UK industry rate cards (Mondays), the monthly artist-profile panel of stated rates (snapshots on the 28th), and fees reported by gig-workers through the public submission form (reviewed, then synced daily). Musicians’ Union and Equity published minimums refresh annually.
Wired in, awaiting volume: confirmed GigXchange bookings — the 1.00-weight reference signal — are plumbed in but have yet to arrive in volume, so the Index still leans on asking prices and listings more than settled fees. Venue gig budgets, web-extracted editorial rates and ticket-derived club estimates have each contributed rows but are not yet routine inflows. This split is reported honestly in every issue — it is the single biggest thing that will sharpen the Index.
Counting rules
Two rules decide what a number means before it ever reaches a percentile: everything is normalised to artist take-home, and nothing is allowed to count twice.
Fee basis and the commission haircut
Every observation carries a fee_basis field. Gross-of-commission sources — industry rate cards and agent-rostered artist profiles — are converted to artist take-home before percentile computation using a 20% default agency commission haircut (net = gross ÷ 1.20); agent-brokered bookings use the booking’s recorded commission. Already-net sources (MU/Equity rates, venue budgets, verified submissions) pass through unchanged. Every published figure is therefore artist take-home — client-facing gross prices typically run ~20% higher.
Re-sighting, deduplication — and what n really counts
A listing that survives week after week is information — the price is stable — but it must never count twice. When a weekly scan meets a listing it already knows, it bumps that observation’s sighting counter instead of inserting a copy.
Reading note: the n shown against a cell counts weighted samples, not unique gigs — an observation counts at every geographic level it informs and once per re-sighting, so cell-level n runs far higher than the pool of unique observations. The distinct pool size is published in every issue (4,290 approved observations in the July 2026 issue).
The quality firewall
Every observation faces the same gates whatever its source, and every rejection is logged with a reason — the audit trail is part of the product.
Five gates, plus one for ticketed clubs
Has the basics — no amount, no source, no gig type: no entry. From a known source — only the vetted source list may write to the Index, through a single ingest funnel. Is an artist fee — the database layer itself refuses ticket money, gear hire, licensing and door splits. Passes the plausibility check — each gig type carries per-musician-per-hour bounds, so a £40 wedding quartet and a £20,000 pub solo both bounce automatically. Not a duplicate — every observation is fingerprinted; a re-scanned listing bumps a sighting counter, never becomes a second row.
Ticketed club fees face a sixth test: a four-archetype room-economics model grounded in Music Venue Trust occupancy data — ticket price × capacity × realistic occupancy × the act’s share of the door.
Anonymous submissions
Anyone who has played or booked a UK gig can report the fee at gigxchange.app/rates — no account needed. Submissions are rate-limited, sanity-checked and human-reviewed before they touch a cell, entering at weight 0.16; match one to a confirmed event later and it graduates to 0.85.
When a figure publishes
A figure only publishes when there is enough behind it — and when there isn't, the calculator tells you exactly which level answered instead.
Cell thresholds and geographic fallback
Publication happens at three levels: city (major UK metros, with satellite towns folded into their hub — Hove reads as Brighton, Oldbury as Birmingham), region (the twelve official UK regions), and the UK baseline. Every level publishes on the same threshold: three distinct observations in the cell — three separate gigs, not three sightings of one rate. When you look up somewhere we cannot yet publish, the live calculator walks the chain — city, then region, then the national figure with a regional adjustment — and tells you which level answered. Thin cells additionally carry a low-sample flag.
Three is deliberately low while the Index is young. A thin cell published with its sample size attached is more useful than no cell at all, and every figure carries its n so a reader can weigh it. The threshold ratchets upward as coverage grows, and it only ever moves up — it is never lowered to make a cell publishable. At present more than half of all measured cells rest on fewer than ten observations, so single-city figures are indicative; the national baselines carry the weight. Cells with no observations behind them at all are derived rather than missing — § 11 explains how, and every one is flagged.
Regional adjustments
The adjustment layer blends ONS regional household income and family-spending data with public industry price benchmarks, tuned per gig type: corporate fees track regional wealth closely, wedding spend barely does, and pub fees hardly flex at all because venue economics set the ceiling everywhere. Adjustments only ever fill gaps — wherever real observations exist, they win outright.
Derived cells, and how they are marked
Coverage is uneven: a city may have plenty of wedding observations and none at all for a four-piece in a pub. Rather than leave a hole that makes cities incomparable, the Index fills that gap with a derived cell — and marks it as derived everywhere it appears, in the API, the dataset and on the page. The value is the national figure for that same gig type and band size, scaled by how that city prices against the national baseline on the cells it does have. We use the city’s own observed pay level rather than its neighbours’, because geography is not what sets gig fees — Brighton’s nearest large market is London, and borrowing London’s rates would simply make Brighton look dearer than it is.
Every city carries the same grid. An index is only an index if you can look up any town and find the same data points, so the grid is every gig type and band size the UK baseline can anchor — 22 cells, identical in all thirteen cities. It is not narrowed to whatever a city happens to have collected; that would make towns incomparable, which is the fault derived cells exist to fix.
Two rules keep it honest, and they are deliberately the ones that stop nonsense rather than the ones that limit coverage. A city needs three real cells of its own before we will estimate how it prices at all — below that it gets no derived cells. And a real cell more than three times, or less than a third of, its national counterpart is treated as unusable and replaced by the derived figure, with the original retained in the record. Both thresholds only ever ratchet upward as coverage grows; they are never loosened to make a figure publishable.
Derived cells are never evidence. They are never counted in a sample size, never used to calculate another cell, and never written back into the observation record — the raw data stays purely observed. They are rebuilt from scratch on every refresh, so the moment real observations arrive for that city and gig type, the derived figure disappears and the real one takes its place. Anyone wanting measured figures only can filter them out in a single step.
| Gig type | Solo | Duo | 3–4 | 5+ |
|---|---|---|---|---|
| Pub / bar | £300 | £251 | £200 | £335 |
| Wedding | £221 | £352 | £663 | £998 |
| Private party | £209 | £290 | £570 | £452 |
| Corporate | £258 | £299 | £544 | £882 |
| Club | £168 | £314 | £402 | · |
| Festival | · | · | £448 | £1045 |
| Theatre | £117 | · | · | · |
Three cells are measured, nineteen derived. Every other city answers the same twenty-two questions — that is what makes the league a like-for-like comparison rather than a comparison of who has collected most.
- London 11/22
- Manchester 10/22
- Bristol 8/22
- Birmingham 6/22
- Brighton 6/22
- Cardiff 5/22
- Edinburgh 5/22
- Glasgow 5/22
- Leeds 5/22
- Liverpool 5/22
- Sheffield 4/22
- Newcastle 3/22
- Nottingham 3/22
This is the number to weigh a city figure by, and it is published beside every one of them. It only goes up.
Refresh cadence
The cells rebuild nightly at 05:00 UTC. Industry rate cards re-scan on Mondays; the artist panel snapshots on the 28th; approved submissions flow daily. Every rebuild is archived rather than overwritten — that is what makes issue-on-issue comparisons possible. The full report ships monthly.
Honest limits
A record of what the UK market paid, asked or budgeted across the observation window — nothing more.
What this is and isn’t
Not a recommended price. We publish where the market sits, not where you should sit in it — undercut or exceed any figure here with a clear conscience. Not an official benchmark. No industry body endorses or regulates these figures; independence is the point. Not financial advice. Evidence in, decision yours. Not the whole market. Most UK gig fees are agreed privately and surface nowhere — an index can only weigh what it can see.
Known gaps are reported in each issue: confirmed platform bookings have yet to arrive in volume, festival and theatre remain the thinnest gig types, and no genre-level cells publish yet — the tags exist on every observation, and publication waits on volume, not engineering. Corrections to our own data are documented in the open in the issue they land.
Many city figures are derived, not measured. Where coverage is thin we publish a derived cell rather than a hole, always flagged as such — see § 11 for exactly how, and the guards that bound it. A derived figure is an estimate of what a city would pay given how it prices elsewhere; it is not a record of a gig anyone played. Coverage is uneven and we publish it openly: London rests on real observations for 11 of its 22 cells, Manchester 10, and Newcastle and Nottingham 3 — every city figure carries that count, so you can see at a glance how much of it is measured.
Datasets, DOIs & downloads
The report, the live figures and the raw dataset are all published under Creative Commons Attribution 4.0 — use them, republish them, build on them commercially, with credit.
GigXchange Index, UK Live Music Booking Rates 2026. Available at: https://gigxchange.app/rates. Licensed under CC BY 4.0.
July 2026 — 4,290 observations, 13 cities
Read online · PDF · CSV · Zenodo DOI 10.5281/zenodo.21712429 · Hugging Face · Kaggle
June 2026 — 4,036 observations, 13 cities
Read online · PDF · CSV · Zenodo DOI 10.5281/zenodo.21197463 · Hugging Face · Kaggle
May 2026 — 3,847 observations, 13 cities
Read online · PDF · CSV · Zenodo DOI 10.5281/zenodo.20304563 · Hugging Face · Kaggle
April 2026 — 2,381 observations, 14 cities
Read online · PDF · CSV · Zenodo DOI 10.5281/zenodo.19663015 · Hugging Face · Kaggle
CC BY 4.0
Cite as “GigXchange Index, gigxchange.app/rates”. Machine-readable snapshot: /data/rates-snapshot.json. Live percentiles: the GX Index hub. All monthly issues: the reports library.











