The rate index for UK live music
The median UK gig fee is £350 for a solo act and £800 for a 3–4 piece function band, based on 4,200+ observations (18,000+ weighted samples). What to charge. What to budget. Live market data, free for everyone.
Last updated: 31 July 2026
Live snapshot — July 2026
As of 2026-07-31 the GigXchange Index holds 4,290 approved observations across 13 UK cities, 9 use cases and 5 band-size buckets. Fees below are artist take-home medians (50th percentile, GBP). Free to cite under CC BY 4.0.
Refresh nightly 05:00 UTC · industry rate cards re-scan Mondays · methodology · monthly reports · CC BY 4.0
Why a transparent rate index matters
The GigXchange Index is an open UK rate benchmark covering 13 cities and 4 band-size brackets — artist take-home percentiles by city, gig type and band size, refreshed every 24 hours, with sources re-scanned every 7 days (methodology). It exists because the UK live music market needs transparent pay data — and the figures below, from the largest survey of UK musicians ever conducted, show the cost of going without it.
Source: Musicians’ Census (Help Musicians UK & the Musicians’ Union, ~6,000 respondents).
Find your market rate
Pick your role, answer three questions. We'll show you where the market sits.
Were you paid fairly?
Set your gig in the calculator above, then drop in what you were paid. We’ll place it against the market — and you can add it to the Index in one click.
What did you actually get paid?
Pick your act type and the kind of gig, drop in what you were paid, and the Index will place it against the market.
The market, your way round
Pick any two of city, gig type and band size. Click a cell to load it into the calculator. Colour depth shows where on the price curve each cell sits.
| City Gig type | Wedding | Corporate | Private party | Pub / bar | Club | Festival | Theatre |
|---|---|---|---|---|---|---|---|
| Birmingham | — | ||||||
| Brighton | — | ||||||
| Bristol | — | ||||||
| Cardiff | — | ||||||
| Edinburgh | — | ||||||
| Glasgow | — | ||||||
| Leeds | — | ||||||
| Liverpool | — | ||||||
| London | — | ||||||
| Manchester | — | ||||||
| Newcastle | — | ||||||
| Nottingham | — | ||||||
| Sheffield | — |
13 of 91 cells hold fewer than 3 samples and are not published.
What a gig pays per musician, per hour
A headline fee hides how many people split it and how long the day runs. Divide by both and the market reads very differently — this is the number the Musicians’ Union and Music Venue Trust argue over.
Working out the hourly rates…
How the Index works
Nine sources spanning 13 cities and 4 band-size brackets, a strict quality firewall, weighted percentiles, and regional price adjustments — rebuilt every 24 hours.
Collect
Publicly available industry rate cards (re-scanned every 7 days), a monthly panel of artist profile asking rates, Musicians' Union and Equity published rates (refreshed every 12 months) and anonymous public submissions — all funnelled into one observations table with documented provenance. Venue gig budgets and editorial pricing extractions are wired in, awaiting volume; confirmed bookings on GIGXCHANGE — the highest-weight signal — join as real booking volume arrives.
Clean
Every row passes a five-gate firewall before ingest: required fields, source whitelist, artist-fee only (ticket prices and licensing are banned), plausibility bounds (typical artist take-home £15–£500 per hour per musician, capped at 8 hours), and dedup. Anything rejected is logged for audit, not silently dropped.
Weight & aggregate
Each observation carries weight × confidence — real bookings count 1.00 per observation, industry rate cards 0.48 per observation, asking prices 0.16 per observation. Percentiles (p25 / p50 / p75 / p90) are weighted, then rolled into cells at three scopes: canonical city → ONS region → UK baseline, with regional economic multipliers filling thin gaps.
Frame
Same cell, different copy per role — artists see a charging recommendation; venues, agents and promoters see a budget. Cells rebuild every 24 hours at 05:00 UTC from the previous day's ingests.
The latest issue is live
Every month we publish a full report covering this month's headline rates by city, gig type and band size, plus the methodology and data sourcing in detail.
Contribute — sharpen the Index
Artists, venues, agents, promoters — every booking you've done is a data point the whole market needs. 3 anonymous submissions unlocks every percentile and trend for 30 days. No email required.
Submit a rate — what you charged or paid
One booking, under 1 minute. City, gig type, band size, fee. Anonymous and rate-limited — capped at 3 per hour per session. Whether you're the act, the buyer or the broker — your data point makes everyone's pricing decisions sharper.
Methodology & transparency
A complete description of the data acquisition, weighting and aggregation framework underpinning every published cell. For the current issue's sources, weights and honest limits, see the full methodology page.
Coverage and definitions
The Index covers the United Kingdom only. A cell is defined by the cross-product of three dimensions: geography (one of three scopes — canonical city, ONS statistical region, or UK national baseline), use case (seven engagement categories: wedding, corporate, private party, pubs & bars, club, festival, theatre), and band size (bucketed: solo, duo, trio/quartet, five-plus). Each cell publishes percentile statistics — the 25th, 50th (median), 75th and 90th percentiles of weighted observations resident in the cell. The Index is median-based throughout; no arithmetic mean is computed or published.
Data acquisition
The Index ingests observations from nine source classes, each with documented provenance and a deterministic reference identifier enabling idempotent re-ingestion: confirmed booking transactions on the GigXchange platform; post-event-verified user submissions; Musicians' Union and Equity published rates (refreshed every 12 months); publicly available industry rate cards (refreshed every 7 days from publicly listed UK booking-agency directories); publicly available editorial cost-explainer articles; artist profile self-declared min_fee/max_fee; venue gig-budget declarations; anonymous public submissions (pending review); and forum observations (reserved). Every row additionally carries descriptive metadata — source channel, market segment, band type, venue hint and genre hint — from which the use case is derived at ingest rather than forced.
Weighting framework — source quotas
Reliability is expressed as a quota, not a per-observation multiplier. Each source class may own at most a fixed share of any published cell, however many rows it holds; the caps sum to 1.00. This bounds a source that grows by collection cadence rather than by market activity — scanning more rate cards refines the rate-card estimate inside its ceiling instead of buying a larger say. Per-observation weighting cannot do this: a class holding 80% of rows retains roughly 80% of the influence at any weight.
| Source class | Max share | Rationale |
|---|---|---|
| Anonymous / unverified submission | 0.20 | A gig someone actually played, self-reported |
| Post-event-verified submission | 0.18 | User-reported, subsequently confirmed |
| Confirmed booking | 0.15 | Cleared transaction; strongest signal per row |
| Artist profile asking rate | 0.13 | Self-declared. Agent-rostered profiles net-normalised at 20%. |
| MU / Equity published rate | 0.10 | Authoritative floor, not market-clearing |
| Industry published rate card | 0.10 | Client-facing gross; normalised to artist take-home via a 20% default agency commission haircut before percentile computation |
| Venue gig budget | 0.09 | Pre-negotiation target, not transacted |
| Editorial / listing extraction | 0.05 | Third-party published text |
Earning the quota. A class reaches its cap only as it accumulates evidence, using the actuarial credibility factor n ÷ (n + k) with k = 50. Three observations therefore cannot spend a 0.20 quota on noise. Within a class the share is divided across its rows in proportion to recency (weight 3 within six months, 2 within twenty-four, otherwise 1), so a class total always equals exactly the share it has earned. Percentiles are computed as a weighted cumulative crossing of the pooled distribution — no observation is duplicated, and the sample size printed against a cell is a count of distinct observations.
Honest limit. A quota can only bind while another class has evidence to absorb the remainder. Where a cell is served by a single source, that source necessarily carries the figure regardless of its cap; the effective ceiling tightens as coverage broadens. Classes with no observations at all — today confirmed bookings and venue gig budgets — hold quota that cannot currently be claimed.
Fee-basis normalisation. Every observation carries a fee_basis field (net, net_derived, unknown) and, where applicable, paired gross_amount / commission_amount fields. Gross-of-commission sources (agent-brokered bookings, industry rate cards, agent-rostered artist profiles) are converted to artist take-home prior to percentile computation: for agent-brokered bookings using the booking's recorded commission; for rate cards and rostered profiles using a 20% default haircut (net = gross ÷ 1.20). Already-net sources (MU/Equity rates, venue gig budgets, verified user submissions) pass through unchanged. Percentiles are therefore all expressed as artist take-home.
Cell aggregation and geographic fallback
Cells publish at three scopes: canonical city (13 population centres; raw city slugs are normalised via a mapping function — e.g. Hove → Brighton, Oldbury → Birmingham); ONS region (twelve Standard Statistical Regions); and UK national baseline. Every scope publishes on the same threshold: at least 3 distinct observations in the cell. That count is a count of separate observations, not of re-sightings of the same rate. At lookup time a three-step fallback applies: if a canonical city cell exists it is used directly; if not, the containing region is consulted; if the region is also thin, the UK baseline is returned.
On the threshold. 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 judge it. The threshold ratchets upward as coverage grows, and it only ever moves up. At present more than half of all published cells rest on fewer than ten observations, so treat single-city figures as indicative and prefer the national baselines where a decision depends on it.
Regional pricing layer
When a lookup falls back to the UK baseline and the user's region is known, a regional multiplier is applied to adjust the published percentile toward that region's market conditions. Multipliers are derived from a source-weighted blend of ONS Regional Gross Disposable Household Income (2023), ONS Family Spending Survey recreation-and-culture expenditure shares, and industry surveys (publicly available wedding-band regional price tables and category-pricing benchmarks). Weighting differs by use case — wedding engagements are 100% industry-anchored (aspirational spend does not track regional income linearly), corporate engagements are 85% ONS GDHI (corporate budgets do), while pubs & bars multipliers are heavily damped toward uniform (local venue cost structures dominate). Observed city or region data always takes precedence; multipliers only fill otherwise-empty fallback slots.
Quality firewall and outlier governance
A single ingest function (ingest_idx_observations) enforces five gates on every incoming row: required-field presence, source whitelist, payment-type restriction (only artist fees permitted — ticket prices, licensing fees, equipment hire and door splits are rejected by database-level CHECK constraint), plausibility bounds (per musician per hour, defined per use case), and duplicate detection. Rejections are logged with reason and raw payload for audit. Anonymous contributions are subject to a database-level rate limit and are held in a pending-review queue until administrator action.
Ticketed-club engagements use a dedicated 4-archetype model grounded in Music Venue Trust survey data (avg ticket £11.56, avg occupancy 38.7%, avg capacity 316) and MU rate floors. The core formula — fee = ticket × capacity × occupancy × artist share ÷ acts on bill — is evaluated across four grassroots archetypes (club night, promoted show, semi-pro headliner, strong regional act) weighted by UK market frequency, producing a blended average of £296 per act. Public ticketing-platform data carries a 0.70× grassroots correction for platform selection bias. Regional variance is modelled via three tiers (London 1.15×, major cities 1.00×, rest of UK 0.85×). All ticket-derived rows enter in shadow mode pending calibration against real booking data.
Refresh cadence and provenance
Cells are rebuilt nightly at 05:00 UTC via a scheduled job that re-runs the full weighted aggregation. Industry rate cards refresh weekly (Monday 03:00 UTC); approved public submissions propagate daily (04:30 UTC). Snapshot sources (rate cards, profile rates) use ISO-week-bucketed reference identifiers, so weekly observations accumulate as a time series rather than overwriting prior values — enabling rate-drift analysis over time. Each published cell exposes its last_refreshed timestamp and its resident sample size.
Disclaimers and licence
The GigXchange Index is a historical observation of fees that have been charged, asked or budgeted in the UK live music market. It is not a recommended price, a regulated benchmark, nor financial advice. Fees in any individual engagement may legitimately fall outside any percentile shown.
Published free of charge under the Creative Commons Attribution 4.0 International licence. Derivative use is permitted with attribution to GigXchange Index, https://gigxchange.app/rates.
Frequently Asked Questions
Everything artists, venues and event planners ask about the GigXchange Index.
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