Buyer guide
Matched betting vs arbitrage vs value betting: the data each needs
Matched betting, arbitrage and value betting get lumped together, but each makes different demands of the data underneath. This guide separates them — what each strategy is, what data it actually needs, and which feed profile fits — so you buy for the one you are building.
8 min read
'Matched betting', 'arbitrage' and 'value betting' are often used loosely, sometimes interchangeably. For anyone buying odds data to build a product, they are three different things with three different data profiles — and buying for the wrong one is a costly mismatch.
This guide defines each plainly, sets out the data each needs, and maps them to the feed profile that fits. It is about the data, not advice on the strategies themselves.
Matched betting
Matched betting turns bookmaker promotions into low-risk value by pairing a bookmaker back bet against an exchange lay so the outcomes cancel, leaving the bonus. It is systematic, not speculative.
The data it needs is the most processed of the three: fixtures and selections matched across books, each bookmaker back price paired against the right exchange lay, rated, with qualifying figures, gated on liquidity and freshness — and bet365 included, because promotions there matter. In short, an oddsmatcher-ready matched feed.
- Matched back/exchange-lay pairs, rated, with qualifying figures.
- Exchange lay prices with liquidity, because the lay side is half the bet.
- bet365 included, for the promotions matched bettors use.
- All the matcher types (standard, each-way, extra-place, BOG, dutching, 2Up).
Arbitrage
Arbitrage exploits disagreements between prices — across bookmakers, or between a bookmaker and the exchange — so that covering every outcome yields a margin regardless of result. It lives on breadth and freshness.
Its data profile is different: it needs many books in one consistent shape (more comparable prices, more disagreements to find), exchange back/lay context, and freshness you can verify, delivered efficiently enough to poll constantly. It does not need the matched feed's rating and qualifying figures — it needs a wide, current, normalised board.
- Breadth: many books normalised to one schema.
- Exchange back/lay context alongside bookmaker odds.
- Verifiable freshness on a tight, timestamped cycle.
- Efficient delivery (ETag/304, gzip) for constant polling.
Value betting
Value betting is the most model-driven of the three: you estimate the 'true' probability of an outcome, and bet when a bookmaker's price implies worse odds than your estimate — betting on your edge over many bets rather than a locked-in margin.
Its data need is the broadest and rawest: a wide, current, normalised market picture — bookmaker prices and exchange reference prices — that feeds your own probability model. The analysis is yours; the feed's job is clean, broad, timestamped inputs. That is a trading-data profile.
- Broad, normalised market data as model inputs.
- Exchange reference prices as a probability anchor.
- Timestamps, so your model can window by freshness.
- A stable, documented schema your model can depend on.
How to tell which you are building
The quickest test is what your product hands the user. If it hands them a finished, rated opportunity to place, you are in matched-betting (or lay-based) territory and need the matched feed. If it hands them a set of bets that together lock a margin, you are in arbitrage and need breadth plus freshness. If it hands them a price your model thinks is mispriced, you are in value betting and need broad, raw market data.
Many products blend these, and one feed can serve more than one — but knowing which is primary tells you which data profile to buy for first.
At a glance
| Criterion | What to look for |
|---|---|
| Matched betting | A matched feed: rated back/exchange-lay pairs, gated, bet365, all matcher typesThe processing is the product; raw prices mean building the matcher. |
| Arbitrage | Breadth in one schema, exchange context, verifiable freshness, efficient pollingOpportunities multiply with comparable prices and currency, not with rating. |
| Value betting | Broad, normalised, timestamped market data as model inputsThe edge is your model; the feed supplies clean, broad inputs. |
Key takeaways
- Matched betting needs a processed matched feed (pairs, ratings, gating, bet365, all types).
- Arbitrage needs breadth, exchange context and verifiable freshness, delivered efficiently.
- Value betting needs broad, raw, timestamped market data to feed your own model.
- Identify what your product hands the user, and buy for that data profile first.
Where OddsRelay fits
OddsRelay covers all three profiles from one backend: the matched feed for matched betting (oddsmatcher-ready, bet365 included), the same broad normalised board with exchange context and verifiable freshness for arbitrage, and clean, timestamped market data as model inputs for value betting. You license the profile you need — and can add another through the same integration as your product grows.
Questions
Are matched betting and arbitrage the same thing?
No. Matched betting pairs a bookmaker back against an exchange lay to extract a promotion's value; arbitrage covers every outcome across prices so any result yields a margin. They need different data — a matched feed versus a wide, fresh, normalised board.
What data does value betting need that the others don't?
Value betting is model-driven, so it needs the broadest, rawest inputs — a wide, normalised, timestamped market picture with exchange reference prices — rather than finished opportunities. The edge lives in your model, not the feed.
Can one feed serve all three?
Yes — OddsRelay serves all three profiles from one backend: matched output for matched betting, breadth and freshness for arbitrage, and clean market inputs for value betting. You license the profile you need and can add another through the same integration.
Keep reading
Matched-betting data
Oddsmatcher-ready rows — back/lay paired, rated, gated, bet365 included.
Live-arbitrage feed
A wide, current market picture for fast cross-book detection — delivered efficiently.
Trading data
Market and exchange reference data for pricing, value detection and trading models.
Oddsmatcher-ready, explained
The difference between raw prices and a row you can render straight into an oddsmatcher.
Lay & exchange coverage
Why the exchange side matters as much as the bookmaker side — and what 'lay coverage' really means.
Near-real-time vs delayed
What odds freshness actually means, how to measure it, and how much you really need.
Choosing a provider
The eight criteria that actually separate odds feeds — coverage, freshness, schema, support and more.
Matched-betting platforms
The matched feed your oddsmatcher renders — back/lay paired, rated, bet365 included.
Arbitrage & trading tools
Cross-book and back/lay data current enough to act on — one feed, bet365 and exchange context included.
For matched betting
What separates a matched-betting feed worth building on — and where OddsRelay fits.
For arbitrage
What an arbitrage feed needs — breadth, freshness, exchange context — and where OddsRelay fits.
Odds & betting glossary
Put the criteria to the test.
Start a free trial of the full UK feed, bet365 included, and judge it against everything in this guide.