Greyhound Favourite Win Rate UK — What the National Data Shows

The favourite wins roughly one in three graded greyhound races in the UK. The precise figure from 2024 data is 35.67 percent — meaning that across all eighteen GBGB-licensed tracks, the dog sent off at the shortest starting price won just over a third of the time. The other two-thirds of the time, something else happened: a longer-priced runner won, the form book got it wrong, or an incident in running overturned the expected outcome.

That headline number is the single most important statistic for anyone betting on greyhound racing. It sets the floor for what you should expect from backing favourites and the ceiling for how much confidence you should place in the market’s top selection. But the national average hides significant variation between tracks, between grades, and between distances — and those variations are where the real analytical value lies.

The National Average — 35.67% in 2024

The 35.67 percent figure is calculated from starting-price (SP) data across all graded races at all licensed tracks during the 2024 calendar year. The “favourite” is defined as the dog with the lowest SP at the off — the one the betting market collectively assessed as most likely to win. In the event of joint favourites, the standard methodology splits the credit between the co-favourites.

A 35.67 percent strike rate means the favourite fails nearly two times out of three. That is not a criticism of the market — it is a structural feature of six-runner racing. In a perfectly efficient market with equally matched fields, each dog would win one-sixth of the time (16.67 percent), and the favourite would still lose five times out of six. The fact that the favourite wins more than twice the baseline rate shows that the market does a reasonable job of identifying the strongest runner — it just cannot do so reliably enough to make blind favourite-backing profitable.

The profitability question matters. Backing every favourite at SP across a full season produces a negative return in virtually every historical dataset. The bookmaker’s margin — the overround built into every six-dog race — ensures that the average SP on favourites is lower than the true probability of winning. A dog with a 35 percent chance of winning should, in a fair market, be priced at roughly 13/8. In practice, it will typically be offered at 6/4 or shorter, which means the bettor is accepting worse value than the probability warrants. That is how bookmakers make money, and it is the fundamental reason why backing favourites without further analysis is a losing strategy.

The data comes from OLBG, which aggregates track-level favourite performance statistics from across the UK licensed network. It is one of the more comprehensive publicly available datasets for this metric and is updated annually.

Track-by-Track Variation

The 35.67 percent national average is just that — an average. Individual tracks deviate substantially. At the low end, Kinsley produced a favourite win rate of 31.60 percent in 2024 — more than four percentage points below the national figure. At the high end, The Valley in South Wales recorded approximately 42 percent — six points above the average. That range of more than ten percentage points between the least and most favourite-friendly tracks represents a significant difference in how predictable racing is at each venue.

What drives the variation? Several factors interact. Track geometry is one: tighter tracks with shorter run-ups produce more first-bend congestion, which increases the chance of the favourite encountering trouble. The grading system at each track is another — a racing manager who grades tightly (ensuring very even fields) will suppress the favourite win rate, because the gaps between dogs are smaller. A racing manager who allows wider grade bands will produce more one-sided races, pushing the favourite rate higher.

Field composition plays a role too. Tracks that attract a higher proportion of visiting dogs from other venues will have fields where the form data is less reliable, because cross-track comparison is inherently harder than within-track comparison. That uncertainty suppresses the market’s ability to identify the correct favourite, which in turn lowers the favourite strike rate.

The hare type and trap bias profile also contribute. At Towcester, where Trap 1 shows a 20 percent win rate — the highest in the country — favourites drawn in Trap 1 carry a double advantage: market support and geometric benefit. At Harlow, where Trap 6 wins at 21 percent, the advantage flows differently and may not align with market favouritism in the same way. These structural quirks mean that a favourite at one track is not the same proposition as a favourite at another, even if the SP is identical.

What This Means for Bettors

The practical question is not “should I back favourites?” but “when should I back favourites and when should I oppose them?” The national data provides the framework; the track-specific data provides the edge.

Back favourites selectively. The 35.67 percent national rate means that roughly one in three favourites wins, but the rate varies by grade, distance and race type. Favourites tend to perform better in lower grades, where the ability gap between the best and worst dog in the field is wider. In A-grade and open races, where the field is more closely matched, the favourite rate drops because the competition is stiffer. Identifying the races where the favourite has the widest margin over the field — rather than backing every favourite indiscriminately — is the key to positive returns.

Oppose favourites with a reason. Blindly opposing the favourite in every race is as unprofitable as blindly backing it — you are simply losing on the other side of the same equation. The value in opposing favourites comes from identifying specific situations where the market has overestimated the favourite’s chance: a front-runner drawn in a wide trap at a track with inside-hare dynamics, a dog stepping up in grade for the first time, or a favourite with a history of trouble in running at a particular bend. Each of these scenarios reduces the favourite’s true probability below the market’s assessment, creating value on the other side.

Track-specific favourite data is more actionable than the national average. If Sunderland’s favourite win rate runs at, say, 34 percent — slightly below the national average — that tells you the track’s grading produces competitive fields and that favourites are marginally less reliable here than elsewhere. If it runs at 38 percent, the opposite is true. Building a local dataset of favourite performance by grade and distance at the tracks you follow is the most direct path to identifying where the market consistently over- or underprices the top selection.

A responsible caveat: no statistical edge in greyhound betting is large enough to guarantee profit, and the bookmaker’s margin ensures that the house wins in the long run across the entire market. The favourite win rate is a tool for making better decisions, not a formula for free money. Use it alongside form, going, trap draw and pace analysis — and always within the boundaries of a session budget you have set in advance.