Greyhound Results Archive — Historical Data and Past Races

In 2026, greyhound racing in the United Kingdom reaches its centenary. A hundred years have passed since the first official race took place at Belle Vue Stadium in Manchester on 24 July 1926, when 1,700 spectators watched a greyhound named Mistley cross the line first. Between that evening and this morning’s opening BAGS fixture, hundreds of thousands of races have been run, recorded and — in varying degrees of completeness — archived. The results archive is where all of that data lives, and for anyone serious about form analysis, historical research or simply understanding how the modern sport connects to its past, it is an indispensable resource.

This page is about the archive itself: what it contains, how to navigate it, what long-term trends it reveals, and how to use historical data for practical purposes like handicapping and form study. The archive is not a museum piece. It is a working dataset — every race on record, available for interrogation by anyone willing to dig into the numbers. The patterns inside it stretch back decades, and the most valuable of them are the ones that still hold true today.

Whether you are looking up a specific dog’s career record, tracking the evolution of race times at a particular track, or trying to understand how the sport has changed since the post-war boom, the archive is where you start. What follows is a practical guide to making the most of it.

What the Archive Contains

The greyhound results archive is, at its most basic level, a record of every race result from every GBGB-licensed meeting. Each entry includes the essential data points: date, track, race number, distance, grade, the finishing order of all runners with their trap numbers and names, the winning time, the starting price for each runner, and the forecast and tricast dividends. For more recent years, additional data fields — sectional times, race comments, going descriptions, weight records — are included with increasing consistency, though the depth of supplementary data diminishes the further back you go.

The archive’s coverage is not uniform across all periods. Records from the modern era — roughly the past 15 to 20 years — are comprehensive and digitally searchable. Data from earlier decades exists but may be incomplete, particularly for smaller meetings and lower-grade races that were not always recorded with the same rigour as headline events. The very earliest years of the sport, from 1926 through to the post-war expansion, are documented primarily through historical records, specialist publications and the archives of individual tracks rather than any single centralised database.

For practical form analysis, the most relevant portion of the archive is the recent past — the last one to five years. This is the window in which the dogs currently racing have their form lines, the tracks have their current configurations, and the grading system is operating under the same rules. Anything older than five years is primarily useful for trend analysis, historical research, and understanding how the competitive landscape has evolved over time.

One often-overlooked category of archived data is open race results. While graded races form the bulk of the archive, open races — category events, invitation races, and championship competitions — are also recorded and are disproportionately useful for assessing the very top tier of greyhound talent. A dog’s performance in an open race at Nottingham or a category event at Hove tells you more about its absolute ability than a dozen wins in graded company, because the competition in open races is drawn from the best dogs in the country rather than from a localised grading pool.

The archive also preserves data from tracks that no longer exist. Wimbledon, which closed in 2017, Walthamstow (2008), Catford (2003) and dozens of others are still represented in the historical record. These defunct-track entries are not just nostalgia — they provide form lines for dogs that raced at those venues and later transferred to tracks that are still operational, creating a continuous data chain even across venue closures.

Navigating Results by Date and Track

The simplest way to navigate the archive is by date. Pick a date, and you get every race run on that day at every track that was operating. From there, you can drill down to a specific meeting, a specific race, or a specific dog. The date-based approach is useful when you know roughly when something happened — a notable performance, a course record, a specific dog’s debut — but cannot remember the exact details.

Navigating by track is the other primary axis. Select a venue, and the archive shows you every meeting that has taken place there, in reverse chronological order. This is the most efficient way to build a venue-specific form dataset: filter by track, set a date range, and extract every result within that window. If you are studying Romford’s last three months of A-grade racing, the track filter gives you exactly that — no noise from other venues, no irrelevant grades.

Combining the two axes — date and track — gives you a single meeting’s complete card. This is where the archive is most immediately useful. A full card from last Tuesday at Monmore, with every race result, every SP, every time and every finishing margin, is a snapshot of one evening’s competitive reality. Stack a dozen of those snapshots on top of each other, and you have a dataset that reveals patterns: which traps are winning, which trainers are performing, which grades are the most competitive, and how the track’s surface conditions are affecting times from week to week.

Beyond date and track, many archive providers also allow searches by dog name, trainer, or race grade. The dog-name search is particularly valuable for building a career profile: every start a dog has ever made, at every track, in every grade, with every finishing position and time recorded. For a dog with 30 or 40 career starts, that profile tells a complete story — from its debut trial through its peak form and into its later runs, with every win, every setback and every regrading visible in the data.

One practical tip: when using the archive for form analysis, always work backwards from the most recent result. Start with today’s card, identify the runners you want to research, then follow their form lines back through the archive. This keeps the analysis focused and prevents the common trap of getting lost in historical data that is interesting but not relevant to the selections you are trying to make.

Trainer searches are another underused feature. By pulling up a trainer’s complete results history at a specific track, you can quickly establish their venue-specific strike rate over any time period — last month, last quarter, last year. That figure is one of the most reliable predictive signals in form analysis, and the archive is the only place where it exists in full. No other data source gives you the depth needed to separate a genuinely in-form trainer from one who simply won a couple of races last week.

Long-Term Form Trends in Archived Data

The archive does not just record individual results. Over time, it reveals structural trends in the sport — shifts in the competitive landscape that no single race result can show you, but that become unmistakable when you look at the data in aggregate over years rather than weeks.

One of the most significant long-term trends visible in the archive is the contraction of the racing population. New greyhound registrations fell to 5,899 in 2023, a decline of 19% compared with 2019 levels. That shrinking pool has practical implications for form analysis: with fewer dogs in the system, the depth of competition at each grade level thins out, which can distort the meaning of results. A dog winning an A3 race in 2026 may be beating a weaker field than a dog that won the same grade at the same track five years ago, simply because there are fewer dogs available to fill the higher grades.

Safety metrics show a contrasting trajectory. The archive, when cross-referenced with GBGB’s published welfare data, shows a clear downward trend in on-track incident rates. The injury rate for 2024 stood at 1.07% — meaning 3,809 injuries across 355,682 individual race runs — the lowest figure in GBGB’s recording history. That trend matters for results analysis because lower injury rates mean fewer non-completions, fewer void races, and more consistent datasets. The archive from ten years ago contains a higher proportion of incomplete or disrupted races than the archive from last year, which makes the more recent data slightly more reliable for systematic analysis.

Race times across the archive also show gradual evolution, though the picture is complicated by surface changes, track renovations, and shifts in the racing programme. Some tracks have become measurably faster over the past decade — Towcester, following its redevelopment, being a notable example — while others have maintained relatively stable time bands. Comparing a dog’s recent times with the long-term track averages available in the archive gives you a sense of whether its performances are ordinary or exceptional in historical context.

The trend in race scheduling is another pattern the archive captures. The explosion of BAGS meetings over the past decade — from 46 per week in 2018 to 74 by 2024 — is visible in the data as a simple increase in the volume of low-to-mid-grade results. If you are working with archived data from five years ago, there are fewer races per week to analyse. If you are working with recent data, there are almost twice as many. That does not make the older data less useful, but it changes the statistical significance of any pattern you identify: a trend observed across 500 recent races carries more weight than the same trend observed across 300 races from an earlier period.

Historical Milestones in UK Greyhound Racing

The archive is not only an analytical tool. It is also a record of the sport’s most significant moments — the races, the dogs and the events that defined eras and reshaped the competitive landscape. Understanding these milestones adds depth to the raw data and helps explain why certain tracks, distances and race formats exist in their current form.

The founding moment is well-documented. On 24 July 1926, Belle Vue Stadium in Manchester hosted the first official greyhound race in the United Kingdom. The crowd was modest — 1,700 spectators — and the winning greyhound, Mistley, ran over a course that bore little resemblance to modern racing circuits. But the event triggered an explosion of interest. Within two years, dozens of tracks had opened across the country, and by the 1930s, greyhound racing was one of the most popular spectator sports in Britain, regularly drawing larger crowds than football matches.

The post-war golden age — roughly the late 1940s through to the 1960s — represents the period of maximum infrastructure. More than 60 licensed tracks were operating simultaneously, and annual attendance figures ran into the tens of millions. The archive from this era is patchy by modern standards, but what survives shows a sport with extraordinary depth: fields of consistently high quality, fierce competition between rival tracks, and a betting market that attracted money from every level of society.

The English Greyhound Derby remains the sport’s flagship event, and its history is woven through the archive. The current format runs over 500 metres at Towcester, offers £175,000 to the winner, and attracts around 180 entries that are whittled down through six rounds of competition. The Derby’s roll of honour is a useful reference point for understanding the standard of the very best dogs across different eras, and the archived results from each year’s competition provide a benchmark against which all other performances can be measured.

The contraction era — from the 1970s onwards — saw tracks close at a steady rate as land values increased, attendance declined and the sport’s cultural position shifted. White City closed in 1984, Hackney in 1995, Catford in 2003, Walthamstow in 2008, Wimbledon in 2017. Each closure is marked in the archive by a final meeting, a last set of results, and then silence. The archived data from these tracks is the only surviving competitive record from venues that no longer exist.

The most recent milestone of note came on 7 March 2026, when Dunstall Park in Wolverhampton hosted the first-ever combined horse racing and greyhound racing fixture in the UK — a centenary event that brought two sports together on a single card for the first time. Whether this becomes a regular feature or remains a one-off, the results from that day are now part of the archive, and they represent a new kind of entry in a dataset that has been growing continuously since 1926.

As GBGB Chairman Sir Philip Davies noted during this year’s centenary celebrations, the sport is marking a hundred years since racing first took place at Belle Vue. That century of data, preserved in the archive, is both a historical record and a working tool — and the milestones within it are the markers that give the data its narrative structure.

How Archived Results Support Handicapping

Handicapping — the process of systematically evaluating each runner’s chances in a race — is the core skill of form-based punting, and the archive is the foundation it rests on. Every element of the handicapping process, from speed rating to class assessment to course suitability, relies on archived results to provide the raw data.

Speed ratings are the most common handicapping tool derived from the archive. The principle is straightforward: take a dog’s recent finishing times, adjust for going, distance and track standard, and produce a normalised figure that represents its expected performance level. A dog with a speed rating of 95 is expected to perform at a certain level regardless of which track it runs at, because the rating has already adjusted for venue-specific factors. Building accurate speed ratings requires a deep archive of results at each track, so that the track standard — the baseline time for a given distance and grade — can be calculated with confidence.

Class ratings work differently. Instead of using times, they evaluate a dog’s finishing positions relative to the grade of competition. A dog that consistently finishes in the first three in A2 company is assigned a higher class rating than a dog that wins regularly in A6 but struggles when stepped up. The archive provides the historical race-by-race data needed to build class profiles for every runner, and the trends within those profiles — improving, declining, or holding steady — inform the handicapping assessment.

Course-specific handicapping is where the archive earns its keep most visibly. A dog that has run ten times at Romford, with all ten results archived, has a course profile that is directly comparable with other dogs that have run at the same venue. The handicapper can extract not just finishing positions but times, margins, trap draws, and race dynamics from every start at that track. That depth of information is what separates serious handicapping from guesswork: it tells you not just what a dog has done, but what it has done under specific conditions at a specific venue, which is far more predictive.

The archive also supports negative handicapping — the process of identifying dogs to oppose. If the data shows that a dog has never run a competitive time at a particular track, or that it consistently fades in the final 100 metres at tracks with long home straights, those patterns are reasons to exclude it from selections regardless of how good its recent form looks in isolation. The archive gives you the evidence to make those calls with confidence rather than intuition.

Data Sources and Archival Standards

The quality of the archive depends on the quality of the data that goes into it. GBGB, as the regulatory body for licensed greyhound racing in the UK, is the primary originator of official results data. Every race run at a licensed track is recorded by the track’s racing office, reviewed by the stewards, and transmitted to GBGB for inclusion in the central record. That process — capture, review, confirm — is the archival standard that underpins everything discussed on this page.

The scale of the data being generated is considerable. With approximately 500 licensed trainers, 15,000 registered owners, and around 6,000 new greyhound registrations per year, the industry produces a continuous stream of competitive data. Each dog generates a form line with every start. Each trainer generates a results record with every entry. Each track generates a meeting record with every fixture. Multiply that across 74 meetings per week, 52 weeks per year, and the archive grows by tens of thousands of result entries annually.

Third-party results providers add a distribution layer on top of the official GBGB data. Websites, apps and data services repackage the raw results into searchable interfaces, adding analytical features like speed ratings, form summaries and statistical breakdowns that the official data does not include. The best of these providers maintain high accuracy because they pull directly from the GBGB feed. Lower-quality providers may introduce errors through manual data entry or delayed updates. If you are building a form database from archived results, use the most authoritative source available and cross-check any figures that look anomalous.

Historical archival standards are less consistent than modern ones. Results from the 1960s and 1970s may be available through specialist publications, club archives, or digitisation projects, but the data fields are often limited — you might get finishing order and time, but not SP, not the going, and not the sectional data that modern archives include as standard. For form analysis, this limits the utility of very old results, though the finishing positions and times alone are sufficient for basic historical comparisons.

The archive, ultimately, is only as useful as your ability to access and interrogate it. A century of greyhound racing data — every race on record, from Mistley’s win at Belle Vue to this morning’s first result at Sunderland — exists in various states of completeness across multiple sources. The task for any serious analyst is to identify the portions of the archive that are relevant to their questions, extract the data systematically, and apply it with the rigour that a hundred years of competition deserves.