Open source · Built on the GreyhoundAPI
Six open projects that read the same feed you can. Predictions made before the off and scored against the result, questions answered from the real archive, and the models underneath — all of it public, all of it runnable on your own key.
The lab
Each one is a small, single-purpose tool built on the public API. Open the repo, or read how it works.
Reads a racecard and returns a ranked prediction with its reasoning — made before the off, then scored against the real result. Nothing cherry-picked.
Ask the archive a question in ordinary English. It picks its own endpoints, fetches the real races and answers with what it actually found — showing which tools it used.
An MCP server for the feed, so Claude, ChatGPT or Cursor can answer "what is Romford's trap-1 rate this year" straight from the live data — no client to write.
Describe a rule, run it across the whole archive, get honest out-of-sample numbers with the staking maths done properly. Built to make a bad idea obvious quickly.
Trap advantage modelled per track, distance and going, with confidence intervals — so you know when a bias is real and when it is 40 races of noise.
Turns a dog's race-by-race record into a readable paragraph a human would actually write — for previews, alerts and anywhere raw form is unreadable.
Why any of this is public
We sell a feed, not a tipping service. Publishing what can be built on it — including when it does not work — is a better argument than a marketing page.
Every prediction is stored before the race runs and scored afterwards. The accuracy figure includes the bad days, because a number you can only see after the fact is worthless.
Nothing here needs our infrastructure. Clone the repo, point it at your own key, and you get the same output — which is also the fastest way to see whether the feed suits you.
These are research tools. They are built to be inspected and argued with, not followed. No tips, no ratings, no service.
Two minutes
Install, point it at a race, and read the ranked preview in your terminal. The free sandbox key is enough to try it.
# install pip install greyhound-ai # rank tonight's card at Romford greyhound-ai preview --track romford --date today Romford 19:04 · A3 · 400m 1. Trap 1 Swift Cassandra 0.31 2. Trap 6 Coolavanny Pin 0.22 3. Trap 2 Newlawn Fifi 0.18 reasoning: T1 rails runner, +4.7pt draw edge at 400m…
What's next
An MCP server so any AI assistant can query the feed directly, a backtesting harness, a proper draw-bias model and a form summariser. Each one ships the same way — open repo, runnable on your key.
Read this bit. The lab is for research and education and is not betting advice. Accuracy figures are true out-of-sample — each race predicted before its result was known — but they are still small samples on a hard problem. Treat them as evidence the pipeline works, not as an edge.