# Racing Model Edge Feed (`articulate_museum_m2g/racing-model-edge-feed`) Actor

One row per runner, per race, with a model win probability alongside the current market price and the de-vigged (bookmaker-margin-stripped) edge - a computed signal, not a tip or a guaranteed outcome.

- **URL**: https://apify.com/articulate_museum_m2g/racing-model-edge-feed.md
- **Developed by:** [kin m](https://apify.com/articulate_museum_m2g) (community)
- **Stats:** 2 total users, 1 monthly users, 31.3% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $1.40 / 1,000 pay-per-results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Racing Model Edge Feed

One row per runner, per race: a model's own win probability alongside the
current market price and the de-vigged market edge (bookmaker margin
stripped out via Shin's method). Computed numbers only — this is a data
feed, not a tip sheet, and it never claims a win rate.

### What you get

For every runner on every race card currently tracked, for the date you
ask for:

| Field | Meaning |
|---|---|
| `track`, `race_number`, `race_name`, `date` | Which race |
| `horse_name`, `tab_number` | Which runner |
| `win_probability` | The model's own win probability (0–1) |
| `decimal_odds` | Current fixed market price, if one is live right now |
| `market_prob_devigged` | Market-implied win probability with the bookmaker's margin removed — only set once every runner in the race has a recorded price |
| `edge_devigged` | `win_probability` minus `market_prob_devigged` — the model's edge over the de-vigged market |
| `tote_odds` | Current pari-mutuel pool price, if one is live right now |
| `code` | Thoroughbred or Harness |
| `as_of` | UTC timestamp this snapshot was computed at |

Any field that has no live price yet comes back `null` rather than a
guessed or stale value.

### Input

| Field | Required | Description |
|---|---|---|
| `date` | No | `YYYY-MM-DD`. Defaults to today. |

### Pricing

Pay-per-result: **$1.40 per 1,000 rows**, billed on exactly what's
delivered — a quiet day costs next to nothing, a full day of wide
coverage costs proportionally more. No subscription, no minimum.

### What this is not

- Not betting advice. Not a recommendation to back anything.
- Not a claimed win rate or guaranteed return — `win_probability` and
  `edge_devigged` are the model's own computed numbers, nothing more.
- Not affiliated with any racing body, bookmaker, or tote operator.

If you're using this to inform real wagering decisions, that's your own
judgment to make — gamble responsibly, and only with money you can
afford to lose.

# Actor input Schema

## `date` (type: `string`):

Leave blank for today's date.

## Actor input object example

```json
{}
```

# Actor output Schema

## `rows` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("articulate_museum_m2g/racing-model-edge-feed").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("articulate_museum_m2g/racing-model-edge-feed").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call articulate_museum_m2g/racing-model-edge-feed --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,articulate_museum_m2g/racing-model-edge-feed"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/YvR43l5YUr36FnZux/builds/77f49NtLs8cSIzIrZ/openapi.json