# Kalshi vs Polymarket Odds – Same Game, Both Prices (`rowfeed/kalshi-polymarket-odds-comparison`) Actor

The same game on Kalshi and Polymarket side by side: both teams' prices on each venue, the cheapest side, the price gap and the cross-venue arbitrage cost before fees. NFL, NBA, MLB, NHL.

- **URL**: https://apify.com/rowfeed/kalshi-polymarket-odds-comparison.md
- **Developed by:** [Rowfeed](https://apify.com/rowfeed) (community)
- **Categories:** Sports, Developer tools, AI
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.00 / 1,000 matched games

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

## Kalshi vs Polymarket Odds Comparison

Get the same sports game priced on both Kalshi and Polymarket, side by side, with the cheapest side, the
price gap and the cross-venue arbitrage cost already worked out. Built for sports traders, odds-screen
builders, betting-model developers and AI agents that poll this repeatedly. Every row is matched by real
team-code and date data pulled live from both venues at run time, not by guessing - an ambiguous or
unmatched game is dropped rather than force-fit.

- **One row per matched game** - both venues' bid/ask/mid for each team, which venue is cheaper for each
  side, the price gap, and whether buying the cheapest YES on both teams costs less than $1 before fees.
- **Real team matching, not string luck** - a static team table (city, nickname, Kalshi ticker code) keeps
  same-city pairs apart (Giants/Jets, Rams/Chargers, Lakers/Clippers, Yankees/Mets, Cubs/White Sox), and a
  game only matches when both team codes and the game date agree.
- **NFL, NBA, MLB, NHL**, filterable by minimum gap or arbitrage-only, with an optional audit view of every
  unmatched game and why it didn't match.

### Example row (from a live run, 2026-09-24)

```json
{
  "league": "NFL",
  "game": "Green Bay Packers vs Atlanta Falcons",
  "start_time": "2026-09-25T00:15:00+00:00",
  "team_a": "Green Bay Packers",
  "team_b": "Atlanta Falcons",
  "kalshi_yes_bid_a": 0.69,
  "kalshi_yes_ask_a": 0.70,
  "kalshi_mid_a": 0.695,
  "kalshi_yes_bid_b": 0.30,
  "kalshi_yes_ask_b": 0.31,
  "kalshi_mid_b": 0.305,
  "polymarket_price_a": 0.695,
  "polymarket_best_bid_a": 0.69,
  "polymarket_best_ask_a": 0.70,
  "polymarket_price_b": 0.305,
  "polymarket_best_bid_b": 0.30,
  "polymarket_best_ask_b": 0.31,
  "gap_a": 0.0,
  "gap_b": 0.0,
  "best_venue_a": "kalshi",
  "best_venue_b": "kalshi",
  "cheapest_ask_a": 0.70,
  "cheapest_ask_b": 0.31,
  "arb_cost": 1.01,
  "arb_opportunity": false,
  "arb_edge": -0.01,
  "thin_market": false,
  "kalshi_event_ticker": "KXNFLGAME-26SEP24ATLGB",
  "polymarket_event_slug": "nfl-atl-gb-2026-09-25",
  "kalshi_url": "https://kalshi.com/markets/kxnflgame",
  "polymarket_url": "https://polymarket.com/event/nfl-atl-gb-2026-09-25",
  "kalshi_volume_a": 1281182.14,
  "kalshi_volume_b": 628492.21,
  "polymarket_volume": 273090.01,
  "polymarket_volume_24h": 145713.48,
  "match_confidence": "ticker_code",
  "matched": true,
  "scraped_at": "2026-09-24T07:42:25+00:00"
}
```

This particular game is a good example of *why* the before-fees caveat below matters: both venues price it
almost identically (a 0-cent gap on both sides), so `arb_cost` lands at 1.01 - one cent *above* $1, not an
opportunity. Real, liquid games are usually efficiently priced across venues; the gaps worth screening for
show up more in thinner markets.

### Input

- **leagues** - `NFL`, `NBA`, `MLB`, `NHL` (default: all four). NBA games start appearing once Polymarket
  opens its season markets; until then NBA simply contributes zero rows.
- **minGap** - only keep a game if at least one side's price gap is at least this big (default `0`, keeps
  everything).
- **onlyArbitrage** - only keep games where `arb_opportunity` is true (default `false`). Can legitimately
  return zero rows.
- **includeUnmatched** - also emit an uncharged `matched: false` row for every Kalshi game that had no
  confident Polymarket match, with an `unmatched_reason` (default `false`).
- **maxGames** - cap on matched rows returned, soonest game first (1-500, default `100`).

### Output

One JSON row per matched game (see the example above), plus optional unmatched-audit rows when
`includeUnmatched` is on. Download the dataset as JSON, CSV, Excel or HTML from the Apify Console, or pull
it through the API.

### Pricing

Pay-per-event: **$2 per 1,000 matched games** (the `game` event, one per row in the main output) plus
**$0.001 per run start**. Unmatched-audit rows (`includeUnmatched`) are never charged.

### Before you trade on this

`arb_opportunity` and `arb_cost` are computed **before fees and slippage**: Kalshi charges a trading fee on
top of the quoted price, and Polymarket's quoted best bid/ask already has a spread that can move against you
between quote and fill. Treat this as a screen for where to look closer, not a guaranteed risk-free trade.

`thin_market` is `true` when the cheapest leg on either side has never traded on that venue (zero lifetime volume). An "arbitrage" on such a row is usually a stale or tiny quote, so check `kalshi_volume_a`/`_b` and `polymarket_volume` before acting. Filter on `thin_market: false` to see only edges that have real trading behind them.

Not affiliated with Kalshi or Polymarket.

# Actor input Schema

## `leagues` (type: `array`):

Leagues to compare, one row per game found on both venues. NBA games will start appearing once Polymarket opens its season markets; until then NBA simply contributes zero rows, not an error.

## `minGap` (type: `number`):

Only keep a game if at least one side's price gap (Polymarket price minus Kalshi price, either team) is at least this big, e.g. 0.03 for a 3-cent gap. 0 keeps every matched game.

## `onlyArbitrage` (type: `boolean`):

Keep only games where buying the cheapest YES on each side, across both venues, costs less than $1 before fees (arb\_opportunity = true). Can legitimately return zero rows - real, fee-free cross-venue arbitrage is rare.

## `includeUnmatched` (type: `boolean`):

Also emit an uncharged row (matched: false) for each Kalshi game that had no confident Polymarket match - either no candidate at all, or more than one candidate within the 36-hour match window (ambiguous). Useful for auditing match coverage.

## `maxGames` (type: `integer`):

Keep this many matched game rows, soonest start\_time first. Each row is one charged "game" event.

## Actor input object example

```json
{
  "leagues": [
    "NFL",
    "NBA",
    "MLB",
    "NHL"
  ],
  "minGap": 0,
  "onlyArbitrage": false,
  "includeUnmatched": false,
  "maxGames": 100
}
```

# Actor output Schema

## `results` (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("rowfeed/kalshi-polymarket-odds-comparison").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("rowfeed/kalshi-polymarket-odds-comparison").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 rowfeed/kalshi-polymarket-odds-comparison --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,rowfeed/kalshi-polymarket-odds-comparison"
        }
    }
}
```

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/F7I5rOGGRilKH7hUk/builds/WVEht1XVeI8FrBrxw/openapi.json