> For the complete documentation index, see [llms.txt](https://docs.sportmonks.com/v3/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sportmonks.com/v3/sportmonks-ai-docs/example-builds.md).

# Example Builds

Concrete things you can build with AI and Sportmonks data. Each of these is achievable in an afternoon using any AI coding tool with the MCP server or a context block.

### Live score dashboard

A real-time dashboard that polls for in-play matches and displays scores, match state, and elapsed minutes.

**What you need:**

* `GET /livescores/inplay?include=participants;scores;state;periods`
* A polling loop (every 30-60 seconds)
* A simple UI framework (React, Vue, or plain HTML)

**Ask your AI:**

> *Build a live score dashboard that polls the Sportmonks inplay livescores endpoint every 30 seconds and renders a card for each match showing home team, away team, score, and current minute. Use React and Tailwind.*

### Pre-match briefing generator

Paste a fixture ID and get a formatted pre-match briefing with team info, recent form, and head-to-head history.

**What you need:**

* `GET /fixtures/{id}?include=participants`
* `GET /fixtures/head-to-head/{team1}/{team2}?per_page=5&order=desc`
* `GET /standings/live/leagues/{league_id}?include=participant;details`

**Ask your AI:**

> *Build a pre-match briefing generator. Given a fixture ID, fetch the two teams, their last 5 head-to-head results, and their current league positions. Format everything as a clean markdown report.*

### Odds comparison table

A side-by-side odds comparison across bookmakers for a given fixture and market.

**What you need:**

* `GET /odds/pre-match/fixtures/{fixture_id}?include=bookmaker;market`
* Filter by market (e.g. 1X2) and sort by bookmaker

**Ask your AI:**

> *Build an odds comparison function that takes a fixture ID and returns a table showing the home win, draw, and away win odds from every available bookmaker, sorted by best home win odds.*

### Transfer tracker

A feed of the latest transfer activity across subscribed leagues, updated on demand.

**What you need:**

* `GET /transfers/latest?include=player;fromTeam;toTeam`
* Optional date range filtering

**Ask your AI:**

> *Build a transfer tracker that fetches the 20 most recent transfers and displays them as a feed with player name, from club, to club, and transfer date. Add a filter for specific leagues.*

### League season explorer

A tool that lets users pick a league, browse its historical seasons, and jump to standings or topscorers for any of them.

**What you need:**

* `GET /leagues/search/{query}`
* `GET /leagues/{id}?include=seasons`
* `GET /standings/seasons/{season_id}?include=participant;details`
* `GET /topscorers/seasons/{season_id}?filters=seasonTopscorerTypes:208`

**Ask your AI:**

> *Build a league explorer. The user types a league name, picks from the search results, then sees a list of all historical seasons. Clicking a season shows the final standings table and top 10 scorers.*

### Tips for building with AI

* **Start with search** - ask the AI to use the search endpoint to find IDs before writing the rest of the code. It avoids hardcoded IDs that break.
* **Use the context block** - paste the full context at the start of your session so the AI knows the endpoint shapes upfront.
* **Ask for real data first** - before writing UI code, ask the AI to fetch a live sample response and print it. It avoids building against the wrong shape.
* **Install the MCP server** - if you're in Claude or Cursor, the AI can fetch real data mid-conversation to test its own code as it writes it.


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