# NHL Presidents' Trophy Odds from Simulated Seasons

**Use case:** 

Estimates each NHL team's chance of finishing with the most points in the league and winning the Presidents' Trophy, by simulating the regular season 20,000 times with home ice, overtime and the loser point built in. The same run returns projected points and division, wild card and playoff probabilities, and the Presidents' Trophy column sums to one across all 32 teams.

## Input

```json
{
  "iterations": 20000,
  "regressionGames": 25,
  "pythagoreanWeight": 0.6,
  "homeIceAdvantage": 0.12,
  "strengthUncertainty": 0.1,
  "overtimeProbability": 0.23,
  "overtimeDamping": 0.5,
  "priorCarryover": 0.6,
  "minGamesPlayedForValue": 10,
  "includeDivisionMarkets": false,
  "edgeThreshold": 0.05,
  "bankroll": 1000,
  "maxPerPositionPct": 0.02,
  "maxTotalExposurePct": 0.06,
  "marketProbabilities": []
}
```

## Output

```json
{
  "division": {
    "label": "Division"
  },
  "team": {
    "label": "Team"
  },
  "projectedPoints": {
    "label": "Projected points"
  },
  "fairDivisionProbability": {
    "label": "Division %"
  },
  "fairWildCardProbability": {
    "label": "Wild card %"
  },
  "fairPlayoffProbability": {
    "label": "Playoff %"
  },
  "fairPresidentsTrophyProbability": {
    "label": "Presidents' Trophy %"
  }
}
```

## About this Actor

This example demonstrates how to use [NHL Playoff Odds API — Monte Carlo Simulator & Value Bets](https://apify.com/commodus67/nhl-playoff-odds-monte-carlo.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/commodus67/nhl-playoff-odds-monte-carlo.md) to learn more, explore other use cases, and run it yourself.


## 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.
This Task's input is already configured above — use it as-is rather than inventing a new one.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/commodus67/nhl-playoff-odds-monte-carlo.md

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
