# Football Odds Movement Tracker (`sleeze22/football-odds-movement-tracker`) Actor Track pre-match football odds, compare snapshots, and detect synchronized steam moves across bookmakers. No external odds API key required. - **URL**: https://apify.com/sleeze22/football-odds-movement-tracker.md - **Developed by:** [zSleezeh](https://apify.com/sleeze22) (community) - **Categories:** Developer tools, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. Actors are written with capital "A". ## 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. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. 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). # README Monitor pre-match football odds, identify synchronized market moves, and build timestamped line-movement datasets without bringing an external odds API key. Football Odds Movement & Steam Tracker compares every successful run with the previous snapshot and returns clean, analysis-ready records. Schedule it on Apify to turn changing prices into a useful historical feed for dashboards, alerts, research, and models. ### Why use this Actor? - **See what changed:** compare current and previous decimal odds for every normalized selection. - **Detect coordinated moves:** flag steam when no-vig probability shifts in the same direction at two or more bookmakers. - **Reduce noise:** return only new or meaningful movements by default. - **Build history automatically:** schedule recurring runs and export results as JSON, CSV, or Excel. - **Start without an odds API key:** requests use your Apify proxy configuration. - **Protect valid state:** failed or empty source responses never overwrite the last complete snapshot. ### Popular use cases - Line-movement and market-monitoring dashboards - Telegram, Discord, Slack, or email alert workflows - Pre-match odds research and closing-line analysis - Historical datasets for football models and backtests - Data pipelines through the Apify API, webhooks, Make, or Zapier ### Supported coverage The initial release monitors pre-match events from: - Serie A - Premier League - La Liga - Bundesliga - Ligue 1 - UEFA Champions League It normalizes these markets when available from the source: - Match result (`1X2`) - Goals totals (`Over/Under`) - Both teams to score (`BTTS`) Coverage varies by event and bookmaker. Unsupported or malformed markets are skipped rather than returned as unreliable data. ### Movement labels | Label | Meaning | | --- | --- | | `new` | The selection was not present in the previous successful snapshot. | | `rising` | Decimal odds increased beyond your configured threshold. | | `falling` | Decimal odds decreased beyond your configured threshold. | | `steam` | No-vig probability moved in the same direction at two or more bookmakers. | | `stable` | Movement remained below the threshold; returned only when requested. | Steam is an observable pricing signal. It is not proof of betting volume, informed money, or future results. ### Input example ```json { "competitions": ["serie_a", "premier_league", "champions_league"], "daysAhead": 7, "movementThresholdPct": 2, "steamThresholdPct": 3, "includeStable": false, "maxEvents": 50, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ```` #### Input options | Field | Default | Description | | --- | --- | --- | | `competitions` | All supported | Competitions to monitor. | | `daysAhead` | `7` | Event window from 1 to 14 days. | | `movementThresholdPct` | `2` | Minimum decimal-odds percentage change to emit. | | `steamThresholdPct` | `3` | Minimum no-vig probability-point move for a steam candidate. | | `includeStable` | `false` | Include records below the movement threshold. | | `maxEvents` | `100` | Maximum events processed in one run. | | `proxyConfiguration` | Residential | Apify proxy used to access the public source. | ### Output example ```json { "eventKey": "sofascore:12345678", "competition": "Serie A", "homeTeam": "Inter", "awayTeam": "Milan", "kickoffAt": "2026-09-20T18:45:00.000Z", "bookmaker": "Example Bookmaker", "market": "1x2", "line": null, "selection": "home", "odds": 1.91, "previousOdds": 2.02, "oddsChangePct": -5.45, "noVigChangePct": 3.18, "classification": "steam", "scrapedAt": "2026-09-20T10:15:00.000Z" } ``` Every run writes matching records to the default Apify dataset, ready for API access and standard exports. ### Recommended setup 1. Select the competitions you need. 2. Keep the residential Apify proxy enabled. 3. Run once to create the initial snapshot; these records are labeled `new`. 4. Schedule the Actor every 15 minutes for useful pre-match history. 5. Connect a webhook or integration if you need alerts. ### Reliability and costs - Residential proxy traffic is billed by Apify and can be the main run cost. - Public source structures and availability can change. - A run fails clearly when the source is blocked, empty, or structurally invalid. - The previous valid snapshot is saved only after a complete successful fetch. - Start with a small `maxEvents` value to measure your real proxy and compute costs. ### Responsible use This Actor provides informational market data only. It does not place bets, guarantee profit, or provide betting advice. Users are responsible for applicable laws, gambling-age requirements, source terms, and data-redistribution rights. This is an unofficial independent tool and is not affiliated with, sponsored by, or endorsed by SofaScore, any bookmaker, football competition, or data provider. ### Support If a competition stops returning data or a market format changes, open an issue from the Actor page and include the run ID and affected competition. Do not include API tokens or private credentials. # Actor input Schema ## `competitions` (type: `array`): Football competitions to monitor. ## `daysAhead` (type: `integer`): Collect events starting within this many days. ## `movementThresholdPct` (type: `number`): Minimum decimal-odds percentage change to emit. ## `steamThresholdPct` (type: `number`): Minimum no-vig probability-point movement for a steam candidate. ## `includeStable` (type: `boolean`): Include records whose movement is below the configured threshold. ## `maxEvents` (type: `integer`): Maximum number of football events processed per run. ## `proxyConfiguration` (type: `object`): Apify residential proxy is recommended. ## Actor input object example ```json { "competitions": [ "serie_a", "premier_league", "la_liga", "bundesliga", "ligue_1", "champions_league" ], "daysAhead": 7, "movementThresholdPct": 2, "steamThresholdPct": 3, "includeStable": false, "maxEvents": 100, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("sleeze22/football-odds-movement-tracker").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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("sleeze22/football-odds-movement-tracker").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).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 sleeze22/football-odds-movement-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=sleeze22/football-odds-movement-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Football Odds Movement Tracker", "description": "Track pre-match football odds, compare snapshots, and detect synchronized steam moves across bookmakers. No external odds API key required.", "version": "0.1", "x-build-id": "cDRjfzmnh1EYNcXq9" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/sleeze22~football-odds-movement-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-sleeze22-football-odds-movement-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/sleeze22~football-odds-movement-tracker/runs": { "post": { "operationId": "runs-sync-sleeze22-football-odds-movement-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/sleeze22~football-odds-movement-tracker/run-sync": { "post": { "operationId": "run-sync-sleeze22-football-odds-movement-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "competitions": { "title": "Competitions", "type": "array", "description": "Football competitions to monitor.", "items": { "type": "string", "enum": [ "serie_a", "premier_league", "la_liga", "bundesliga", "ligue_1", "champions_league" ] }, "default": [ "serie_a", "premier_league", "la_liga", "bundesliga", "ligue_1", "champions_league" ] }, "daysAhead": { "title": "Days ahead", "minimum": 1, "maximum": 14, "type": "integer", "description": "Collect events starting within this many days.", "default": 7 }, "movementThresholdPct": { "title": "Movement threshold (%)", "minimum": 0, "maximum": 100, "type": "number", "description": "Minimum decimal-odds percentage change to emit.", "default": 2 }, "steamThresholdPct": { "title": "Steam threshold (percentage points)", "minimum": 0, "maximum": 100, "type": "number", "description": "Minimum no-vig probability-point movement for a steam candidate.", "default": 3 }, "includeStable": { "title": "Include stable odds", "type": "boolean", "description": "Include records whose movement is below the configured threshold.", "default": false }, "maxEvents": { "title": "Maximum events", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of football events processed per run.", "default": 100 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Apify residential proxy is recommended.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```