# ESPN Sports Data Scraper (`parseforge/espn-sports-scraper`) Actor Extract live scores, standings, team rosters, and news from ESPN. Covers NFL, NBA, MLB, NHL, Premier League, La Liga, Serie A, Bundesliga, Ligue 1, and MLS. Get game schedules, odds, venue info, and team details. No proxy needed, pure API. - **URL**: https://apify.com/parseforge/espn-sports-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** News, Developer tools, Other - **Stats:** 13 total users, 1 monthly users, 100.0% runs succeeded, 2 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ![ParseForge Banner](https://github.com/ParseForge/apify-assets/blob/ad35ccc13ddd068b9d6cba33f323962e39aed5b2/banner.jpg?raw=true) ## ๐Ÿˆ ESPN Sports Scraper > ๐Ÿš€ **Collect sports data from ESPN in minutes.** Filter by sport, data type, and team. Export scores, standings, rosters, and stats. No coding, no ESPN account required. > ๐Ÿ•’ **Last updated:** 2026-04-23 ยท **๐Ÿ“Š 20+ fields** per record ยท **๐Ÿˆ Multi-sport** ยท **๐Ÿ“Š Scores + stats** ยท **๐Ÿšซ No auth** required
Pull structured records from ESPN Sports Data โ€” clean fields ready as CSV, JSON, JSONL, Excel, or XML for downstream pipelines.
##### Copy to your AI assistant Copy this block into ChatGPT, Claude, Cursor, or any LLM to start using this actor. ```` parseforge/espn-sports-scraper on Apify. Call: ApifyClient("TOKEN").actor("parseforge/espn-sports-scraper").call(run\_input={...}), then client.dataset(run\["defaultDatasetId"]).list\_items().items for results. Key inputs: maxItems (integer, default 10), sport (string, default "nfl"), dataType (string, default "scoreboard"), teamId (string). Full actor spec: fetch build via GET https://api.apify.com/v2/acts/parseforge~espn-sports-scraper (Bearer TOKEN). Get token: https://console.apify.com/account/integrations ```` The **ESPN Sports Scraper** collects sports data from ESPN, returning **20+ fields per record**: team names, scores, standings, player rosters, game schedules, and statistics across NFL, NBA, MLB, NHL, soccer, and more. Filter by sport, data type, and specific team. | ๐ŸŽฏ Target Audience | ๐Ÿ’ก Primary Use Cases | |---|---| | Sports analysts, fantasy players, betting researchers, sports media, data scientists | Scores tracking, standings analysis, roster monitoring, statistical research, fantasy sports data | --- ### ๐Ÿ“‹ What the ESPN Sports Scraper does - ๐Ÿˆ **Multi-sport.** NFL, NBA, MLB, NHL, soccer, and more. - ๐Ÿ“Š **Multiple data types.** Scores, standings, rosters, schedules, stats. - ๐Ÿข **Team filter.** Narrow to a specific team by ID. - ๐Ÿ“ฆ **Automatic pagination.** Follows pages until maxItems. > ๐Ÿ’ก **Why it matters:** tracking scores, standings, and stats across ESPN manually means visiting multiple pages per sport. This Actor exports structured sports data at scale for your dashboards, models, or content. --- ### ๐ŸŽฌ Full Demo _๐Ÿšง Coming soon._ --- ### โš™๏ธ Input
InputTypeDefaultBehavior
maxItemsinteger10Max records.
sportstring""Sport: nfl, nba, mlb, nhl, soccer.
dataTypestring""Data: scores, standings, rosters, schedule.
teamIdstring""Specific ESPN team ID.
**Example: NFL standings.** ```json { "sport": "nfl", "dataType": "standings", "maxItems": 32 } ```` **Example: NBA scores today.** ```json { "sport": "nba", "dataType": "scores", "maxItems": 20 } ``` *** ### ๐Ÿ“Š Output #### ๐Ÿงพ Schema | Field | Type | Example | |---|---|---| | ๐Ÿˆ sport | string | `"NFL"` | | ๐Ÿข teamName | string | `"Kansas City Chiefs"` | | ๐Ÿ“Š record | string | `"14-3"` | | ๐Ÿ’ฏ score | number | `27` | | ๐Ÿ“… gameDate | string | `"2026-01-12"` | | ๐Ÿ† standing | string | `"1st AFC West"` | | ๐Ÿ”— url | string | `"https://www.espn.com/..."` | | ๐Ÿ•’ scrapedAt | ISO 8601 | `"2026-04-16T00:00:00.000Z"` | #### ๐Ÿ“ฆ Sample records
๐Ÿˆ NFL team standing ```json { "sport": "NFL", "teamName": "Kansas City Chiefs", "record": "14-3", "standing": "1st AFC West", "url": "https://www.espn.com/nfl/team/_/name/kc/kansas-city-chiefs", "scrapedAt": "2026-04-16T00:00:00.000Z" } ```
๐Ÿ€ NBA game score ```json { "sport": "NBA", "teamName": "Boston Celtics", "score": 112, "opponentName": "LA Lakers", "opponentScore": 105, "gameDate": "2026-04-15", "url": "https://www.espn.com/nba/game/_/gameId/12345", "scrapedAt": "2026-04-16T00:00:05.000Z" } ```
โšพ MLB roster entry ```json { "sport": "MLB", "teamName": "New York Yankees", "playerName": "Aaron Judge", "position": "RF", "number": "99", "url": "https://www.espn.com/mlb/team/roster/_/name/nyy", "scrapedAt": "2026-04-16T00:00:10.000Z" } ```
*** ### โœจ Why choose this Actor | | Capability | |---|---| | ๐Ÿˆ | **Multi-sport.** NFL, NBA, MLB, NHL, soccer, and more. | | ๐Ÿ“Š | **Multiple data types.** Scores, standings, rosters, schedules. | | ๐Ÿข | **Team filter.** Narrow to specific teams. | | โšก | **Scalable.** Quick lookups to full league sweeps. | | ๐Ÿšซ | **No authentication.** Public ESPN data. | *** ### ๐Ÿ“ˆ How it compares to alternatives | Approach | Cost | Sports | Data types | Setup | |---|---|---|---|---| | **โญ ESPN Scraper** *(this Actor)* | $5 free credit | Multi-sport | Scores, standings, rosters | โšก 2 min | | Manual ESPN browsing | Free | One at a time | UI only | ๐Ÿ•’ Hours | | Paid sports APIs | $50-500/month | Multi-sport | Many | โณ Hours | *** ### ๐Ÿš€ How to use 1. ๐Ÿ“ **Sign up.** [Create a free account with $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) (takes 2 minutes). 2. ๐ŸŒ **Open the Actor.** Go to the ESPN Sports Scraper page. 3. ๐ŸŽฏ **Set input.** Pick a sport and data type. 4. ๐Ÿš€ **Run it.** Click **Start**. 5. ๐Ÿ“ฅ **Download.** Grab results in the **Dataset** tab. > โฑ๏ธ Total time: **3-5 minutes.** No coding required. *** ### ๐Ÿ’ผ Business use cases
#### ๐Ÿ“Š Sports Analytics - Track team performance over time - Build statistical models - Monitor roster changes - Analyze scheduling patterns #### ๐ŸŽฎ Fantasy & Betting - Pull player stats for projections - Track injury reports - Monitor standings changes - Build custom dashboards
#### ๐Ÿ“ฐ Sports Media - Generate automated game recaps - Track standings for content - Build real-time scoreboards - Monitor league-wide trends #### ๐Ÿข Sports Business - Track franchise valuations - Monitor attendance data - Analyze broadcast schedules - Build sports market research
*** *** ### ๐ŸŒŸ Beyond business use cases Data like this powers more than commercial workflows. The same structured records support research, education, civic projects, and personal initiatives.
#### ๐ŸŽ“ Research and academia - Empirical datasets for papers, thesis work, and coursework - Longitudinal studies tracking changes across snapshots - Reproducible research with cited, versioned data pulls - Classroom exercises on data analysis and ethical scraping #### ๐ŸŽจ Personal and creative - Side projects, portfolio demos, and indie app launches - Data visualizations, dashboards, and infographics - Content research for bloggers, YouTubers, and podcasters - Hobbyist collections and personal trackers
#### ๐Ÿค Non-profit and civic - Transparency reporting and accountability projects - Advocacy campaigns backed by public-interest data - Community-run databases for local issues - Investigative journalism on public records #### ๐Ÿงช Experimentation - Prototype AI and machine-learning pipelines with real data - Validate product-market hypotheses before engineering spend - Train small domain-specific models on niche corpora - Test dashboard concepts with live input
### ๐Ÿค– Ask an AI assistant about this scraper Open a ready-to-send prompt about this ParseForge actor in the AI of your choice: - ๐Ÿ’ฌ [**ChatGPT**](https://chat.openai.com/?q=How%20do%20I%20use%20the%20ESPN%20Sports%20Data%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) - ๐Ÿง  [**Claude**](https://claude.ai/new?q=How%20do%20I%20use%20the%20ESPN%20Sports%20Data%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) - ๐Ÿ” [**Perplexity**](https://perplexity.ai/search?q=How%20do%20I%20use%20the%20ESPN%20Sports%20Data%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) - ๐Ÿ…’ [**Copilot**](https://copilot.microsoft.com/?q=How%20do%20I%20use%20the%20ESPN%20Sports%20Data%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) ### โ“ Frequently Asked Questions
๐Ÿ’ณ Do I need a paid Apify plan to run this actor? No. You can start right now on the free Apify plan, which includes **$5 in free monthly credit**. That is enough to run this actor several times and explore the output before committing to anything. Paid plans unlock higher limits, more concurrent runs, and larger datasets. [Create a free Apify account here](https://console.apify.com/sign-up?fpr=vmoqkp) to get started.
๐Ÿšจ What happens if my run fails or returns no results? Failed runs are not charged. If the source site changes, proxies get rate-limited, or a specific input matches nothing, re-run the actor or open our [contact form](https://tally.so/r/BzdKgA) and we will investigate. You can also check the run log in the Apify console to see why the run stopped.
๐Ÿ“ How many items can I scrape per run? Free users are limited to **10 items per run** so you can preview the output and confirm the actor works for your use case. Paid users can raise maxItems up to **1,000,000** per run. [Upgrade here](https://console.apify.com/sign-up?fpr=vmoqkp) if you need full scale.
๐Ÿ•’ How fresh is the data? Every run fetches live data at the moment of execution. There is no cache or delay: the records you get reflect what the source returned at that moment. Schedule the actor to maintain a rolling snapshot of the data you need.
๐Ÿง‘โ€๐Ÿ’ป Can I call this actor from my own code? Yes. Apify exposes every actor as a REST endpoint and ships first-class SDKs for [Node.js](https://docs.apify.com/sdk/js) and [Python](https://docs.apify.com/sdk/python). You can start a run, read the dataset, and handle webhooks from your own app in a few lines. All you need is your Apify API token.
๐Ÿ“ค How do I export the data? Every Apify dataset can be downloaded in one click from the console as CSV, JSON, JSONL, Excel, HTML, XML, or RSS. You can also pull results programmatically via the [Apify API](https://docs.apify.com/api/v2) or stream them into BigQuery, S3, and other destinations through built-in integrations.
๐Ÿ“… Can I schedule the actor to run automatically? Yes. Use the Apify scheduler to run the actor on any cadence, from hourly to monthly. Results are saved to your dataset and can be delivered to webhooks, email, Slack, cloud storage, or automation tools such as Zapier and Make. ***
### ๐Ÿ”Œ Automating ESPN Sports Scraper - ๐ŸŸข **Node.js.** Install the apify-client NPM package. - ๐Ÿ **Python.** Use the apify-client PyPI package. - ๐Ÿ“š See the [Apify API documentation](https://docs.apify.com/api/v2) for full details. ### ๐Ÿ”Œ Integrate with any app - [**Make**](https://docs.apify.com/platform/integrations/make) - Automate workflows - [**Zapier**](https://docs.apify.com/platform/integrations/zapier) - Connect 5,000+ apps - [**Slack**](https://docs.apify.com/platform/integrations/slack) - Get score alerts - [**Airbyte**](https://docs.apify.com/platform/integrations/airbyte) - Data pipelines - [**GitHub**](https://docs.apify.com/platform/integrations/github) - Trigger from commits - [**Google Drive**](https://docs.apify.com/platform/integrations/drive) - Export to Sheets *** ### ๐Ÿ”— Recommended Actors - [**๐ŸŽฒ DraftKings Scraper**](https://apify.com/parseforge/draftkings-scraper) - Betting odds and DFS data - [**๐ŸŽซ StubHub Scraper**](https://apify.com/parseforge/stubhub-scraper) - Event ticket pricing - [**๐ŸŽ‰ Eventbrite Scraper**](https://apify.com/parseforge/eventbrite-scraper) - Event listings - [**๐Ÿ“ฑ Reddit Posts Scraper**](https://apify.com/parseforge/reddit-posts-scraper) - Fan discussions - [**๐Ÿฆ X.com Tweets Scraper**](https://apify.com/parseforge/x-com-scraper) - Sports commentary > ๐Ÿ’ก Browse the complete [ParseForge collection](https://apify.com/parseforge). *** **๐Ÿ†˜ Need Help?** [**Open our contact form**](https://tally.so/r/BzdKgA) to request a new scraper or report an issue. *** > **โš ๏ธ Disclaimer:** Independent tool, not affiliated with ESPN or The Walt Disney Company. Only publicly available sports data is collected. # Actor input Schema ## `maxItems` (type: `integer`): Free users: Limited to 10 records (preview). Paid users: Optional, max 1,000,000 ## `sport` (type: `string`): Select the sport or league to get data from. ## `dataType` (type: `string`): What data to collect. ## `teamId` (type: `string`): Optional: Get data for a specific team by ESPN ID (e.g. 25 for 49ers). Only used with Teams data type. ## Actor input object example ```json { "maxItems": 10, "sport": "nfl", "dataType": "scoreboard" } ``` # Actor output Schema ## `overview` (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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "maxItems": 10, "sport": "nfl", "dataType": "scoreboard" }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/espn-sports-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "maxItems": 10, "sport": "nfl", "dataType": "scoreboard", } # Run the Actor and wait for it to finish run = client.actor("parseforge/espn-sports-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "maxItems": 10, "sport": "nfl", "dataType": "scoreboard" }' | apify call parseforge/espn-sports-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/espn-sports-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "ESPN Sports Data Scraper", "description": "Extract live scores, standings, team rosters, and news from ESPN. Covers NFL, NBA, MLB, NHL, Premier League, La Liga, Serie A, Bundesliga, Ligue 1, and MLS. Get game schedules, odds, venue info, and team details. No proxy needed, pure API.", "version": "1.0", "x-build-id": "MLzPmAg1G9cKQ0F9L" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~espn-sports-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-espn-sports-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~espn-sports-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-espn-sports-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~espn-sports-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-espn-sports-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Free users: Limited to 10 records (preview). Paid users: Optional, max 1,000,000" }, "sport": { "title": "Sport / League", "enum": [ "nfl", "nba", "mlb", "nhl", "premier-league", "la-liga", "serie-a", "bundesliga", "ligue-1", "mls", "all" ], "type": "string", "description": "Select the sport or league to get data from." }, "dataType": { "title": "Data Type", "enum": [ "scoreboard", "teams", "standings", "news", "roster", "schedule" ], "type": "string", "description": "What data to collect." }, "teamId": { "title": "Team ID", "type": "string", "description": "Optional: Get data for a specific team by ESPN ID (e.g. 25 for 49ers). Only used with Teams data type." } } }, "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 } } } } } } } } } } ```