# Polymarket Sports Odds Scanner & Divergence Finder (`bigdavidson/polymarket-sports-odds-divergence`) Actor Scan live Polymarket sports markets across 13 sports, or surface sharp-line divergence vs Pinnacle and other books using your own The Odds API key (free tier works): edge percent, direction, quarter-Kelly sizing. Scan mode needs no key. From $1 per 1,000 markets. - **URL**: https://apify.com/bigdavidson/polymarket-sports-odds-divergence.md - **Developed by:** [Jack Sheward](https://apify.com/bigdavidson) (community) - **Categories:** Developer tools, Other - **Stats:** 5 total users, 1 monthly users, 83.3% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 1,000 market rows 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 ## Polymarket Sports Odds Scanner & Divergence Finder Pull live **Polymarket sports odds** — every active sports market (soccer, NBA, NFL, MLB, NHL, UFC, tennis, cricket, esports and more) — as clean JSON records, then optionally surface **divergence between Polymarket prices and sharp sportsbook lines** (Pinnacle by default) using *your own* The Odds API key: no-vig fair probability, edge in percentage points, buy direction, and quarter-Kelly stake sizing per signal. Polymarket data comes straight from the public, unauthenticated Gamma API — no login, no scraping. Sportsbook lines come from [The Odds API](https://the-odds-api.com) with a **buyer-supplied key** (the free tier — 500 credits/month — covers daily runs; this actor spends at most 1 credit per active sport league per run, never per market). ### What you get #### `scan` mode — one `market` record per Polymarket sports market | Field | Example | Notes | |---|---|---| | `record_type` | `market` | | | `market_id` | `1356224` | Gamma market id | | `condition_id` | `0xace48…` | on-chain condition id | | `title` | `Will Houston Dynamo win on 2026-03-07?` | market question | | `sport` | `soccer` | canonical sport from the built-in classifier (`null` if unclassifiable) | | `teams` | `["New England Revolution", "Houston Dynamo"]` | best-effort, in **title order** (not home/away); `null` for outrights/props | | `event_date` | `2026-08-08T20:30:00Z` | game start when known, else market end date | | `yes_price` | `0.28` | price of outcome 0 (USD, 0–1) | | `no_price` | `0.72` | price of outcome 1 | | `outcome_labels` | `["Yes", "No"]` | may also be team names on some markets | | `volume` | `27480.27` | USD total traded | | `liquidity` | `2894.87` | USD posted liquidity | | `outcome_token_ids` | `["854285…", "637307…"]` | CLOB token ids, index-aligned with `outcome_labels` | | `url` | `https://polymarket.com/event/mls-ner-hou-2026-03-07` | event page | Example market record (key fields): ```json { "record_type": "market", "market_id": "1356224", "title": "Will Houston Dynamo win on 2026-03-07?", "sport": "soccer", "teams": ["New England Revolution", "Houston Dynamo"], "event_date": "2026-08-08T20:30:00Z", "yes_price": 0.28, "no_price": 0.72, "volume": 27480.27, "url": "https://polymarket.com/event/mls-ner-hou-2026-03-07" } ```` #### `divergence` mode — everything above **plus** one `signal` record per matched market × book with edge ≥ `minEdgePct` Signal records repeat all market fields and add: | Field | Example | Notes | |---|---|---| | `record_type` | `signal` | | | `book` | `pinnacle` | bookmaker key | | `book_odds_decimal` | `3.40` | the book's decimal odds for the YES side's outcome | | `implied_prob_novig` | `0.2846` | fair probability after removing the book's vig | | `polymarket_prob` | `0.445` | Polymarket YES price — for `buy_no` signals the actionable price is `no_price` (same record) | | `edge_pct` | `16.04` | fair prob of the recommended side minus its Polymarket price, ×100 | | `direction` | `buy_no` | `buy_yes` or `buy_no` | | `kelly_fraction_25` | `0.0901` | quarter-Kelly fraction of bankroll for that side | | `match_confidence` | `high` | `high` (exact team match) or `medium` (conservative fuzzy match) | | `matched_event` | `New England Revolution vs Houston Dynamo` | the sportsbook event it matched | | `commence_time` | `2026-08-08T20:30:00Z` | game start per the book | Example signal record: ```json { "record_type": "signal", "market_id": "1356220", "condition_id": "0xd1e93b3af50b6218aaf8ac710eef6dce437a93aad52cedacfbc0a45f36b5d7cd", "title": "Will New England Revolution vs. Houston Dynamo end in a draw?", "sport": "soccer", "teams": ["New England Revolution", "Houston Dynamo"], "event_date": "2026-08-08T20:30:00Z", "yes_price": 0.445, "no_price": 0.555, "outcome_labels": ["Yes", "No"], "volume": 31897.01, "liquidity": 2616.91, "outcome_token_ids": ["79383150873788993025…", "27555650786861172807…"], "url": "https://polymarket.com/event/mls-ner-hou-2026-03-07", "book": "pinnacle", "book_odds_decimal": 3.40, "implied_prob_novig": 0.2846, "polymarket_prob": 0.445, "edge_pct": 16.04, "direction": "buy_no", "kelly_fraction_25": 0.0901, "match_confidence": "high", "matched_event": "New England Revolution vs Houston Dynamo", "commence_time": "2026-08-08T20:30:00Z" } ``` Export as JSON, CSV, or Excel directly from the dataset. ### Input Default (scan, all sports, 200 markets — fast): ```json { "mode": "scan", "sports": ["all"], "maxMarkets": 200 } ``` Divergence example (bring your own The Odds API key): ```json { "mode": "divergence", "sports": ["soccer", "mlb", "nba"], "minVolume": 10000, "maxMarkets": 500, "oddsApiKey": "YOUR-ODDS-API-KEY", "books": ["pinnacle"], "minEdgePct": 3 } ``` - `mode` — `scan` (Polymarket markets only) or `divergence` (scan + sportsbook comparison). - `sports` — canonical names (`nba`, `wnba`, `nfl`, `mlb`, `nhl`, `ufc`, `soccer`, `tennis`, `cricket`, `f1`, `golf`, `boxing`, `esports`) or `"all"`. - `minVolume` / `minLiquidity` — USD floors; 0 disables. - `maxMarkets` — 1–2000 cap on market records. - `oddsApiKey` — **your** The Odds API key; required only for divergence mode. Used solely for this run's requests — never stored, never logged. Missing key = warning + scan output. - `books` — The Odds API bookmaker keys (default `["pinnacle"]`, the sharp baseline). - `minEdgePct` — signal floor in percentage points (default 3). - `regions` — The Odds API regions (`us,eu` default); only used when `books` is empty. ### How divergence detection works 1. **Scan** active Polymarket sports markets (Gamma API, stale and non-trading markets filtered out at the market level). 2. **Classify** each market's sport (Gamma tags first, then a two-pass keyword/team-name classifier carried over from a production sports trading system). 3. **Match conservatively**: only game-level moneyline markets with two parsed team names; team names are normalized (case, accents, punctuation, common aliases like "Man City") and both home/away orientations are checked; game time must agree within 12 hours. Anything below medium confidence is dropped, not guessed. 4. **De-vig** the book's h2h line: implied probabilities `1/odds` are normalized over **all** outcomes (including Draw for soccer), so `p(team)` is the true win probability with draws counting against — exactly the YES side of Polymarket's "Will X win?" game markets. 5. **Score**: `edge_pct = (fair probability of side − Polymarket price of side) × 100`; the better of `buy_yes`/`buy_no` is emitted when it clears `minEdgePct`, with quarter-Kelly sizing `0.25 × (p − price) / (1 − price)`. ### Pricing Pay per result — no subscription: - **$0.005** per run (`actor-start`) - **$0.001** per market record (`market-row`) - **$0.02** per divergence signal (`divergence-signal`) A default scan run (200 markets) costs **$0.205**. A divergence run with 200 markets and 10 signals costs **$0.405** — plus your own (free-tier) Odds API credits, typically 1–8 per run. ### FAQ #### How do I find arbitrage between Polymarket and sportsbooks? Run `divergence` mode with your The Odds API key. Each signal tells you which side of the Polymarket market is cheap relative to the sharp no-vig line (`direction`), by how much (`edge_pct`), and a conservative stake size (`kelly_fraction_25`). True risk-free arbitrage additionally requires hedging the other side at the book — these signals are *value* signals against the sharp line. #### What is no-vig (fair) probability? Bookmaker odds embed a margin (vig): implied probabilities sum to more than 1. Dividing each implied probability by that sum removes the margin. Pinnacle's no-vig line is a widely used proxy for true probability. #### Do I need an API key? Not for `scan` mode — Polymarket's Gamma API is public. For `divergence` mode you supply your own The Odds API key; the free tier (500 credits/month) is plenty because this actor spends at most one credit per active sport league per run (Pinnacle-only counts as a single region). #### How are Polymarket markets matched to sportsbook games? By normalized team names (both orientations — Polymarket titles don't guarantee home team first) plus a ±12 h game-time window. Exact name matches are `high` confidence; token-subset/nickname matches are `medium`. Anything weaker is dropped rather than guessed. #### How does it handle soccer's three-way (draw) odds? The fair probability is computed over all three outcomes, so a team's `implied_prob_novig` already counts draws against it — directly comparable to Polymarket's binary "Will X win?" markets. Draw markets themselves match the book's Draw outcome. Double-chance or "to advance/qualify" markets are excluded from matching entirely. #### Which sports are supported? Scan: everything under Polymarket's Sports tag. Divergence: nba, wnba, nfl, mlb, nhl, ufc, boxing, soccer (top leagues + World Cup), tennis and cricket — golf, F1 and esports have no usable h2h coverage on The Odds API. #### Is my Odds API key stored anywhere? No. It is used for this run's HTTP requests only — never written to the dataset, key-value store, or logs (HTTP client URL logging is explicitly disabled, and error messages are scrubbed). #### Is this financial advice? No. It is market data plus arithmetic. Prediction markets and sports betting carry real risk; sizing outputs are informational. ### Limitations - **Matching is conservative by design** — markets that can't be matched at medium-or-better confidence produce no signal at all. Expect coverage, not completeness. - **Gamma prices can lag the live order book** (responses are CDN-cached up to 5 minutes, and `yes_price` is the Gamma outcome price, not CLOB top-of-book). Always verify the live book before trading; `outcome_token_ids` are included so you can query the CLOB directly. - **Divergence covers game-level moneyline markets only** — no totals, spreads, props, or outright/futures markets. - `liquidity` is total deposited liquidity, not depth at the current price — don't size positions off it. - The Odds API stops listing games near/after start; Polymarket may still show them. Postponed games can mismatch on date. - `event_date` falls back to the market end date when Gamma omits `gameStartTime`; rescheduled games can then fall outside the ±12 h match window — missed signals, never false matches. - When Gamma tags are generic, `sport` comes from a text classifier; rare cross-sport team-name clashes (e.g. an NHL "Kings vs Oilers" title without league tags classifies as `nba`) can make a `sports` filter miss a market. - The buyer's The Odds API key is required for divergence mode; without it the run still succeeds and ships scan records. - Not financial advice. ### Use with AI agents (MCP) Connect your agent to the Apify MCP server (mcp.apify.com) and it can call this actor as a tool: ask for "scan Polymarket soccer markets over $10k volume" or "find divergence vs Pinnacle above 5% in MLB" and the agent fills the input schema (mode, sports, minVolume, minEdgePct) itself. Pair the scan output with the CLOB token ids for execution research. ### More prediction-market data actors - [Kalshi Weather Markets Data — KXHIGH & KXLOW](https://apify.com/bigdavidson/kalshi-weather-markets) - live brackets and settlement history for Kalshi temperature markets. - [METAR & NWS Weather Station Observations API](https://apify.com/bigdavidson/metar-nws-weather-station-observations) - the raw station observations weather markets settle on. - [Prediction Market Resolution Evidence Checker](https://apify.com/bigdavidson/prediction-market-resolution-evidence) - paste a market URL, get the live observation that resolves it, graded. # Actor input Schema ## `mode` (type: `string`): scan = pull live Polymarket sports markets as clean records. divergence = scan, then match game-level markets against sportsbook h2h lines via your The Odds API key and emit edge signals on top. ## `sports` (type: `array`): Canonical sport names: nba, wnba, nfl, mlb, nhl, ufc, soccer, tennis, cricket, f1, golf, boxing, esports — or "all" for every sport ("all" also includes markets the classifier cannot label). ## `minVolume` (type: `integer`): Keep only markets with at least this much total traded volume (USD). 0 = no filter. ## `minLiquidity` (type: `integer`): Keep only markets with at least this much posted liquidity (USD). Note: Gamma liquidity is total deposited liquidity, not depth at the current price. 0 = no filter. ## `maxMarkets` (type: `integer`): Hard cap on scanned market records (caps the per-record charge too). ## `oddsApiKey` (type: `string`): Your own key from the-odds-api.com — the free tier (500 credits/month) covers daily divergence runs; this actor spends at most 1 credit per active sport league per run. Used only for this run's requests, never stored or logged. Without it, divergence mode degrades to scan output with a warning. ## `books` (type: `array`): The Odds API bookmaker keys to compare against (pinnacle = the sharp-money baseline). One signal per market per book. Overrides regions when set. ## `minEdgePct` (type: `number`): Only emit divergence signals with at least this edge, in percentage points (no-vig fair probability minus Polymarket price, x100). ## `regions` (type: `string`): Comma-separated The Odds API regions (us, us2, uk, eu, au). Only used when books is empty — bookmaker keys override regions. Each region multiplies the per-call credit cost. ## Actor input object example ```json { "mode": "scan", "sports": [ "all" ], "minVolume": 0, "minLiquidity": 0, "maxMarkets": 200, "books": [ "pinnacle" ], "minEdgePct": 3, "regions": "us,eu" } ``` # 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 = { "mode": "scan", "sports": [ "all" ], "maxMarkets": 200, "books": [ "pinnacle" ] }; // Run the Actor and wait for it to finish const run = await client.actor("bigdavidson/polymarket-sports-odds-divergence").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 = { "mode": "scan", "sports": ["all"], "maxMarkets": 200, "books": ["pinnacle"], } # Run the Actor and wait for it to finish run = client.actor("bigdavidson/polymarket-sports-odds-divergence").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 '{ "mode": "scan", "sports": [ "all" ], "maxMarkets": 200, "books": [ "pinnacle" ] }' | apify call bigdavidson/polymarket-sports-odds-divergence --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=bigdavidson/polymarket-sports-odds-divergence", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Polymarket Sports Odds Scanner & Divergence Finder", "description": "Scan live Polymarket sports markets across 13 sports, or surface sharp-line divergence vs Pinnacle and other books using your own The Odds API key (free tier works): edge percent, direction, quarter-Kelly sizing. Scan mode needs no key. From $1 per 1,000 markets.", "version": "0.1", "x-build-id": "5LjqZstg5r9Jm2XOY" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/bigdavidson~polymarket-sports-odds-divergence/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-bigdavidson-polymarket-sports-odds-divergence", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/bigdavidson~polymarket-sports-odds-divergence/runs": { "post": { "operationId": "runs-sync-bigdavidson-polymarket-sports-odds-divergence", "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/bigdavidson~polymarket-sports-odds-divergence/run-sync": { "post": { "operationId": "run-sync-bigdavidson-polymarket-sports-odds-divergence", "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": { "mode": { "title": "Mode", "enum": [ "scan", "divergence" ], "type": "string", "description": "scan = pull live Polymarket sports markets as clean records. divergence = scan, then match game-level markets against sportsbook h2h lines via your The Odds API key and emit edge signals on top.", "default": "scan" }, "sports": { "title": "Sports", "type": "array", "description": "Canonical sport names: nba, wnba, nfl, mlb, nhl, ufc, soccer, tennis, cricket, f1, golf, boxing, esports — or \"all\" for every sport (\"all\" also includes markets the classifier cannot label).", "default": [ "all" ], "items": { "type": "string" } }, "minVolume": { "title": "Min volume (USD)", "minimum": 0, "type": "integer", "description": "Keep only markets with at least this much total traded volume (USD). 0 = no filter.", "default": 0 }, "minLiquidity": { "title": "Min liquidity (USD)", "minimum": 0, "type": "integer", "description": "Keep only markets with at least this much posted liquidity (USD). Note: Gamma liquidity is total deposited liquidity, not depth at the current price. 0 = no filter.", "default": 0 }, "maxMarkets": { "title": "Max markets", "minimum": 1, "maximum": 2000, "type": "integer", "description": "Hard cap on scanned market records (caps the per-record charge too).", "default": 200 }, "oddsApiKey": { "title": "The Odds API key (divergence mode only)", "type": "string", "description": "Your own key from the-odds-api.com — the free tier (500 credits/month) covers daily divergence runs; this actor spends at most 1 credit per active sport league per run. Used only for this run's requests, never stored or logged. Without it, divergence mode degrades to scan output with a warning." }, "books": { "title": "Bookmakers", "type": "array", "description": "The Odds API bookmaker keys to compare against (pinnacle = the sharp-money baseline). One signal per market per book. Overrides regions when set.", "default": [ "pinnacle" ], "items": { "type": "string" } }, "minEdgePct": { "title": "Min edge %", "minimum": 0, "maximum": 50, "type": "number", "description": "Only emit divergence signals with at least this edge, in percentage points (no-vig fair probability minus Polymarket price, x100).", "default": 3 }, "regions": { "title": "Odds API regions", "type": "string", "description": "Comma-separated The Odds API regions (us, us2, uk, eu, au). Only used when books is empty — bookmaker keys override regions. Each region multiplies the per-call credit cost.", "default": "us,eu" } } }, "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 } } } } } } } } } } ```