OpticOdds has become the first provider to place its proprietary sportsbook data API directly inside Claude, marking a new step in how AI is being applied to sports betting data and user-facing analysis.
The move will enable Claude to gain access to the OpticOdds feed instantly. The feed pulls odds from more than 200 bookmakers, including some of the top-ranked operators in the industry.
By pulling data directly through the OpticOdds API, the business delivers structured sportsbook information in a cleaner format, which is better suited for automated analysis inside an AI assistant.
The integration changes how end users can interact with sports betting information. Instead of manually checking screens, comparing books, or filtering spreadsheets, users can submit complex prompts in plain language.
A bettor could ask Claude to identify NBA player props that moved by more than two points within the last hour, while also checking whether a player’s primary defender has been ruled out. Claude can then process those inputs against the OpticOdds feed across hundreds of sportsbooks at once.
Below, NEXT.io sits down with OpticOdds Vice President Ryan Weinstock to gain better clarity on how the system works, receiving significant insight into this new integration.
NEXT: How does the Claude integration maintain the real-time integrity of your API when passing through an LLM’s reasoning layer, and what is the typical ‘glass-to-glass’ latency for a user query?
Ryan Weinstock: The key thing to understand is that Claude isn’t sitting between the user and our data, but sitting next to it. We built this as an MCP server, which means Claude can call our API directly, get the real-time odds, and then do what it does best: make sense of it in natural language. The data itself isn’t being filtered or reinterpreted before it hits Claude. It’s the same unified feed, same freshness, same sub-second delivery we give to every client, whether that’s a startup or one of the largest sportsbooks in the world. Claude is just the interface layer.
On latency, our API delivers odds in under 900 milliseconds. We have hundreds of servers processing over a million odds per second, and that infrastructure doesn’t change just because the request is coming from an AI assistant instead of a dashboard. The full round trip stays sub-one-second for the data retrieval, before being processed via Claude in its typical timeframe for requests, ensuring that it remains an incredible seamless process to collate data.
NEXT: Claude is known for its sophisticated reasoning, but LLMs historically struggle with high-precision math and hallucinations. How does this integration ensure that Claude isn’t just guessing a value, but is performing accurate, verifiable arbitrage and expected value calculations using your raw data?
RW: This traditional ‘problem’ with LLMs is precisely why we built the extension the way we did. Claude is not doing the math, our engine is. When you ask something like “show me the best EV plays on tonight’s NBA slate” Claude calls our API, and what comes back are pre-calculated values. Expected value, fair odds, arbitrage opportunities, all computed by our pricing models.
Our platform was built by ex-traders and quants, it’s trusted by over 200 companies of varying scale, and it processes over a million odds per second. Claude’s job is to take those numbers and present them in a way that’s useful to a human. Its role is purely translating, not calculating.
That distinction matters. We’re not asking an LLM to become a calculator. We’re pairing the best reasoning model in the market with the most comprehensive real-time sports data feed available. Claude handles delivering content in a way that can be easily digestible and gets to the key outcomes. We handle the “what are the actual numbers” part. If Claude tells you there’s a 3.2% edge on a player prop, that 3.2% came from our engine, not from Claude doing mental math.
NEXT: Does the Claude integration allow users to cross-reference OpticOdds’ market data with unstructured data sources like X, injury reports, or weather feeds to explain line movement in real-time?
RW: [Our] API already includes injury data, confirmed lineups, and full game schedules natively. That’s baked into the same feed, not a separate source. We also track every line movement across 200+ sportsbooks in real time, so tracking what has moved is already covered on our side.
Now for the broader question about layering in things like social media sources or weather, that’s where the Model Context Protocol (MCP) architecture gets really interesting. MCP is an open protocol, so there’s nothing stopping a developer or power user from connecting additional MCP servers that pull from X, weather APIs, or whatever else they want. Claude can talk to all of them in the same conversation alongside our data.
Can someone ask Claude “why did the Chiefs line just move two points” and have it cross-reference our odds movement data with an injury report that dropped on social media 10 minutes ago? Absolutely. We provide the market data backbone, such as odds, line movement, injuries, schedules. And the MCP ecosystem lets users layer on whatever additional context matters to their workflow. Claude ties it all together.
NEXT: Will this Claude integration eventually merge with the Copilot ecosystem?
RW: That’s the direction we’re heading. Copilot is our automated trading platform. It handles pricing, position management, and settlement. We’re working on bringing blended lines from Copilot into the Claude integration. Operators and sharp bettors will be able to access Copilot-generated pricing through natural language, which is a pretty big unlock.
Currently, customers can ask Claude to pull real-time odds from 200+ books through our API. Soon that capability will also include being able to pull our Copilot-blended fair value lines into that same conversation. That means that users won’t just have visibility on the market is doing, but also what OpticOdds thinks the market should be doing, and you can have a real conversation about the delta.
NEXT: Is the integration already live everywhere Claude is available?
RW: Yes. The MCP server works anywhere Claude supports the Model Context Protocol. If you can run an MCP server with Claude, you can connect to OpticOdds via API key. It’s live.
The beauty of building on MCP is that we’re not dependent on any single Claude product or interface. As Anthropic expands where MCP is supported, our integration automatically goes with it. We built it once, and it works everywhere.
The practical appeal of this integration lies in speed and scale. A human bettor switching between tabs may miss pricing differences across operators, especially when odds move quickly.
With access to a centralised feed, Claude can surface discrepancies in near real time, such as one book offering a team at -110 while another posts +105.
That ability to synthesise large volumes of market data into an immediate answer is central to the pitch.
The integration also points to a wider use case for contextual analysis. Claude can combine sportsbook data with outside variables, such as weather changes or injury developments to support more detailed betting research.
It can also examine relationships between outcomes when users are building same-game parlays, including how one event may affect another within the same matchup.
For sports bettors, the immediate result is a more practical interface for handling vast betting datasets. For the industry, it’s another sign that AI tools are moving from novelty to embedded utility inside everyday wagering research.