Give your AI assistant the actual lines.
Build a prompt from a recorded board sample, with observation times and explicit limits. Connect MCP when you need full board queries or historical results.
Choose a board sample
Filters apply to the returned sample, not the whole board. For full search and historical results, use the authenticated API or MCP data tools.
Your evidence prompt
Load a board to generate a prompt with real recorded rows and their observation times.
Connect the data source
MCP endpoint: https://prizepicksapi.com/api/mcp. Public search and fetch can read public pages; authenticated data tools use your account access and credits. Keep keys in your client’s secure credential configuration.
A reproducible research workflow
- Load the league’s recorded sample and check the row observation times.
- Filter the sample. If the player is absent, query the full API instead of assuming no line exists.
- Copy the prompt into your assistant. Ask it to cite the supplied rows and identify missing evidence.
- For historical context, query hit rates and game logs with the same player, market and observation window.
Questions
Does an AI assistant automatically know current PrizePicks lines?
No. Give it a timestamped data source or connect the API. This builder includes observed rows and tells the assistant to distinguish a sample from full board coverage.
Does this generate picks?
No. It builds an evidence prompt for analysis and explicitly forbids invented lines, payouts, results and predictions.
How do I get a player missing from this sample?
The public sample is bounded to 40 rows. Use authenticated projections with league, search or stat filters for the full matching board.
Are historical hit rates included?
Not in this public board sample. Connect the documented hit-rate and game-log tools through MCP or API to add recorded history.