17 posts tagged “tutorial”.
Use Kalshi’s current eligibility, identity and bank-deposit documentation. Separate account approval, trading balance, settled funds and referral conditions.
Practical architecture guide for building a Polymarket trading bot in Python in 2026 — the eight components you need, how they fit together, what to build...
Identify the correct Polymarket product before following account or funding instructions. Then read its fees, bid/ask prices and settlement rules.
Pragmatic seven-step workflow for integrating a sports prediction API into your trading bot, dashboard, or research pipeline — auth, polling cadence, edge...
Step-by-step guide to building a sports prediction API in Python, from live data collection and feature engineering to model calibration and FastAPI...
Understand $1 contracts, executable bids and asks, gross break-even probabilities, fees and settlement rules using a hypothetical sports example.
Prediction market APIs compared: Polymarket CLOB, Kalshi REST, ESPN scoreboard/summary endpoints, The Odds API, auth, fees, rate limits, and Python.
How win probability models actually work — from Elo ratings through logistic regression to XGBoost. Includes calibration, feature engineering, and the...
Train and evaluate a calibrated NBA win probability model in Python using play-by-play game states, walk-forward validation, XGBoost and isotonic regression.
Step-by-step Polymarket CLOB API guide in Python: authentication, reading orderbooks, fetching market data, and placing limit orders programmatically.
Measure sports-model calibration with Brier score, ECE and held-out calibration examples. Separate reliability from executable-price profitability.
How to get real-time sports scores using WebSockets in Python. Compares HTTP polling vs WebSocket streaming, with working code for building a live data feed.
A complete step-by-step tutorial to implement an Elo rating system in Python for sports prediction. Covers the math, K-factor tuning, season resets, and...
A practical guide to backtesting sports betting and prediction market strategies in Python. Covers the common pitfalls — survivorship bias, look-ahead...
Python examples for ESPN scoreboard and summary endpoints: event IDs, winprobability fields, playId joins, missing sports and data limits.
A beginner's guide to automated trading on Polymarket. Learn how bots find edges using win probability models, and how to build your own.
How to implement Elo ratings from scratch in Python for sports prediction. Covers home advantage, K-factor tuning, and season resets.