Sports analytics, prediction markets, and building trading bots with Python.
WTA prediction model results: 41W-21L, 66.1% win rate. ML-powered fair value vs Polymarket prices.
Counter-Strike 2 prediction model results: 33W-27L, 55.0% win rate. ML-powered fair value vs Polymarket prices.
Honest guide to Polymarket referral codes, promo codes, and sign-up bonuses in May 2026. How the referral program actually works, which codes are real...
MLB Baseball prediction model results: 16W-17L, 48.5% win rate. ML-powered fair value vs Polymarket prices.
ATP prediction model results: 6W-10L, 37.5% win rate. ML-powered fair value vs Polymarket prices.
Honest 2026 guide to Kalshi's referral code and new-user sign-up bonus. How the referral program actually works, what the typical welcome offer is, which...
NHL Hockey prediction model results: 5W-3L, 62.5% win rate. ML-powered fair value vs Polymarket prices.
NBA Basketball prediction model results: 0W-3L, 0.0% win rate. ML-powered fair value vs Polymarket prices.
Honest 2026 comparison of Polymarket vs Kalshi sign-up bonuses, referral programs, and new-user offers. How each platform's promotion actually works, the...
ZenHodl week 21 live trading results across 8 sports. 52.2% win rate on 224 trades.
Is Polymarket legal for US users in 2026? Full breakdown of the 2022 CFTC settlement, the 2024 DOJ raid, the current geo-block, what US-based traders can...
Step-by-step 2026 walkthrough for US users signing up to Kalshi — eligibility check, account creation, KYC with SSN, ACH funding from your bank, finding...
League of Legends prediction model results: 8W-13L, 38.1% win rate. ML-powered fair value vs Polymarket prices.
SOCCER prediction model results: 8W-13L, 38.1% win rate. ML-powered fair value vs Polymarket prices.
Practical guide to backtesting Polymarket trading strategies in 2026 — the free CLOB price-history API, what it misses (orderbook depth), how to model...
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...
Practical 2026 comparison of Kalshi alternatives — Polymarket, PredictIt, Manifold, Robinhood Event Contracts, and sportsbook futures. Liquidity, fees...
Practical orientation to Polymarket's API documentation in 2026 — the three API surfaces, what the official docs cover well, the operational gotchas...
Polymarket has no built-in paper trading mode. Here are the real options for testing strategies without risk — Manifold Markets, historical price...
Direct answer to whether Kalshi supports parlays in 2026 — what Kalshi's actual order types do, the structural reason event contract exchanges don't offer...
Practical 2026 walkthrough for first-time Polymarket users — geographic access, wallet setup, USDC funding on Polygon, finding sports markets, placing...
Head-to-head comparison of Polymarket and Kalshi for sports prediction trading in 2026 — liquidity per sport, fees, regulation, API access, and which...
Structural guide to the Kalshi NFL MVP market — how multi-outcome contracts work, how to read per-player implied probabilities, seasonal liquidity...
Practical guide to how Polymarket fees actually work in 2026 — maker vs taker, per-market variation, the NCAAMB winnings fee, gas costs on Polygon, and...
Comparison of the most useful sports prediction tools in 2026 — calibrated APIs, odds aggregators, public model dashboards, live data feeds, and bot...
Honest breakdown of our automated Polymarket trading bots' on-chain P&L by market type — moneyline vs spread vs total, in-play vs pregame, sport by sport...
Plain-English guide to sports prediction APIs in 2026 — what they return, how authentication and rate limits work, what calibration means, and how to...
Pragmatic seven-step workflow for integrating a sports prediction API into your trading bot, dashboard, or research pipeline — auth, polling cadence, edge...
Architecture and Python patterns for scanning live sports markets in real time and surfacing edge signals — WebSocket subscriptions, latency budgets, edge...
Head-to-head comparison of ZenHodl's calibrated win probabilities against Polymarket's market-implied probabilities across 5,000+ resolved games. Where...
A practical playbook for turning calibrated machine-learning win probabilities into profitable bets — fair-value gates, Kelly sizing, edge band filters...
A year of on-chain trading data on Polymarket — what it reveals about sports prediction market efficiency, where systematic mispricing persists, and where...
Complete guide to betting odds formats with conversion math — American, decimal, fractional, and implied probability — plus how vig distorts the implied...
How we designed a single unified API schema that serves calibrated win probabilities for 11 different sports — basketball, hockey, baseball, football...
Full Kelly assumes your edge is real. After six losing days in a row, that assumption deserves a second look. How we layered a drawdown-aware sizing ramp...
The Kelly Criterion tells you the mathematically optimal bet size when you have an edge. Most traders bet 2-4x too much. Here's the formula, the Python...
Step-by-step guide to building a sports prediction API in Python, from live data collection and feature engineering to model calibration and FastAPI...
Several people asked why the pre-committed NBA Playoffs benchmark starts at Conference Semifinals instead of covering First Round games already in...
We just announced and on-chain anchored a 7-week head-to-head benchmark: ZenHodl's NBA model vs the live Polymarket consensus, every Conference Semis...
We surveyed 21 sports prediction providers — KenPom, BetQL, Sportradar, FiveThirtyEight, MoneyPuck, OddsJam, and 15 others — for the one number a...
After Florida beat Edmonton 4-2 to repeat as Stanley Cup champions in 2025, we ran our NHL win-probability model on every playoff game using only...
PSG, Arsenal, Atlético Madrid, and Bayern Munich are the 2025-26 UCL semifinalists. Our production club-soccer model (trained on 3,000+ matches, 75%...
A math-first 2026 analysis of sportsbook welcome bonuses, bonus bets, and promo codes. Most 'free $200' offers are net-negative in expected value once you...
Prediction markets are the fastest-growing alternative to traditional sportsbooks. This 2026 guide explains what they are, how they differ from...
A 2026 honest guide to AI sports predictions. Most 'AI' picks sites are ChatGPT wrappers generating narrative content around sportsbook lines. The genuine...
Most sports prediction models are accurate but not calibrated — and that gap is why their backtests lie. A practical guide to what calibration means, how...
Most sports prediction platforms advertise accuracy that doesn't hold up to measurement. Here's how to evaluate one properly — with published ECE...
After the 2025 World Series ended in November, we ran our MLB win-probability model on every postseason game — Wild Card through Game 7 — using only...
A 2026 honest answer to whether sports prediction apps actually work. Most 'expert picks' sites are post-hoc curation of sportsbook lines; about 5%...
A 2026 investigation of insider trading in prediction markets. We examine the 2024 Polymarket election dispute, academic studies of PredictIt...
An honest, math-first answer to whether you can profit from sports betting long-term. The arithmetic of edge, vig, variance, and Kelly sizing — plus the 5...
Two days into the 2026 NHL playoffs. Our calibrated NHL model has Colorado and Tampa Bay as the Cup favorites, with Carolina close behind. Here's every...
Every major sports picks site says 'for entertainment purposes only' — but what does that actually mean? It's a legal admission that the publisher doesn't...
After Super Bowl LX wrapped on February 8, we ran our NFL win-probability model on every 2025-26 playoff game using only pre-playoff data. It hit 9 of 13...
The 2026 FIFA World Cup kicks off June 11 in USA/Canada/Mexico. Our Monte Carlo bracket simulator gives Argentina a 26.2% chance to repeat, Brazil at...
After the 2025 NBA Finals wrapped with OKC beating Indiana in seven games, we ran our NBA win-probability model on all 84 postseason games using only...
Our initial college football win probability model backtested at -2.1c/trade across 728 simulated positions. The bug wasn't the model — it was a feature...
We backtested our NCAAMB win-probability model on every non-tournament game of the 2025-26 college basketball season — 5,345 games. Accuracy: 68.19%...
After the 2026 NCAA tournament ended, we ran our NCAAMB win-probability model on all 67 games using only pre-tournament data. It called 48 of 67 correctly...
A developer and trader's guide to the best prediction market platforms in 2026. Kalshi, Polymarket, PredictIt, Manifold Markets, and ForecastEx — compared...
Original research on prediction market liquidity, accuracy, and profitability across Polymarket, Kalshi, DraftKings, and FanDuel. Based on 25M+ data...
Every prediction market API compared: Polymarket CLOB, Kalshi REST, DraftKings odds via The Odds API. Authentication, endpoints, rate limits, and Python...
How win probability models actually work — from Elo ratings through logistic regression to XGBoost. Includes calibration, feature engineering, and the...
League of Legends prediction model results: 10W-13L, 43.5% win rate. ML-powered fair value vs Polymarket prices.
ZenHodl week 16 live trading results across 7 sports. 58.7% win rate on 201 trades.
ATP prediction model results: 9W-8L, 52.9% win rate. ML-powered fair value vs Polymarket prices.
NHL Hockey prediction model results: 28W-12L, 70.0% win rate. ML-powered fair value vs Polymarket prices.
NBA Basketball prediction model results: 6W-6L, 50.0% win rate. ML-powered fair value vs Polymarket prices.
Transparent breakdown of 335 live Polymarket trades across NBA, MLB, NHL, tennis, LoL, CS2, and more. Win rates, P&L by sport, what worked and what didn't.
SOCCER prediction model results: 3W-5L, 37.5% win rate. ML-powered fair value vs Polymarket prices.
Counter-Strike 2 prediction model results: 11W-18L, 37.9% win rate. ML-powered fair value vs Polymarket prices.
Inside ZenHodl's NBA prediction engine: XGBoost models, team stats, real-time injury overlays, and isotonic calibration. How our ML system processes...
MLB Baseball prediction model results: 51W-21L, 70.8% win rate. ML-powered fair value vs Polymarket prices.
Complete tutorial for building an NBA live win probability model in Python using XGBoost. Covers data collection, feature engineering, training...
Comparing the top sports data APIs for prediction modeling and trading in 2026. Coverage, pricing, latency, and what each is best for.
We run automated prediction bots on Polymarket across 7 sports. Here's our verified P&L, the strategy, and what we learned from 938+ live trades.
The same NBA game is priced differently on Polymarket, DraftKings, FanDuel, and BetMGM. Here's the math, the architecture, and the actual disagreements we...
Our system finds dozens of trading signals per day. We trade 35% of them. The discipline to reject bad signals is worth more than the ability to find good...
Our NBA bot had 65% accuracy and was losing money. The problem wasn't the model — it was a calibration bug that left it confidently wrong. Here's how we...
Counter-Strike 2 has the widest mispricings on Polymarket. It also has the worst data infrastructure. Here's how we built a 4-tier model that handles both.
We audited every bot, found the gaps between backtest and live performance, and fixed them. CS2, NBA, MLB, LoL, and Tennis — five different problems, five...
You don't need a quant fund. Our complete trading infrastructure runs on a $7/month VPS plus $5/month for sportsbook odds. Here's the full breakdown.
League of Legends prediction model results: 10W-6L, 62.5% win rate. ML-powered fair value vs Polymarket prices.
Counter-Strike 2 prediction model results: 19W-25L, 43.2% win rate. ML-powered fair value vs Polymarket prices.
NCAAWB prediction model results: 3W-0L, 100.0% win rate. ML-powered fair value vs Polymarket prices.
NBA Basketball prediction model results: 2W-4L, 33.3% win rate. ML-powered fair value vs Polymarket prices.
MLB Baseball prediction model results: 21W-12L, 63.6% win rate. ML-powered fair value vs Polymarket prices.
ZenHodl week 15 live trading results across 9 sports. 57.8% win rate on 147 trades.
NHL Hockey prediction model results: 16W-10L, 61.5% win rate. ML-powered fair value vs Polymarket prices.
SOCCER prediction model results: 2W-1L, 66.7% win rate. ML-powered fair value vs Polymarket prices.
College Basketball prediction model results: 4W-0L, 100.0% win rate. ML-powered fair value vs Polymarket prices.
ATP prediction model results: 8W-4L, 66.7% win rate. ML-powered fair value vs Polymarket prices.
Every one of our bots holds to settlement instead of actively trading. Here's why patience crushes activity on Polymarket — and the failed strategies that...
The same game is priced differently on Polymarket, DraftKings, FanDuel, and BetMGM. Here's how to systematically find and exploit the differences.
Real P&L from 5 live Polymarket bots trading NBA, MLB, NHL, NCAAMB, CS2, LoL, Tennis, and Soccer. Honest about what works and what doesn't.
Tennis prediction model results: 6W-0L, 100.0% win rate. ML-powered fair value vs Polymarket prices.
Step-by-step guide to using the Polymarket CLOB API in Python. Covers authentication, reading orderbooks, fetching market data, and placing limit orders...
ZenHodl week 14 live trading results across 5 sports. 81.8% win rate on 11 trades.
We backtested 237 trade signals with and without execution constraints. 99% of theoretical profit vanished. Here's what actually kills your trades — and...
A 6-feature model outperforms a 50-feature model at making money — even with a worse accuracy score. Here's why, and what it means for how you should...
A well-calibrated model makes money even with lower accuracy. Learn how to measure calibration with Brier score and ECE, and fix it with isotonic...
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...
How to use Python to scrape live scores, play-by-play data, and win probabilities from ESPN's hidden API. Complete tutorial with working code.
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.