GSS Analytics · Field notes
Blog
CLV, edge detection, backtesting math, and what we learn from running probability models against live football markets every day. Written for bettors who'd rather check the work than read the hype.
-
Value Betting vs Matched Betting vs Arbitrage: Which Actually Builds a Bankroll?
All three try to beat the bookmaker, but only one scales into a long-term, growing bankroll. The honest comparison — including the catch nobody advertises.
Read post → -
How AI Predicts Football Matches: Poisson, Dixon-Coles and the Limits of Models
Not crystal balls — probability. A plain-language look inside the models that turn goals, xG and context into calibrated football predictions.
Read post → -
Expected Value in Football Betting: How +EV Turns Luck Into Edge
A single result tells you almost nothing. Expected value (+EV) tells you whether the bet was smart — the metric that separates disciplined bettors from gamblers.
Read post → -
Why CLV is the only honest scoreboard for sports bettors
Profit and win rate lie. Closing Line Value tells you whether you actually beat the market — and unlike the others, it stabilises in weeks instead of years.
Read post → -
The Kelly criterion for football bettors — explained without the math PhD
Most bettors stake the same amount every time. The Kelly criterion stakes by edge — and is the formula behind every serious bankroll-growth strategy.
Read post → -
Three flags to spot a curve-fit backtest before you trust one
Every Discord can show a 200% backtest. Most are tuned in hindsight and collapse on tomorrow's data. Here's how to spot them.
Read post →