xG · Expected Goals
Quantifies the actual quality of the chances created. Distinguishes the team that deserved to win from the one that was merely lucky. It is the most predictive indicator of future performance.
The ball obeys physics. Statistics obey patterns. Our AI obeys the data.
Goetia sets mysticism aside and becomes a sophisticated Machine Learning system with massive ingestion of sports Big Data. The algorithm processes dozens of contextual variables in real time and far surpasses the limitations of manual human analysis, identifying genuine, measurable value in every match.
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Manual football analysis has always been held back by two problems: observer bias and an impossible volume of data. No human analyst can simultaneously process the rigorous statistics of the last 50 matches for both teams, their advanced metrics, injury reports and market movements.
Our Artificial Intelligence engine can. It processes massive, constantly evolving databases. The model detects patterns and analyses dozens of complex variables: rigorous match statistics, expected goals (xG), head-to-head history (H2H), ball possession and the latest market and injury news.
Far surpassing the capacity of manual human analysis, Goetia delivers objective, long-term consistent forecasts, identifying real value in every match. We do not promise perfect predictions: we promise analysis free of emotional bias, free of favouritism and free of the influence of the last game watched.
This is Machine Learning applied to a sport that was analysed by instinct for decades. It is time to change sides.
Quantifies the actual quality of the chances created. Distinguishes the team that deserved to win from the one that was merely lucky. It is the most predictive indicator of future performance.
Results, scorelines and tactical patterns from the most recent meetings between both teams. Enables detection of bogey teams and recurring dynamics.
Not raw possession, but possession that translates into dangerous zones: passes in the final third, touches in the box and vertical progression.
Confirmed absences, last-minute doubts and the real weight of each missing player based on their tactical role within the team's system.
The last 5–10 matches count, but not equally. Goetia weights performance against opponents of comparable quality to avoid inflation from an easy fixture run.
Odds move for a reason. The model tracks opening lines, intermediate shifts and closing prices to detect where the smart money is going.
The engine consumes real-time databases: statistics, injuries, line-ups, weather, pitch conditions and odds movements.
The AI filters noise, normalises variables, discards outliers and cross-references contextual data to build a model for the specific match.
Machine Learning algorithms calculate probabilities for 1×2, double chance, Asian handicap, totals (over/under) and both teams to score.
Goetia compares its calculated probability against market odds and flags where genuine, measurable value exists. That is the edge.
«I spent years doing manual analysis and never achieved the consistency I have had since following Goetia's predictions. The cross-reference of xG with H2H is remarkable.»
«What convinced me was that the AI explains the reasoning behind every forecast. It is not a blind recommendation: it shows you the variables that carried the most weight for each match.»
«I found value in odds the market had underestimated. The way Goetia identifies "real value" completely changed how I read a match.»
Tell us the match you want analysed and our Artificial Intelligence engine will process all available variables to deliver a technical, reasoned forecast with detail on every metric considered.