Common Strategy Patterns
While every strategy is unique, many effective strategies are built around recurring match patterns. These patterns describe situations that tend to appear frequently in live football data.
This page does not provide ready-made strategies. Instead, it helps you recognize common types of situations and understand how they can be translated into clear, logical rules.
Late pressure without goals
One frequent pattern occurs when a team applies sustained pressure late in the match but has not yet converted it into goals.
Typical signals may include:
- High momentum over a sustained period
- Strong attacking activity
- Low or unchanged scoreline
- Match time well into the second half
This type of pattern is usually expressed by bounding rules, such as combining minimum and maximum values.
Dominance imbalance
Another common scenario is when one team clearly dominates the game, while the scoreline does not yet reflect that control.
Indicators often involve:
- Large differences in attacks or dangerous attacks
- Clear momentum imbalance
- One-sided possession or shot distribution
These situations are often modeled using difference-based rules or comparisons between teams.
Early dominance vs late reaction
Some strategies focus on how a match evolves over time rather than on raw totals.
Examples include:
- Strong activity early in the match that later fades
- Slow starts followed by increasing pressure
- Momentum shifts after a key event
These patterns are typically captured using time-based rules, comparing values from different periods of the match.
Pre-match strength vs live performance
A common analytical approach is to contrast expectations with reality.
For example:
- Strong pre-match indicators paired with weak in-play output
- Average pre-match data followed by unexpected live dominance
These strategies usually combine pre-match rules with in-play conditions to detect deviations from expected behavior.
Ranges instead of OR logic
Because rules inside a single strategy are always combined using AND logic, many patterns are expressed through ranges rather than explicit alternatives.
For example:
- Using a minimum and maximum value to capture several outcomes
- Bounding match time, score, or activity within a defined window
When a situation cannot be represented as a continuous range, it is usually better modeled as multiple strategies, each representing one logical branch.