Scoring rate filter: over and under hit rate

What the scoring rate filter does

The filter evaluates one scoring condition over a team's last N matches: the dimension (goals scored, conceded, or the match total), a threshold on the sport's scoring grid, and an at-least or below comparison. It then computes how often the condition was met and keeps the matchup when that share clears your minimum. "Under 2.5 hit in at least 70 percent of the last 10" is a scoring rate; it tolerates the occasional outlier match in a way a scoring streak cannot.

Hit rate versus average: why it matters

An average hides distribution. A team averaging 2.6 goals per match might score steadily around 2 and 3, or alternate 0-0 stalemates with 6-goal blowouts, and those two profiles behave completely differently against a totals line. The hit rate speaks the bettor's language directly: it estimates how often a specific line would have cashed. When you bet over 2.5, what you care about is precisely the share of matches clearing 3 goals, and that is the number this filter thresholds. For the mean-based view, use goals average instead; the two together describe both level and consistency.

Example strategies

• Keep teams whose matches went over 2.5 goals at least 70 percent of the time in the last 10, then price-check the overs with an odds range.
• Build an unders system on teams conceding under 1 goal in 80 percent of recent matches, isolating genuinely locked-down defenses.

Combining it with other filters

Scoring consistency gains meaning inside a context: scope it with a league filter since baseline scoring varies by competition, and confirm the profile with BTTS rate in soccer or hockey when the angle involves both teams scoring. This is a Pro filter.

A hit rate is a testable claim about how often a line cashes, so test it: run the rule through backtesting on years of Pinnacle historical odds. Set your threshold and backtest it in the Strategy Builder now.