Big Blind Aggression Frequency (BB AFq)

Overview

BB AFq (Big Blind Aggression Frequency) is an advanced statistic commonly used in poker data analysis, specifically tracking a player's behavior from the Big Blind position. It measures how often a player chooses to bet or raise (rather than check or call) after entering the flop. Expressed as a percentage, a higher value indicates that the player tends to be more aggressive in defending or contesting the pot from the BB.

Calculation

Generally, AFq is calculated using the formula:

• (Number of Bets + Number of Raises) ÷ (Number of Bets + Number of Raises + Number of Checks + Number of Calls) × 100% In specific tools (e.g., Hold'em Manager, PokerTracker), the denominator excludes folds and only considers opportunities where the player has a decision (i.e., facing a bet, the player can raise, call, or fold, but AFq only cares about aggressive actions among non-fold decisions). Therefore, AFq differs from Aggression Factor (AF), which is (Bets + Raises) / (Checks + Calls). AFq is a percentage-based frequency metric.

Application

BB AFq is mainly used to evaluate an opponent's defensive style from the Big Blind. The Big Blind is the worst position in the game, as players must face continuation bets from the preflop raiser. A high BB AFq (e.g., over 50%) indicates that the player frequently donk-bets or raises postflop, possibly exploiting the BB's range advantage for bluffs or value raises. A low BB AFq (e.g., below 30%) suggests the player employs a more check-call defensive strategy, preferring to see cards passively.

Notes

• AFq data requires a sufficient sample size to be statistically meaningful (at least 100 postflop BB decisions is recommended).
• Different playing styles affect normal variance; a single number should not be viewed in isolation but combined with other stats (e.g., VPIP, PFR, Fold to C-bet) for a comprehensive assessment.
• Some software may use different calculation methods; confirm the specific definition when using.