Search Statistics

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Search statistics refers to counting various appearances of interest inside the search or evaluation routines and to analyze their relationships to eventually spot bugs or unfavorable conditions in move ordering.

Node Statistics

Of interest is the appearance of searched nodes inside an iterative deepening framework and the ratio of quiescent nodes, per depth and/or aggregated, in conjunction with effective branching factor (EBF) and of course nodes per second.


Inside Alpha-beta- or PV-search it is of particular interest to count how often a node failes high or not, in relation to its node types, that is expected cut-Nodes or expected All-nodes. If a fail-high occurs, it is illuminative to know whether the fail-high move it was tried first, early or late and what move ordering classification like move from the transposition table, winning captures, killer moves, etc. was applied.


At PV-nodes inside a alpha-beta- or PV-search the number of re-searches does concern, and how often a re-search does improve alpha (or even performs a cutoff) or not.

Root Statistics

The Root as distinguished PV-node specially with aspiration window often has its own statistics related to how much relative time (nodes) of the whole iteration is performed per each root-move, and how often another best move was found. In conjunction with static move properties, score graph by searched depth so far, etc., these statistic based informations may be considered in time management to possibly decide about a new iteration.


Counting the various extensions, reductions and forward pruning decisions in relation with effective branching factor might also spot some deficiency inside the search.

TT Statistics

Statistics of the transposition table covers number of probes and stores, fill level, and number of probe hits, likely differentiated by sufficient draft and type of stored node.

See also


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