Filter Dimensions

The filtering system is organized into nine dimensions, ordered to match the Pillar 1 data model sequence. Each dimension addresses a distinct aspect of the query, and they combine using the composition rules described in Dimension Composition.

Dimension 1: Rating & Confidence

Filter games by community rating quality and reliability.

Notes:

• rating_min=7.0&min_rating_votes=1000 finds well-rated games with enough votes to be statistically meaningful.
• confidence_min=0.7 filters out games with unreliable ratings (brigaded, too few votes, or highly polarized). See the pre-release brigading case study for why this matters.
• Confidence captures what vote count alone cannot: a game with 500 votes and std dev 4.0 has low confidence despite a reasonable sample size.

Dimension 2: Weight (Complexity)

Filter games by their community-voted complexity score.

Notes:

• weight_min=2.0&weight_max=3.5 selects “medium weight” games – substantial decisions without being overwhelming.
• Weight is a community-voted value on a 1.0-5.0 scale. See Weight Model for the scale interpretation and known limitations.
• Games with fewer than a configurable threshold of weight votes (default: 30) can be excluded with min_weight_votes=30.

Dimensional Weight Filters (Implementation-Dependent)

Implementations that support the detailed weight mode may expose per-dimension filters:

These enable queries like “high strategic depth but low fiddliness” – separating good complexity from tedious bookkeeping. These parameters are optional – only available if the implementation collects dimensional weight data.

Dimension 3: Player Count

Filter games by how many people can play them.

Semantics:

Notes:

• players=4 means “supports exactly 4 players” – the game’s range includes 4.
• top_at=4 means “the community rates the 4-player experience highly.” This is a much smaller set than players=4. The threshold is implementation-defined (e.g., 4.0+/5).
• recommended_at=4 is broader than top_at=4 – it includes games where 4 is acceptable but not necessarily the sweet spot. The threshold is implementation-defined (e.g., 3.0+/5).
• players_min=3 returns games that require 3+ players (excludes solo and 2-player games). players_max=4 returns games that cap at 4 or fewer (excludes 5+ player games).
• Per-count ratings use the numeric model from ADR-0043. Legacy BGG three-tier data (Best/Recommended/Not Recommended) is converted to numeric ratings for filtering. See Player Count Model.

Dimension 4: Play Time

Filter games by how long they take to play.

Notes:

• playtime_max=90 with playtime_source=publisher matches games where the publisher’s max_playtime <= 90.
• playtime_max=90 with playtime_source=community matches games where community_max_playtime <= 90.
• You can use community_playtime_max directly instead of the playtime_source toggle for explicit control.
• When effective=true, play time considers expansion combinations. See Effective Mode.
• playtime_experience=first_play adjusts game times upward before comparison. A game with community max 90 min and a 1.5x first-play multiplier is treated as 135 min for filtering. This composes with playtime_source and effective=true: source is selected first, then expansion resolution, then experience adjustment, then comparison.

Dimension 5: Age Recommendation

Filter games by age appropriateness.

Notes:

• age_max=10 with age_source=publisher matches games where the publisher’s min_age <= 10.
• age_max=10 with age_source=community matches games where community_suggested_age <= 10.
• You can use community_age_max directly instead of the age_source toggle for explicit control.
• Publisher age recommendations tend to be conservative (see Age Recommendation Model). Community age data provides an alternative perspective based on actual play experience.

Dimension 6: Game Type & Mechanics

Filter by the game’s type discriminator and its mechanical classification.

Notes:

• type defaults to ["base_game", "standalone_expansion"] because most queries want playable games, not individual expansions or promos.
• mechanics=["cooperative", "deck-building"] matches games with cooperative OR deck-building (or both).
• mechanics_all=["cooperative", "hand-management"] matches games with BOTH cooperative AND hand-management.
• mechanics_not=["player-elimination"] excludes games with player elimination.
• These three mechanic parameters can be combined: mechanics_all=["cooperative"]&mechanics_not=["dice-rolling"] finds cooperative games that do not use dice.

Dimension 7: Theme

Filter by thematic setting.

Notes:

• theme=["fantasy", "mythology"] matches games themed around fantasy OR mythology.
• theme_not=["space"] excludes all space-themed games.
• Theme inclusion and exclusion can be combined: theme=["historical"]&theme_not=["war"] finds historical games that are not war-themed.

Dimension 8: Metadata

Filter by publication metadata and creators.

Notes:

• designer=["cole-wehrle"] finds all games by Cole Wehrle.
• year_min=2020&year_max=2025 finds games published in the 2020s.
• family=["pandemic"] finds all games in the Pandemic family, regardless of type.
• language_dependence=["no_text", "some_text"] finds games playable without significant language knowledge – useful for international groups or non-native speakers.

Dimension 9: Corpus & Archetype (Aspirational)

Filter by player population or behavioral archetype. This dimension is enabled by the Player entity and represents a fundamentally new kind of filtering: “what do players like me think?” rather than “what does the undifferentiated crowd think?”

Example queries:

• corpus=similar_to_player:01912f4c-a1b2&corpus_rating_min=4.0 – “games rated 4.0+ by players whose collection resembles mine”
• corpus=archetype:solo-gamer&top_at=1 – “games solo gamers rate highly at 1 player”

Status: This dimension is aspirational. The Player entity and archetype model define the data structures that make it possible, but the query syntax and implementation details are future RFC topics. Implementations may experiment with corpus-based filtering before the syntax is formally specified.

Sorting

Results can be sorted by:

Default sort is rating_desc.

Pagination

All filtered results are paginated using keyset cursors. See Pagination.