Early-edition preview. 11th edition is only weeks old. The Index is live on Performance (tournament results), Practice (early expert tier lists), and Attention (community interest) — while Theory’s datasheet inputs are rebuilt for the new edition, so its column reads “no 11e data” and its weight slider stays inert. Samples are thin and the meta is unsettled: read the standings directionally, not as a verdict.
The Strength Index is one number per faction, but it is not a verdict. It is four independent signals — datasheet theory, tournament performance, practitioner consensus, and community attention — combined at weights you can see and change, with the uncertainty left visible rather than hidden. The single-number tier lists the methodology library takes apart collapse those signals into a confidence they have not earned; this page is the opposite move — the same signals, kept separate, measured, and adjustable.
We don’t collapse these to a single number. Theory, Performance, Practice, and Attention measure different things — what an army can do on paper, what it has done at tournaments, what top players think of it, and what the community is talking about. The disagreement between signals is the editorial product. Read across the row.
Theoretical ceiling from datasheet math (Unit Lab rollup).
Observed game outcomes from four sources — tournament play (Stat Check, Warpfriends, Archive’s own BCP pull) plus the broader TableTop Battles app dataset (40kstats). Equal-weight composite.
Curated top-player tier-list position.
Community discourse signal.
Every “Theory Z” number on this page is a comparison to all matched-play units across all factions in the current dataset. Zero is the population average. A unit at +1.0 is one standard deviation above average — roughly the top 16% of all units in the game on paper. +2.0 is the top 2–3%; exceptional. The scale works the same way going down: −1.0 is the bottom 16%, −2.0 the bottom 2–3%. These numbers measure what units should do against fixed reference targets — they do not predict tournament outcomes. A faction’s score is the average of its units’ z-scores; small-roster factions have less smoothing.
Each per-faction dossier shows two radar charts with five axes radiating out from the centre. The faction’s average performance against each target type (left chart) or against each threat type (right chart) is plotted as a point on each axis, and the points are connected to form a polygon. The inner pentagon marks the population average (0σ); rings move outward by one standard deviation each. A point past the +1σ ring means the faction performs meaningfully above average against that target or threat. The polygon’s SHAPE shows specialisation — pointy means strong in one direction and weak in others; broad and even means the faction has comparable capability across the board. A polygon that’s far from the centre overall (whether pointy or even) means a strong faction in that dimension; a polygon clustered near the centre means roughly average.
Pick a signal on the right. The X axis shows the composite z-score computed WITHOUT that signal — what the other three say collectively. The Y axis shows the selected signal alone. If the cloud lines up along a rising diagonal, the four-signal model cross-validates itself: each signal agrees with what the other three already point at. If the cloud is messy, the signals are genuinely independent — and the editorial product is in the off-diagonal factions.
The Strength Index used to publish a single tier-list ranking. It doesn’t any more. We argue against false-precision composites in the methodology library — Big Soup, Six Bins, and the upcoming Player or Army? and ELO Under Uncertainty articles each spell out a different reason a single number across these signals doesn’t survive scrutiny. So we don’t produce one. Each of the four columns measures a different thing with a different methodology.
Theory is theoretical ceiling computed from datasheet math: expected damage and durability per point, aggregated over a faction’s roster. Predictive but rollup-sensitive. Performance is what actually happens at tournaments — the closest we get to ground truth, with the well-known caveats (Big Soup, Six Bins, Player or Army?). While the structured Performance ingest is still pending, current per-faction win rates live on the three aggregators linked in the Performance column legend above. Practice is curated top-player impression, which captures expertise the data can’t but is biased by what each practitioner sees. Attention is community discourse signal — volume of conversation, which correlates loosely with strength and absolutely is not the same thing.
The forest plot above keeps an alphabetical row order on purpose so a single faction’s range bar can be tracked at a fixed Y position across weight changes; the breakdown table below picks up the composite-sorted ranking with STRONGER / AVERAGE / WEAKER zone headers and reshuffles live as the sliders move. The split is itself part of the methodology: the plot answers "where is this faction?", the table answers "who’s where under these weights?".
The Performance column shows observed game outcomes from four primary sources, equally weighted. Stat Check (≥24 players), Warpfriends (≥20 players), and the Archive’s own BCP pull (5+ rounds, no player floor) are tournament-only with different inclusion windows. 40kstats includes the broader TableTop Battles app dataset (tournament + casual games) over the Editor-set date window (currently the post-Defiler-patch window). Each source strikes its own trade between recency and sample size; the composite is the equal-weight mean across the four, treating each as a distinct methodological observation rather than four samples of one underlying meta. Sample-size weighting would let 40kstats’ larger sample dominate; equal-weight preserves each source’s voice and the inter-source disagreement that the methodology editorial What the Numbers Can Bear argues IS the editorial product. The composite CI is the between-source standard error — it widens when sources disagree, narrows when they converge. See the Big Soup methodology article for the full argument about pooled rates and what they hide.
When a faction-source cell has fewer than 80 games in the snapshot, a “READ WITH CARE” chip fires on the cell. Small samples produce wide Wilson CIs; the displayed number is the point estimate, but the underlying uncertainty may be substantial.
The Practice column aggregates editorial verdicts from five named expert tier-list publications (Art of War, Fireside 40k, Stat Check, Breaking Heads, Veizla). Per-publication tiers map to a numeric scale, then we recency-weight across in-window publications with a 60-day half-life and drop anything older than 180 days. Expert tier lists are practitioner-impression-shaped: top players see top matchups disproportionately, and “Faction X is bad” is often shorthand for “Faction X is bad against the current top two”. The per-faction tooltip surfaces the per-source breakdown so readers can audit the inputs; the small “n=N publications” caption under each cell shows how many publications contributed. Stat Check appears in both Performance (their published win rates) and Practice (their editor verdicts) — those are real but partially-overlapping signals from the same editorial team; readers may want to weight Practice down slightly to reflect that overlap.
The Attention column aggregates community discourse volume from two sources: Google Trends search interest and YouTube videos uploaded in the past seven days. Per-faction queries appear in the attention_faction_queries.json audit table so readers can inspect what was actually searched. Raw values are log-transformed before z-scoring because the loudest factions would otherwise dominate the composite at multi-sigma positions. Attention measures community focus, not faction strength — a faction loud on Trends could be dominant, recently nerfed, newly released, or the subject of a meme. Reddit was part of the original column design but is not currently in scope: Reddit’s self-serve API access was wound down in 2026 and the project is not pursuing paid alternatives at this time. Week-over-week change is often more informative than absolute level; a faction trending sharply up is a meaningful signal even at mid-pack volume.
All four columns carry real data. The most editorially valuable output on the page is the disagreement between columns. When columns agree, that’s confirming. When they disagree, that disagreement is the point — not a bug.
What gets populated when: