Solo Ranked Recon
Division 4
The parity division. Nine of twelve occupy one statistical band — 51–54% lifetime, no meaningful mode splits — the tightest large cluster in the league. Three players sit above it, and two of those three are delisted, so the division's top shelf is half-dark on current form.
Brazil splits Div 4 nearly down the middle: five list it a strength, six a weakness — the most contested country anywhere in the league. Russia is where the division wins (six strong, one weak).
Two of the three top-cluster players (mrjohnboy, derflipster) are delisted. Ades' 77.8% moving rests on 27 games. dawae's overall win-rate is treated as unreliable per the note above.
State of the field
A snapshot before the detail: where the twelve sit on rating, experience and volume. The headline is the gap between seeded and current form — this is a field well off its collective best.
Seeded ratings average 1774; current form averages 1402 — the division sits 372 points below its enrollment ratings. 2 players carry no live rating, so a seeded value stands in; the current curve is, if anything, flattered. The axis is scaled to this division's own range.
Tick marks are individual players. Mean ~4.1 years, but read it loosely: account age is only a proxy for GeoGuessr experience, and it breaks for fresh accounts of veteran players. Median lifetime volume is 2,729 ranked duels.
Geographic signal map
Every player against every country that appears in a top-3 or bottom-3 list. Warm = a ranked strength, cool = a ranked weakness, intensity = list position. Columns are ordered by how much the field cares about that country. Hover any cell for the value.
Ordinal signal only: a blank cell means the country isn't in that player's top or bottom three — not that they're necessarily neutral there.
Contested ground
Countries that are a strength for some players and a weakness for others — the regions where a matchup is won or lost rather than shared.
Field patterns
Where the field collectively excels and bleeds. Shared weaknesses are the soft ground worth drilling — common blind spots across skill tiers.
Common strengths
- RU — LG, Ades, ra1n, BluebSON, Snatzy, derflipster
- BR — Ades, BluebSON, derflipster, Lao, Flixbus
- AR — Ades, GeoSynxzy, dawae, Lao
- CA — mrjohnboy, BluebSON, FilipVibeGuessin
- AU — mrjohnboy, GeoSynxzy
Common weaknesses
- BR — LG, mrjohnboy, ra1n, Snatzy, GeoSynxzy, FilipVibeGuessin
- US — LG, BluebSON, GeoSynxzy, Flixbus
- ID — mrjohnboy, Snatzy, dawae, FilipVibeGuessin
- MY — LG, Ades
- AR — ra1n, derflipster
Shared soft spots (2+)
- BR — LG, mrjohnboy, ra1n, Snatzy, GeoSynxzy, FilipVibeGuessin
- US — LG, BluebSON, GeoSynxzy, Flixbus
- ID — mrjohnboy, Snatzy, dawae, FilipVibeGuessin
- MY — LG, Ades
- AR — ra1n, derflipster
- MX — GeoSynxzy, dawae, Lao
Player clusters — win-rate model
Our primary segmentation, built on lifetime per-mode win-rates over hundreds-to-thousands of ranked duels per player — measured outcomes, not imputed ratings, so no synthetic data props it up. Features: current ELO, lifetime overall and per-mode win-rate, a win-rate-derived mode lean, accuracy and volume. Ward and k-means agree. Two players resolve as singletons for real reasons (below). A second, rating-based model in section 06 triangulates this one. At n=12 these are reading aids, not hard tiers — silhouette ≈ 0.31, a real but soft structure.
57–59% overall. Flixbus arrives from seed 12 with an 81.9% moving rate — the latest instance of this league's recurring pattern, the under-seeded moving specialist. mrjohnboy's edge is the opposite shape: 62.4% NM, the division's best restricted number. Both he and derflipster are delisted, so current form is unverifiable.
Nine players, 51–54%, mode-flat. Within-pack notes: FilipVibeGuessin and GeoSynxzy carry moving tilts (68.7%, 61.7%) that the overall numbers hide, and LG's 1,412 km average distance is the group's accuracy floor. dawae's register line is internally inconsistent — see the caveat below.
How to read the two cluster views
The clustering runs in a 6-dimensional feature space; these two plots are different windows onto it. The PCA map flattens that space to its two most informative axes; the dendrogram shows the order in which players merged into groups. Same data, complementary views.
PCA map. Each player projected onto the two directions of greatest spread in this division's data. A principal component has no fixed meaning — it is whatever mix of the six features varies most here — so the axis readings below are derived from this division's own loadings, not carried over from any other division. PC1, the horizontal axis (45% of the variance): moving right means more uneven win-rates across modes, a higher current rating and a moving-mode lean. PC2, the vertical axis (26%): moving up means more ranked volume, a wider average guess distance and a moving-mode lean. Two of the six features deserve definition, since both are computed from win-rates rather than from how often a mode is played: mode lean = mean(NM%, NMPZ%) − Moving%, i.e. which way a player's results tilt; mode spread = the standard deviation across their three mode win-rates, i.e. how lopsided they are regardless of direction. A player who wins 74/75/71 across the modes and one who wins 49/52/47 both score flat on these; a 65/54/33 profile scores strongly on both. Distance on the plot ≈ overall dissimilarity. Together the two axes hold 71% of the variance in the six clustering features.
Dendrogram. Built bottom-up: each player starts alone, then the two most similar join, repeatedly, until all are one. Bar height = how different two groups were when they merged — low joins (Ades+Snatzy) are near-twins; high joins happen late and grudgingly. Reading down from the top, the first split separates the strong tier from everyone else; cut the tree at any height to get that many clusters. Dot colour marks final cluster membership.
Two models, triangulated
We trust two models, built on independent signals. The win-rate model (section 04) asks who beats their opponents, from measured lifetime outcomes. The ELO model asks where the ladder places them now, from current per-mode ratings with mode-lean computed only from real (non-imputed) data — the honest rating view, silhouette 0.29. Where they agree, a finding is robust; where they diverge, that disagreement is itself signal worth a second look.
| Player | Win-rate model | ELO model |
|---|---|---|
| Flixbus | The three above | Lower rated |
| derflipster | The three above | Higher rated |
| mrjohnboy | The three above | Higher rated |
| Ades | The pack | Higher rated |
| BluebSON | The pack | Mid rated |
| FilipVibeGuessin | The pack | Lower rated |
| GeoSynxzy | The pack | Mid rated |
| LG | The pack | Mid rated |
| Lao | The pack | Lower rated |
| Snatzy | The pack | Mid rated |
| dawae | The pack | Higher rated |
| ra1n | The pack | Higher rated |
What the divergences mean. The ELO model scatters the pack into four sub-groups the outcome data gives no reason to believe — with nine players this evenly matched, current-rating noise creates structure that isn't there. Trust the two-band read. One register flag: dawae shows 26.6% overall against 53–61% in every individual mode, which is arithmetically impossible for the same pool of games — almost certainly a capture artefact in the overall field. His per-mode numbers are the credible ones.
Geographic similarity
Where each player's competence is concentrated — thread weight is the overlap in best-country lists. GeoGuessr ranks these countries within each player, so the lists say where someone is strong relative to their own baseline, not how strong they are.
Reading it
Thick threads mean two players' strengths sit in the same places — on a map drawn from those countries, neither gets an edge from familiarity. Thin or absent threads mean their competence is concentrated elsewhere, so map choice cuts between them. Because each player's top-3 is ranked against their own record, this maps the shape of a player's geographic knowledge with their overall level divided out: a Division 8 player and a Division 1 player can share a thread while being nowhere near each other in strength. It is a map of where someone is strong, not how strong they are — which is why it is kept separate from the clustering, and why a thread is a matchup cue rather than a prediction.