Solo Ranked Recon
Division 3
A two-speed division. Five players win on moving — all five clear 70% there, one clears 96 — and seven players are mode-flat grinders who concede nothing and take nothing. In restricted modes the whole division compresses to near-parity, which makes format choice worth more here than anywhere else in the league.
Russia is Div 3's true divider — simultaneously the most-listed strength (four players) and the most-listed weakness (five). Indonesia leans weakness (two strong, five weak). Structurally: every one of the division's five winners is a moving specialist whose restricted rates fall back to 46–58%.
Full current-rating coverage; alongside 1B the cleanest division. tacocat's 96.7% moving sits on a modest total sample (960 lifetime duels) — read it as a strong tilt, not a law of nature.
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 1900; current form averages 1531 — the division sits 368 points below its enrollment ratings. Every player carries a live current rating, so no imputation is involved. The axis is scaled to this division's own range.
Tick marks are individual players. Mean ~5.4 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 2,789 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
- AU — RLH, Burgo, tacocat
- US — RLH, koendew, Stingray
- RU — PLAYHRD, JoeySpeeltGames, Burgo, Matepotato
- FR — Causey, Quarksauce
- ZA — JoeySpeeltGames, koendew
Common weaknesses
- RU — RLH, Slam4, Stingray, Kiquke, tacocat
- BR — Quarksauce, JoeySpeeltGames, koendew, Matepotato
- ID — RLH, JoeySpeeltGames, koendew, Stingray, Kiquke
- US — JoeySpeeltGames, Matepotato
- UA — Causey
Shared soft spots (2+)
- RU — RLH, Slam4, Stingray, Kiquke, tacocat
- BR — Quarksauce, JoeySpeeltGames, koendew, Matepotato
- ID — RLH, JoeySpeeltGames, koendew, Stingray, Kiquke
- US — JoeySpeeltGames, Matepotato
- CA — Causey, Stingray
- ES — RLH, PLAYHRD
- MX — Quarksauce, Matepotato
- IN — Quarksauce, Kiquke
- ZA — PLAYHRD, Slam4
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.
51–54% in every mode, samples of 1,300–6,000. No edge to press, no hole to attack — games against this group are decided by the day's form and the map. Causey heads the seeding from inside it, which is examined below.
All five clear 70% moving — tacocat's 96.7% is the most extreme mode figure in the league — and all five fall to 46–58% restricted. RLH's split is the widest that matters: 70.4% moving against 46.4% NM. If you can drag any of these five into NM or NMPZ, the fight is even; on moving it is not.
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 (53% of the variance): moving right means a restricted-mode lean, more even win-rates across modes and a lower lifetime win-rate. PC2, the vertical axis (23%): moving up means a wider average guess distance and a higher current rating. 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 76% 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 (PLAYHRD+koendew) 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 |
|---|---|---|
| Burgo | Mode-flat grinders | Mid rated |
| Causey | Mode-flat grinders | Lower rated |
| Kiquke | Mode-flat grinders | Lower rated |
| PLAYHRD | Mode-flat grinders | Isolated |
| Slam4 | Mode-flat grinders | Mid rated |
| Stingray | Mode-flat grinders | Mid rated |
| koendew | Mode-flat grinders | Mid rated |
| JoeySpeeltGames | Moving specialists | Mid rated |
| Matepotato | Moving specialists | Mid rated |
| Quarksauce | Moving specialists | Mid rated |
| RLH | Moving specialists | Mid rated |
| tacocat | Moving specialists | Isolated |
What the divergences mean. The ELO model at its preferred k=5 splinters the division and, in doing so, points at the two form stories the win-rate model can't date: PLAYHRD, isolated with a current of 2019 — the only player above 2000, up 109 on enrollment — and tacocat, seed 12, current up 56, with that 96.7% moving rate. Meanwhile Causey holds seed 1 on an enrollment snapshot while carrying a 51.0% lifetime rate and the division's weakest moving number (45.7%). On the evidence assembled here, that is the most pressured top seed in the league.
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.