Solo Ranked Recon
Division 5
The league's most homogeneous division. The outcome model's best split here is the weakest primary separation anywhere (silhouette 0.29), because nine of twelve players are statistically adjacent — 51.6 to 56.2%. Div 5 also has the league's oddest top: seeds 1, 2 and 3 all carry sub-50 moving records. The top of this division was built in restricted modes.
Indonesia is Div 5's strength (five strong, two weak); Mexico its shared weakness (four list it). The structural headline: OceanicPrairie, Owen and Juri — the top three seeds — hold moving rates of 45.4%, 49.1% and 42.6%. Nominate moving against the top of this division; ban it when they hold the choice.
Starkily is delisted. Cameera's moving record is 12 games; OceanicPrairie's 45.4% moving is the number most worth verifying against live rounds before trusting. Everything else is adequately sampled.
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 1643; current form averages 1335 — the division sits 308 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 ~3.9 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 1,986 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
- ID — OceanicPrairie, Owen, Cameera, Starkily, Arpansarangi
- US — GeoMango, Starkily, Leo
- BR — OceanicPrairie, Owen, Leo
- IN — Juri, Arpansarangi, Leo
- ZA — Owen, Lirik, Dragon, PML
Common weaknesses
- US — OceanicPrairie, Owen, Dragon
- MX — Owen, Dragon, PML, Arpansarangi
- RU — Owen, Cameera, PML
- CL — OceanicPrairie, Cameera, GeoMango
- ES — OceanicPrairie, EvBeverage, Arpansarangi
Shared soft spots (2+)
- US — OceanicPrairie, Owen, Dragon
- MX — Owen, Dragon, PML, Arpansarangi
- RU — Owen, Cameera, PML
- CL — OceanicPrairie, Cameera, GeoMango
- ES — OceanicPrairie, EvBeverage, Arpansarangi
- CA — Juri, Dragon
- MY — Lirik, Leo
- ID — Lirik, EvBeverage
- TR — GeoMango, Starkily
- PE — PML, Leo
- AR — Cameera, Arpansarangi
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.
The only two lifetime rates that clear the pack: 59.7% and 63.8%, both on light volume (729 and 348 duels). Starkily is delisted, so the stronger of the two numbers is also the least verifiable.
Nine players inside five percentage points of each other. The differences that matter are inside the modes, not the totals: the NM-tilted top seeds noted above, and Owen's 1,755 km average distance — the division's widest — sustained across 5,705 duels.
The division's one sharp mode split: 70.2% moving against 51.6% NM and 47.4% NMPZ. In a division whose top seeds are moving-weak, PML holds the inverse profile — the most format-sensitive player in Div 5, in both directions.
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 (47% of the variance): moving right means a higher lifetime win-rate, less ranked volume and more uneven win-rates across modes. PC2, the vertical axis (29%): moving up means a restricted-mode lean, more even win-rates across modes 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 77% 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 (Dragon+Arpansarangi) 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 |
|---|---|---|
| GeoMango | Above the line | Higher rated |
| Starkily | Above the line | Higher rated |
| Arpansarangi | The undifferentiated middle | Lower rated |
| Cameera | The undifferentiated middle | Higher rated |
| Dragon | The undifferentiated middle | Mid rated |
| EvBeverage | The undifferentiated middle | Lower rated |
| Juri | The undifferentiated middle | Higher rated |
| Leo | The undifferentiated middle | Mid rated |
| Lirik | The undifferentiated middle | Higher rated |
| OceanicPrairie | The undifferentiated middle | Mid rated |
| Owen | The undifferentiated middle | Isolated |
| PML | The moving specialist | Mid rated |
What the divergences mean. Div 5 inverts the league's usual pattern: here the ELO model carries more structure (k=4, silhouette 0.328) than outcomes do. When results are this even, the live ladder does the differentiating. Its standout is Cameera — current 75 above enrollment, 58.1% NM, and twelve moving games in her entire recorded history. Form, or a profile the data simply hasn't measured yet; round results will say.
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.