A nine-player main body and three sprinters. The sprinters hold the division's win-rates — but on the thinnest samples of any winners' cluster outside Div 8, and one of them carries the league's largest rating collapse. Div 7's structure is real; its magnitudes are provisional.
N = 12 players32 countries in playsource · ranked-system/progresssignal · ordinal (top/bottom 3)
Headline read
The US is Div 7's divider — six strengths against three weaknesses, the same pattern old Div 6 had. Russia is the shared weakness (five list it). And one profile inverts the whole league's shape: Aimbot is NMPZ-tilted (56.4% NMPZ over 43.9% moving) — the only player in nine divisions whose restricted game leads by that margin.
Data quality — Division 7
Three of twelve delisted (Icy3P, Portport, DayC19). NendWr's profile is the least stable in the division: seventeen moving games and a 554-point rating swing. Gleefulglacier has four NMPZ games on record.
00
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.
1269
mean seeded ELO
1042
mean current ELO
−227
seeded → current
3.1y
mean account age
17,772
total ranked duels
ELO distribution — seeded vs current
seeded (enrollment)current (seeded value where absent)
Seeded ratings average 1269; current form averages 1042 — the division sits 227 points below its enrollment ratings. 1 player carries 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.
Account age — a proxy for experience
Tick marks are individual players. Mean
~3.1 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 1,397 ranked duels.
01
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.
strengthweaknessnot in top/bottom 3
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.
02
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.
03
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
US — Icy3P, Gleefulglacier, Portport, DayC19, Arcuron, UmmAdam
ZA — Gleefulglacier, Sunset
MX — 46Raw, DayC19, Aimbot
AR — NendWr, Icy3P, Mr Cooliman
ID — Arcuron, Pudiedie
Common weaknesses
US — Aimbot, Pudiedie, Sunset
RU — Icy3P, Mr Cooliman, DayC19, Pudiedie, Sunset
AR — Arcuron, UmmAdam, Sunset
AU — Icy3P, Mr Cooliman
NG — Gleefulglacier, Mr Cooliman
Shared soft spots (2+)
US — Aimbot, Pudiedie, Sunset
RU — Icy3P, Mr Cooliman, DayC19, Pudiedie, Sunset
AR — Arcuron, UmmAdam, Sunset
AU — Icy3P, Mr Cooliman
NG — Gleefulglacier, Mr Cooliman
CO — DayC19, UmmAdam
CA — Gleefulglacier, Pudiedie
IT — Portport, Aimbot
IN — DayC19, UmmAdam
04
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.
Thin-sample sprinters
63.9%, 65.8% and 57.4% on 457, 351 and 728 duels. Portport's 79.8% moving is the sturdiest number of the three. NendWr's 94.1% moving rests on seventeen games, and his current rating has collapsed 554 points below enrollment — the largest fall in the league. Sunset arrives from seed 12 with a rising rating: the division's likeliest quiet overperformer.
NendWrPortportSunset
The main body
50–60% with most of the division's volume. Icy3P (59.7%) and Gleefulglacier (54.4%, current up 32) are its strongest residents; 46Raw holds seed 1 from inside it on a 50.8% record — a seeding built on the enrollment snapshot, not on outcomes.
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 (57% of the
variance): moving right means a higher lifetime win-rate, more uneven win-rates across modes and less ranked volume. PC2, the vertical axis
(18%): moving up means 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 75% 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 (DayC19+Arcuron) 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.
06
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
NendWr
Thin-sample sprinters
Lower rated
Portport
Thin-sample sprinters
Higher rated
Sunset
Thin-sample sprinters
Higher rated
46Raw
The main body
Higher rated
Aimbot
The main body
Higher rated
Arcuron
The main body
Lower rated
DayC19
The main body
Lower rated
Gleefulglacier
The main body
Higher rated
Icy3P
The main body
Higher rated
Mr Cooliman
The main body
Higher rated
Pudiedie
The main body
Higher rated
UmmAdam
The main body
Higher rated
What the divergences mean. Rare agreement: both models settle on the same two-band shape at k=2, each at its own best silhouette. They argue only at the edges — the ELO model drags DayC19 and Arcuron down alongside NendWr's collapsed rating, while the outcome model keeps both in the main body. Given NendWr's −554 is doing most of the pulling, the outcome model's placement is the more trustworthy here.
07
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.
