Princess Fjällborren

Princess Fjällborren — CS2 Stats

SE76561198172195065[U:1:211929337]Steam profile ↗✓ No bans

1,055Tracked matches40%Win rate2020Tracked since
2,614Hours in CS
CSDB Rating5.7 SolidSupport
WingmanLegendary Eagle
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 7 Sep 2026 (39 days ago). Ranks are recorded once per day this page is viewed.

0Faceit ELO · 2,041 → 2,041
+12Tracked matches · now 1,055
0.0ppWin rate · 40.0% → 40.0%

Rating over time

Premier CS Rating: 17,512 +1,589 20 Nov – 18 Jan · 25 days played
14,53917,998peak 17,99820 Nov18 Jan
18,190Peak Premier in tracked matches
2,041Highest Faceit ELO seen on CSDB
40Days played since 2025-11-20

Faceit ELO

  • At peak — 2,041
  • Next: 2,500 ELO at 2,500 — 459 to go
  • Reached: Level 10 · Level 9 · Level 8 · Level 7
  • Level 10 first seen 2026-09-07
  • Level 9 first seen 2026-09-07

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

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CSDB.GGPrincess FjällborrenPEAK ELO2,041csdb.gg/stats

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Performance scores

Aim83
Positioning45
Utility55

0–100 skill scores via Leetify.

Recent form

COLD44–54–2Last 10044%Win rateLWLLLLTWLW

Last 10 vs previous 10: −20pp win rate · −0.01 avg rating · +0.6pp headshot accuracy · +24ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 26%
  • Avg reaction 631ms

Last 10

  • 3–6–1 · 30% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 30%
  • Avg reaction 591ms

Last 20

  • 8–11–1 · 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 30%
  • Avg reaction 579ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Support — Utility contribution stands above the rest of this profile (+1.8 against its own average).

Aim8.3
Utility5.5
Positioning4.5
Opening Duels1.4
Clutch3.4

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

Twistzz

Plays most like Twistzz 92% playstyle similarity

Most alike: aim profile, positioning profile.

Where you differ: lower utility contribution; lower opening-duel success.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

Strengths & areas to improve

Areas to improve

Positioning. Positioning trails aim by 38 points — deaths here waste a strong aim profile.

Reaction time. 592ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim8.3
Positioning4.5
Utility5.5
Mechanics7.8
Opening Duels1.5
Win Impact1.7

Composite 5.7/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.05
first ⅓ avg 0.03 → last ⅓ avg -0.02
Reaction time583ms−19ms
first ⅓ avg 602ms → last ⅓ avg 583ms
Headshot accuracy29.3%−2.5%
first ⅓ avg 31.7% → last ⅓ avg 29.3%

Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.19Best match rating · 13–9 · dust2, 1 Dec →
50%Best headshot accuracy · 9–13 · mirage, 3 Dec →
391msFastest reaction time · 5–13 · ancient, 13 Jan →
13–1Biggest win · overpass, 20 Nov →

Across the last 100 tracked matches.

Highlights

4Longest win streak
6–7In matches decided by ≤2 rounds
7Overtime games

Map breakdown

overpassBest map · 71% over 7infernoWeakest map · 21% over 14
MapGradePlayedRecordWin rateAvg rating
dust2C218–1338%0.01
mirageC208–1240%0.01
infernoD143–1121%0.03
ancientA127–558%-0.01
nukeD93–633%0.00
overpassS75–271%0.00
trainA53–260%0.05
anubis—32–167%0.03
office—21–150%-0.02
boulder—10–10%0.08
cache—10–10%-0.03
eldorado—10–10%-0.09
debris—11–0100%-0.05
cache_b—11–0100%-0.00
italy—11–0100%-0.03
palacio—11–0100%-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (21% over 14). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

143,728Lifetime kills
1.09K/D · Top 50% of tracked players
6,804Matches
44.4%Match win rate
50.9%Headshot % · Top 25% of tracked players
20.0%Shot accuracy · Top 5% of tracked players
16,994MVPs
2,614Hours (in match)
5,165Bombs planted
1,787Bombs defused

Most-used weapons

AK-4760,847
AWP9,241
FAMAS2,984
Knife1,511

Lifetime map wins

7,246inferno
4,008vertigo
3,950dust2
3,590cbble
3,221nuke
2,700train
417office
408lake

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

315Matches
56%Win rate
1.11Avg K/D
85.8ADR
51%Headshot %

Clutches & streaks

37%1v1 clutch win
23%1v2 clutch win
10Longest win streak

Recent Faceit resultsLWWLL

MapMatchesWin rateAvg K/DAvg kills
Inferno2966%1.0915.6
Overpass2979%1.1719.4
Ancient2462%1.0617.8
Train2458%1.2017.2
Nuke2438%0.9917.3
Mirage1872%1.2115.9
Dust21833%1.0518.8
Vertigo560%1.2018.2

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

28.8%Headshot accuracy
32.7%Accuracy (enemy spotted)
40.4%Spray accuracy
85.0%Counter-strafing
10.0°Preaim
592msReaction time
33.2%T opening success
39.0%CT opening success
0.68Enemies flashed / flash
6.4%Flash assists
8.63HE damage / grenade
8.36Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.

  1. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 33.1624% — below the 40% mark we flag

Spend your practice time on Inferno

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

21% win rate across 14 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis2–13-0.078%25 Sept →
dust213–60.0132%24 Sept →
inferno6–13-0.0219%18 Sept →
dust27–130.0331%15 Sept →
boulder4–130.0839%15 Sept →
cache5–13-0.0336%12 Sept →
eldorado8–8-0.0922%12 Sept →
debris9–4-0.0546%12 Sept →
ancient9–13-0.0439%12 Sept →
dust213–6-0.0127%12 Sept →
inferno13–60.0421%11 Sept →
dust25–130.0037%23 Jul →
nuke13–80.0239%5 Jul →
ancient3–13-0.0212%5 Jul →
ancient13–90.0133%9 May →
overpass10–13-0.0127%9 May →
mirage1–13-0.0727%21 Mar →
office10–13-0.0927%21 Mar →
office13–110.0641%23 Jan →
mirage13–80.0131%23 Jan →
overpass13–11-0.0420%18 Jan →
dust27–13-0.0919%18 Jan →
ancient13–10-0.0038%18 Jan →
mirage13–20.0243%16 Jan →
overpass13–5-0.0816%15 Jan →
dust21–13-0.0138%15 Jan →
inferno5–130.0130%15 Jan →
nuke9–13-0.0447%15 Jan →
ancient5–13-0.0824%13 Jan →
dust29–13-0.1117%12 Jan →
nuke6–13-0.0217%12 Jan →
mirage13–9-0.0222%11 Jan →
cache_b13–11-0.0039%10 Jan →
ancient7–13-0.0124%10 Jan →
nuke6–13-0.0246%9 Jan →
overpass11–130.0128%9 Jan →
dust216–13-0.0018%9 Jan →
mirage17–190.0325%5 Jan →
inferno14–160.0317%4 Jan →
train13–110.0126%4 Jan →
dust210–130.0929%4 Jan →
ancient7–13-0.0310%3 Jan →
mirage13–110.0731%3 Jan →
mirage13–100.0423%2 Jan →
dust28–13-0.0031%2 Jan →
dust213–8-0.0221%2 Jan →
inferno13–70.0332%2 Jan →
dust26–130.0625%1 Jan →
inferno8–130.0334%1 Jan →
mirage13–60.1323%30 Dec →
overpass13–30.0225%30 Dec →
inferno15–150.1122%30 Dec →
dust212–16-0.0115%30 Dec →
train6–13-0.0341%30 Dec →
overpass13–70.0222%30 Dec →
ancient13–10-0.0417%28 Dec →
inferno5–130.1322%25 Dec →
dust29–13-0.0744%25 Dec →
inferno10–13-0.0241%25 Dec →
nuke13–70.0036%18 Dec →
mirage10–130.0229%8 Dec →
dust213–70.0129%8 Dec →
ancient13–60.0131%8 Dec →
mirage13–11-0.0136%8 Dec →
ancient13–100.0232%7 Dec →
nuke4–9-0.0836%7 Dec →
inferno9–50.0017%7 Dec →
mirage11–130.0726%4 Dec →
nuke11–130.1038%4 Dec →
mirage0–13-0.0936%4 Dec →
mirage10–13-0.0328%4 Dec →
inferno13–16-0.0224%4 Dec →
mirage9–130.0250%3 Dec →
train8–130.1231%3 Dec →
inferno6–13-0.0429%3 Dec →
train13–30.1149%3 Dec →
dust24–130.0532%3 Dec →
mirage13–60.0627%2 Dec →
nuke7–13-0.0234%2 Dec →
inferno11–130.0328%2 Dec →
inferno13–160.0628%1 Dec →
mirage2–13-0.0127%1 Dec →
dust27–130.0129%1 Dec →
anubis13–20.1046%1 Dec →
dust213–90.1930%1 Dec →
mirage8–130.0925%1 Dec →
italy13–6-0.0323%1 Dec →
anubis13–90.0430%30 Nov →
nuke13–100.0525%26 Nov →
dust211–130.0232%24 Nov →
ancient13–80.0631%24 Nov →
mirage10–13-0.0443%22 Nov →
dust213–30.0235%22 Nov →
dust213–70.0339%21 Nov →
mirage8–13-0.0522%21 Nov →
mirage10–130.0229%20 Nov →
ancient13–20.0720%20 Nov →
palacio13–7-0.0432%20 Nov →
overpass13–10.1137%20 Nov →
train13–50.0333%20 Nov →

Match data via Leetify.

Recent teammates

Milestones

2K ELO1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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