Fern — CS2 Stats

76561198055486520[U:1:95220792]

194Tracked matches48%Win rate2020Tracked since

791Hours in CS

CSDB Rating6.8 SolidAggressive Rifler

Premier CS Rating21,072Pink band · top ~7.3% of ranked players (population est.)

CSDB Leaderboard#6426 of 16822 tracked

FaceitLevel 2Top 97.9% of ranked FACEIT players

WingmanGold Nova Master

Ladder ranks via Leetify

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Performance scores

Aim86

Positioning64

Utility48

0–100 skill scores via Leetify.

Recent form

STEADY49–45–6Last 10049%Win rateLWWLTWTWLL

Last 10 vs previous 10: +0pp win rate · +0.01 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim8.6

Aggression7.9

Utility4.8

Positioning6.4

Opening Duels3.5

Clutch0.0

Sharp aimerExcellent counter-strafingLimited utility dependence

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

Your pro match

Plays most like b1t 95% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

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

Strengths

Aim. Aim score of 86 — the mechanical foundation is a clear strength.

Areas to improve

Preaim. Mechanical aim is strong but the crosshair sits 10.6° off target when enemies appear — placement, not flicking, is the bigger win available.

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 587ms 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

Aim8.6

Positioning6.4

Utility4.8

Mechanics8.5

Opening Duels3.5

Win Impact4.4

Composite 6.8/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.03+0.01

first ⅓ avg 0.01 → last ⅓ avg 0.03

Reaction time601ms−29ms

first ⅓ avg 630ms → last ⅓ avg 601ms

Headshot accuracy26.7%+1.3%

first ⅓ avg 25.4% → last ⅓ avg 26.7%

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.

Highlights

0.24Best rating — boulder 13–2

13–0Biggest win — ancient

5Longest win streak

8–9In matches decided by ≤2 rounds

15Overtime games

Map breakdown

mirageBest map · 57% over 14dust2Weakest map · 36% over 11

Map	Grade	Played	Record	Win rate	Avg rating
ancient	B	21	10–11	48%	0.03
inferno	A	18	10–8	56%	0.02
mirage	A	14	8–6	57%	0.02
dust2	C	11	4–7	36%	-0.00
nuke	A	11	6–5	55%	0.04
anubis	B	11	5–6	45%	0.01
train	B	6	3–3	50%	0.04
cache	—	4	1–3	25%	0.04
boulder	—	1	1–0	100%	0.24
shelter	—	1	0–1	0%	0.03
fachwerk	—	1	1–0	100%	0.02
overpass	—	1	0–1	0%	0.10

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (36% over 11). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

39,546Lifetime kills

1.16K/D · Top 50% of Pink band

1,850Matches

47.2%Match win rate · Top 50% of Pink band

49.7%Headshot % · Top 50% of Pink band

16.9%Shot accuracy · Top 25% of Pink band

6,406MVPs

791Hours (in match)

2,360Bombs planted

456Bombs defused

Most-used weapons

AK-4713,093

M4A4 / M4A1-S7,272

P2000 / USP-S3,067

AWP3,003

P2502,183

Desert Eagle2,180

Glock-181,309

P901,235

Five-SeveN1,002

Tec-9642

Lifetime map wins

7,607dust2

1,883inferno

466nuke

324cbble

256train

203vertigo

13assault

12office

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

Faceit stats

Combat

230Matches

53%Win rate

1.32Avg K/D

82.8ADR

45%Headshot %

Clutches & streaks

0%1v1 clutch win

100%1v2 clutch win

7Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	2	100%	1.17	14.5
Vertigo	1	0%	1.14	24.0
Nuke	1	0%	1.53	29.0
Overpass	1	0%	0.94	15.0

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.

26.1%Headshot accuracy

38.2%Accuracy (enemy spotted)

39.7%Spray accuracy

88.4%Counter-strafing

10.6°Preaim

587msReaction time

42.0%T opening success

46.3%CT opening success

0.49Enemies flashed / flash

11.2%Flash assists

12.36HE damage / grenade

4.70Flashes / 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.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4944 — below the 0.5 mark we flag
Grenade Lineups →

Spend your practice time on Dust 2

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

36% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	6–13	-0.03	28%	27 Aug →
ancient	13–0	0.14	41%	27 Aug →
nuke	13–4	0.01	27%	27 Aug →
dust2	13–16	-0.03	25%	26 Aug →
ancient	15–15	-0.01	22%	19 Aug →
ancient	13–10	0.04	19%	19 Aug →
nuke	15–15	0.03	33%	19 Aug →
nuke	13–7	0.15	23%	19 Aug →
inferno	6–13	-0.03	30%	15 Aug →
ancient	9–13	0.02	25%	15 Aug →
anubis	8–13	-0.03	19%	14 Aug →
anubis	16–13	0.03	16%	14 Aug →
nuke	9–13	0.04	31%	13 Aug →
nuke	8–13	-0.03	32%	13 Aug →
dust2	13–10	0.05	35%	13 Aug →
ancient	13–11	0.05	18%	13 Aug →
inferno	5–13	-0.01	14%	13 Aug →
inferno	8–13	0.00	28%	11 Aug →
inferno	13–10	0.01	21%	11 Aug →
ancient	10–13	0.06	30%	11 Aug →
anubis	13–6	0.04	28%	11 Aug →
mirage	10–13	-0.04	16%	7 Aug →
cache	6–13	0.05	36%	7 Aug →
inferno	13–11	0.01	21%	5 Aug →
ancient	10–13	0.03	24%	5 Aug →
dust2	15–15	-0.01	27%	5 Aug →
ancient	13–6	0.10	33%	5 Aug →
dust2	13–4	0.13	26%	4 Aug →
cache	11–13	0.03	27%	4 Aug →
nuke	13–9	0.05	38%	4 Aug →
mirage	15–15	0.03	28%	4 Aug →
ancient	9–13	-0.03	22%	4 Aug →
dust2	13–9	0.01	37%	2 Aug →
inferno	13–2	-0.00	30%	2 Aug →
mirage	13–7	0.08	24%	2 Aug →
anubis	11–13	-0.03	28%	1 Aug →
cache	4–13	0.05	30%	1 Aug →
nuke	13–10	0.01	25%	1 Aug →
mirage	7–13	-0.06	31%	30 Jul →
mirage	13–5	0.03	26%	30 Jul →
dust2	16–13	0.06	26%	30 Jul →
anubis	13–7	0.07	18%	26 Jul →
boulder	13–2	0.24	19%	26 Jul →
cache	13–8	0.05	20%	26 Jul →
shelter	8–13	0.03	23%	26 Jul →
fachwerk	13–9	0.02	22%	26 Jul →
ancient	13–7	0.07	28%	26 Jul →
inferno	8–13	0.08	25%	26 Jul →
inferno	5–0	0.11	10%	26 Jul →
overpass	12–12	0.10	28%	26 Jul →
nuke	13–9	0.12	46%	26 Jul →
dust2	13–16	-0.04	24%	18 Jul →
ancient	16–14	0.02	31%	27 Jun →
dust2	11–13	-0.06	16%	27 Jun →
mirage	13–8	-0.05	21%	26 Jun →
mirage	13–10	0.07	35%	9 Sept →
train	11–13	0.00	26%	26 Jul →
mirage	4–13	-0.03	37%	20 Jul →
inferno	13–11	-0.02	38%	20 Jul →
ancient	10–13	0.02	27%	20 Jul →
inferno	14–16	0.03	27%	12 Jul →
train	16–14	-0.01	19%	12 Jul →
mirage	16–12	-0.03	28%	12 Jul →
train	6–13	0.06	26%	11 Jul →
mirage	13–8	0.12	29%	11 Jul →
anubis	13–6	0.05	10%	11 Jul →
inferno	13–10	0.04	25%	11 Jul →
ancient	9–13	-0.01	20%	10 Jul →
ancient	16–13	-0.05	33%	10 Jul →
inferno	10–13	0.01	19%	10 Jul →
mirage	13–7	0.12	21%	9 Jul →
anubis	9–13	-0.04	13%	9 Jul →
train	13–5	0.06	26%	9 Jul →
dust2	11–13	-0.04	28%	9 Jul →
anubis	13–4	0.03	31%	5 Jul →
inferno	11–13	0.02	22%	5 Jul →
ancient	11–13	0.02	14%	3 Jul →
mirage	13–5	0.12	30%	3 Jul →
inferno	13–6	0.10	28%	3 Jul →
anubis	5–13	-0.01	18%	3 Jul →
inferno	13–11	-0.01	27%	2 Jul →
ancient	13–7	-0.01	13%	2 Jul →
anubis	10–13	0.02	32%	2 Jul →
ancient	13–9	0.06	24%	1 Jul →
nuke	4–13	-0.03	24%	1 Jul →
train	13–7	0.00	20%	1 Jul →
nuke	9–13	0.02	25%	1 Jul →
mirage	7–13	-0.02	25%	1 Jul →
anubis	7–13	-0.04	32%	30 Jun →
ancient	16–14	0.10	39%	30 Jun →
ancient	15–15	-0.01	25%	30 Jun →
train	8–13	0.11	37%	30 Jun →
ancient	11–13	-0.03	30%	30 Jun →
dust2	2–13	-0.10	23%	30 Jun →
inferno	13–10	0.02	26%	30 Jun →
mirage	5–13	-0.03	31%	30 Jun →
inferno	7–13	-0.07	26%	30 Jun →
ancient	8–13	-0.00	30%	29 Jun →
inferno	13–11	0.10	22%	26 Jun →
nuke	13–8	0.03	26%	26 Jun →