nenQ*BIG BOOTY ENJOYER — CS2 Stats

76561198092316680[U:1:132050952]✓ No bans

424Tracked matches45%Win rate2020Tracked since

CSDB Rating6.0 SolidPassive Rifler

Premier CS Rating21,712Top 50% of 17,162 CSDB-tracked playersPink band · top ~6.6% of ranked players (population est.)

FaceitLevel 8 · 1,661 ELOTop 31.2% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim88

Positioning33

Utility52

0–100 skill scores via Leetify.

Recent form

COLD57–37–6Last 10057%Win rateLLWLWLLLTW

Last 10 vs previous 10: -20pp win rate · -0.02 avg rating

Player DNA

Primary style: Passive Rifler — Aim-led profile without a single dominant tendency.

Aim8.8

Aggression4.0

Utility5.2

Positioning3.3

Opening Duels0.0

Clutch5.6

Sharp aimerExcellent counter-strafing

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 NiKo 86% playstyle similarity

Most alike: aim profile, opening-fight frequency.

Where you differ: lower opening-duel success; lower positioning profile.

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 88 — the mechanical foundation is a clear strength.

Counter-strafing. 91% of shots taken properly stopped — movement discipline most players never reach.

Areas to improve

Positioning. Positioning trails aim by 55 points — deaths here waste a strong aim profile.

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

Reaction time. 607ms 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

Aim8.8

Positioning3.3

Utility5.2

Mechanics9.1

Opening Duels0.8

Win Impact3.3

Composite 6.0/10 (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 rating-0.00−0.02

first ⅓ avg 0.02 → last ⅓ avg -0.00

Reaction time566ms−73ms

first ⅓ avg 639ms → last ⅓ avg 566ms

Headshot accuracy27.5%−1.1%

first ⅓ avg 28.6% → last ⅓ avg 27.5%

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

0.27Best rating — mirage 9–0

13–0Biggest win — mirage

7Longest win streak

L2Current streak

7–5In matches decided by ≤2 rounds

5Overtime games

Map breakdown

infernoBest map · 77% over 13mirageWeakest map · 41% over 17

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	19	12–7	63%	0.01
cache	B	18	9–9	50%	0.01
mirage	C	17	7–10	41%	0.02
inferno	S	13	10–3	77%	0.02
anubis	B	11	5–6	45%	0.00
nuke	A	8	5–3	63%	-0.00
vertigo	S	6	4–2	67%	0.02
ancient	A	5	3–2	60%	0.02
train	—	2	1–1	50%	-0.02
overpass	—	1	1–0	100%	-0.02

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (41% over 17). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

127Matches

62%Win rate

1.52Avg K/D

86.8ADR

57%Headshot %

Clutches & streaks

48%1v1 clutch win

32%1v2 clutch win

7Longest win streak

Recent Faceit resultsLWLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	47	66%	1.62	18.0
Dust2	26	69%	1.51	16.5
Ancient	21	43%	1.36	17.7
Inferno	16	69%	1.60	20.0
Nuke	9	67%	1.27	15.1
Overpass	3	33%	1.27	20.3
Vertigo	2	50%	1.47	19.0
Anubis	2	50%	1.46	18.0

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.

28.5%Headshot accuracy

32.3%Accuracy (enemy spotted)

39.6%Spray accuracy

91.1%Counter-strafing

7.8°Preaim

607msReaction time

21.5%T opening success

36.2%CT opening success

0.54Enemies flashed / flash

8.6%Flash assists

3.96HE damage / grenade

15.78Flashes / 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.

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 21.4668% — below the 40% mark we flag

Spend your practice time on Mirage

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

41% win rate across 17 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
mirage	3–13	0.00	18%	24 Jul →
inferno	11–13	-0.01	22%	23 Jul →
dust2	13–8	-0.03	34%	23 Jul →
dust2	4–13	-0.13	43%	23 Jul →
inferno	13–7	-0.02	22%	21 Jul →
cache	5–13	-0.00	45%	21 Jul →
anubis	9–13	-0.05	24%	20 Jul →
mirage	6–13	0.06	50%	19 Jul →
anubis	15–15	0.01	22%	18 Jul →
cache	13–11	0.02	24%	18 Jul →
dust2	13–11	0.02	36%	18 Jul →
cache	11–13	0.03	30%	17 Jul →
cache	13–1	0.02	45%	17 Jul →
mirage	0–2	-0.11	0%	17 Jul →
anubis	13–5	0.07	27%	17 Jul →
mirage	5–13	-0.01	39%	16 Jul →
dust2	16–12	0.08	23%	16 Jul →
cache	13–7	-0.02	27%	16 Jul →
nuke	1–8	-0.03	0%	14 Jul →
inferno	9–13	0.02	23%	14 Jul →
nuke	2–13	-0.07	25%	14 Jul →
dust2	13–6	0.04	15%	14 Jul →
inferno	13–6	0.05	21%	13 Jul →
dust2	14–16	-0.05	43%	13 Jul →
mirage	13–0	-0.00	75%	12 Jul →
ancient	13–2	0.10	42%	12 Jul →
cache	0–13	-0.03	0%	12 Jul →
nuke	0–13	-0.06	0%	12 Jul →
cache	0–13	-0.09	0%	12 Jul →
dust2	13–6	0.12	34%	12 Jul →
dust2	14–16	-0.02	31%	12 Jul →
cache	13–8	0.11	40%	12 Jul →
anubis	13–7	-0.07	25%	11 Jul →
inferno	13–5	0.02	33%	11 Jul →
nuke	13–2	-0.00	53%	11 Jul →
anubis	13–5	0.04	36%	11 Jul →
cache	13–7	-0.03	19%	10 Jul →
nuke	13–4	0.10	34%	10 Jul →
cache	8–13	-0.03	31%	9 Jul →
mirage	13–5	0.08	27%	9 Jul →
inferno	8–6	0.05	55%	8 Jul →
mirage	10–13	0.01	23%	8 Jul →
cache	12–12	0.02	30%	7 Jul →
inferno	13–7	-0.02	22%	6 Jul →
mirage	10–3	-0.09	7%	6 Jul →
dust2	11–2	-0.02	50%	5 Jul →
inferno	13–8	0.00	23%	5 Jul →
dust2	13–8	0.03	28%	5 Jul →
cache	4–13	-0.01	14%	5 Jul →
mirage	12–1	0.02	21%	4 Jul →
vertigo	13–9	0.06	24%	4 Jul →
mirage	12–12	0.14	36%	3 Jul →
cache	0–13	-0.05	0%	3 Jul →
vertigo	6–13	-0.02	31%	3 Jul →
nuke	13–10	0.03	19%	1 Jul →
mirage	13–3	-0.03	14%	1 Jul →
dust2	13–11	-0.01	27%	1 Jul →
anubis	12–12	0.04	34%	30 Jun →
train	6–0	-0.01	67%	30 Jun →
nuke	13–5	0.03	13%	30 Jun →
inferno	13–11	0.04	19%	29 Jun →
ancient	13–9	-0.03	33%	29 Jun →
vertigo	13–5	0.07	25%	29 Jun →
overpass	13–1	-0.02	6%	28 Jun →
dust2	12–12	0.06	36%	28 Jun →
cache	7–1	0.06	27%	28 Jun →
dust2	5–13	-0.03	39%	27 Jun →
cache	8–13	0.07	26%	26 Jun →
dust2	16–14	0.03	15%	26 Jun →
ancient	13–10	0.07	23%	24 Jun →
mirage	9–0	0.27	61%	24 Jun →
cache	13–5	0.06	40%	24 Jun →
dust2	7–13	-0.04	24%	23 Jun →
mirage	4–13	-0.06	35%	23 Jun →
dust2	13–7	-0.02	29%	22 Jun →
anubis	12–12	-0.02	23%	22 Jun →
mirage	13–4	-0.04	18%	21 Jun →
anubis	10–13	-0.05	16%	20 Jun →
inferno	13–5	0.07	35%	20 Jun →
train	3–13	-0.02	35%	19 Jun →
ancient	0–13	-0.06	0%	19 Jun →
ancient	10–13	0.01	37%	16 Jun →
inferno	4–13	-0.01	34%	14 Jun →
dust2	13–2	0.05	50%	12 Jun →
cache	13–10	0.02	39%	11 Jun →
mirage	0–13	-0.02	0%	11 Jun →
vertigo	13–2	0.12	23%	11 Jun →
vertigo	0–13	-0.08	23%	9 Jun →
vertigo	13–5	-0.02	15%	9 Jun →
inferno	13–10	0.03	31%	7 Jun →
dust2	13–0	0.01	50%	4 Jun →
anubis	13–5	0.09	21%	2 Jun →
anubis	13–11	0.01	22%	30 May →
anubis	2–13	-0.03	40%	30 May →
mirage	4–13	0.02	20%	24 May →
mirage	7–13	0.06	29%	18 May →
inferno	13–5	-0.01	24%	18 May →
dust2	2–13	0.02	28%	18 May →
cache	13–6	0.00	30%	18 May →
nuke	13–7	0.02	47%	18 May →