nightmareK-- — CS2 Stats

76561198169738329[U:1:209472601]

1,424Tracked matches69%Win rate2020Tracked since

CSDB Rating6.7 SolidHybrid Rifler

FaceitLevel 10 · 2,557 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim74

Positioning53

Utility75

0–100 skill scores via Leetify.

Recent form

STEADY52–47–1Last 10052%Win rateWLWWLLWWWW

Last 10 vs previous 10: -20pp win rate · -0.00 avg rating

Player DNA

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

Aim7.4

Aggression5.6

Utility7.5

Positioning5.3

Opening Duels2.1

Clutch3.4

Strong CT-side openerEffective flashesHigh utility contribution

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 Twistzz 93% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower aim 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

Areas to improve

T-side openings. Opening success drops from 49% on CT to 27% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 598ms 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

Aim7.4

Positioning5.3

Utility7.5

Mechanics6.4

Opening Duels2.4

Win Impact10.0

Composite 6.7/10 (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 rating0.02+0.02

first ⅓ avg -0.00 → last ⅓ avg 0.02

Reaction time607ms+23ms

first ⅓ avg 584ms → last ⅓ avg 607ms

Headshot accuracy24.0%+3.2%

first ⅓ avg 20.8% → last ⅓ avg 24.0%

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

0.11Best rating — dust2 13–6

13–2Biggest win — dust2

8Longest win streak

10–5In matches decided by ≤2 rounds

11Overtime games

Map breakdown

mirageBest map · 70% over 10anubisWeakest map · 42% over 12

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	35	18–17	51%	0.01
dust2	A	34	20–14	59%	0.02
anubis	C	12	5–7	42%	0.02
mirage	S	10	7–3	70%	-0.00
nuke	—	3	1–2	33%	-0.01
ancient	—	2	0–2	0%	-0.01
train	—	2	1–1	50%	-0.02
cache	—	1	0–1	0%	0.03
overpass	—	1	0–1	0%	-0.07

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (42% over 12). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

5,212Matches

54%Win rate

1.14Avg K/D

75.2ADR

52%Headshot %

Clutches & streaks

37%1v1 clutch win

20%1v2 clutch win

12Longest win streak

Recent Faceit resultsLLWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	409	56%	1.16	15.5
Inferno	336	54%	1.10	15.6
Mirage	236	52%	1.09	15.3
Anubis	232	50%	1.09	16.3
Nuke	98	48%	1.05	16.5
Ancient	83	51%	1.12	16.6
Overpass	44	36%	1.04	15.6
Train	18	50%	0.93	15.1

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.

23.7%Headshot accuracy

32.7%Accuracy (enemy spotted)

37.7%Spray accuracy

78.6%Counter-strafing

9.3°Preaim

598msReaction time

27.3%T opening success

49.3%CT opening success

0.72Enemies flashed / flash

18.4%Flash assists

10.14HE damage / grenade

12.55Flashes / 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 27.3225% — below the 40% mark we flag

Spend your practice time on Anubis

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

42% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	13–7	0.06	32%	23 May →
cache	4–13	0.03	30%	6 May →
mirage	13–10	0.00	21%	23 Apr →
mirage	13–7	0.06	22%	23 Apr →
anubis	6–13	-0.01	18%	1 Apr →
dust2	10–13	-0.01	22%	1 Apr →
anubis	13–8	0.09	14%	1 Apr →
dust2	13–6	0.06	22%	31 Mar →
dust2	13–10	0.04	15%	31 Mar →
inferno	13–11	-0.04	18%	31 Mar →
mirage	13–10	0.01	29%	31 Mar →
dust2	13–4	-0.04	13%	31 Mar →
dust2	13–11	0.00	21%	31 Mar →
mirage	9–13	0.02	25%	31 Mar →
dust2	13–9	0.04	30%	30 Mar →
dust2	13–7	-0.02	31%	30 Mar →
dust2	13–9	0.08	21%	30 Mar →
dust2	13–6	0.11	38%	30 Mar →
dust2	13–6	0.07	19%	30 Mar →
dust2	13–2	0.04	19%	30 Mar →
dust2	13–2	0.00	20%	30 Mar →
inferno	13–11	0.05	22%	29 Mar →
dust2	12–12	0.07	23%	29 Mar →
dust2	10–13	0.02	27%	29 Mar →
dust2	6–13	-0.04	47%	28 Mar →
inferno	13–5	0.08	17%	27 Mar →
anubis	7–13	-0.03	18%	27 Mar →
dust2	9–13	-0.03	29%	26 Mar →
dust2	13–4	-0.00	25%	26 Mar →
inferno	3–13	0.04	26%	24 Mar →
anubis	13–16	-0.01	34%	21 Mar →
mirage	13–6	-0.02	24%	17 Mar →
anubis	8–13	-0.00	20%	16 Mar →
ancient	3–13	-0.03	35%	16 Mar →
dust2	4–13	-0.02	13%	15 Mar →
mirage	13–8	-0.01	13%	15 Mar →
inferno	9–13	-0.01	22%	15 Mar →
inferno	7–13	0.02	36%	14 Mar →
inferno	13–6	0.06	46%	14 Mar →
inferno	8–13	0.07	18%	13 Mar →
inferno	13–2	0.07	27%	11 Mar →
anubis	15–19	0.04	17%	11 Mar →
inferno	13–9	-0.01	17%	10 Mar →
dust2	7–13	-0.00	23%	10 Mar →
inferno	16–14	-0.04	21%	10 Mar →
dust2	13–16	0.01	18%	4 Mar →
dust2	13–2	0.07	20%	3 Mar →
inferno	13–4	0.08	22%	28 Feb →
inferno	13–9	0.00	23%	21 Feb →
inferno	9–13	-0.03	26%	19 Feb →
mirage	5–13	-0.03	27%	17 Feb →
inferno	13–9	0.03	20%	14 Feb →
inferno	13–9	0.03	20%	6 Feb →
dust2	11–13	0.02	12%	2 Feb →
anubis	19–17	0.05	19%	30 Jan →
inferno	13–10	0.09	17%	30 Jan →
mirage	8–13	-0.04	15%	23 Jan →
anubis	13–5	0.08	22%	23 Jan →
dust2	16–13	0.00	19%	19 Jan →
nuke	10–13	-0.05	16%	18 Jan →
anubis	8–13	-0.02	21%	15 Jan →
inferno	10–13	-0.02	21%	26 Dec →
inferno	8–13	0.00	12%	19 Dec →
nuke	13–7	-0.01	21%	17 Dec →
dust2	9–13	-0.02	15%	16 Dec →
inferno	11–13	0.09	30%	9 Dec →
inferno	9–13	-0.06	29%	7 Dec →
dust2	10–13	-0.02	32%	3 Dec →
dust2	13–6	0.00	21%	25 Nov →
dust2	9–13	-0.03	14%	22 Nov →
dust2	13–10	0.03	20%	21 Nov →
inferno	10–13	0.01	24%	18 Nov →
dust2	16–12	0.01	29%	8 Nov →
inferno	4–13	-0.06	9%	7 Nov →
inferno	13–2	0.04	31%	1 Nov →
mirage	16–12	-0.02	25%	25 Oct →
mirage	13–6	-0.01	13%	18 Oct →
ancient	5–13	0.00	28%	17 Oct →
dust2	9–13	0.04	22%	16 Aug →
dust2	16–14	-0.01	24%	12 Aug →
inferno	13–10	0.07	13%	7 Aug →
inferno	11–13	0.03	24%	4 Aug →
overpass	5–13	-0.07	9%	25 Jul →
inferno	15–19	-0.02	17%	22 Jul →
inferno	13–7	0.01	15%	13 Jul →
inferno	13–11	-0.01	11%	12 Jul →
dust2	10–13	0.00	30%	8 Jul →
dust2	13–10	0.04	21%	5 Jul →
nuke	11–13	0.03	22%	3 Jul →
inferno	8–13	-0.07	16%	2 Jul →
anubis	13–9	0.00	30%	27 Jun →
inferno	9–13	0.00	29%	26 Jun →
anubis	17–19	-0.01	15%	26 Jun →
train	3–13	-0.05	30%	24 Jun →
train	13–11	0.00	11%	21 Jun →
inferno	13–11	0.01	20%	19 Jun →
anubis	13–11	0.02	17%	17 Jun →
inferno	13–3	0.00	23%	15 Jun →
inferno	5–13	-0.03	17%	21 May →
inferno	7–13	0.03	24%	12 May →