NaZtY — CS2 Stats

76561199078191603[U:1:1117925875]Steam profile ↗✓ No bans

1,878Tracked matches57%Win rate2020Tracked since

CSDB Rating4.2 Developing

FaceitLevel 6 · 1,397 ELOTop 54.0% of ranked FACEIT players

WingmanGold Nova Master

Ladder ranks via Leetify

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Performance scores

Aim48

Positioning43

Utility60

0–100 skill scores via Leetify.

Recent form

HOT52–48Last 10052%Win rateWLWLWWWLWW

Last 10 vs previous 10: +30pp win rate · -0.01 avg rating

Player DNA

Aim4.8

Aggression5.4

Utility6.0

Positioning4.3

Opening Duels1.8

Clutch2.8

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 84% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: lower positioning profile; 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 52% on CT to 22% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 570ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 64% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim4.8

Positioning4.3

Utility6.0

Mechanics3.0

Opening Duels2.7

Win Impact7.2

Composite 4.2/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.00−0.01

first ⅓ avg 0.00 → last ⅓ avg -0.00

Reaction time578ms−15ms

first ⅓ avg 593ms → last ⅓ avg 578ms

Headshot accuracy15.8%+0.4%

first ⅓ avg 15.4% → last ⅓ avg 15.8%

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

0.10Best rating — overpass 13–3

13–2Biggest win — train

6Longest win streak

15–14In matches decided by ≤2 rounds

13Overtime games

Map breakdown

overpassBest map · 77% over 13dust2Weakest map · 29% over 7

Map	Grade	Played	Record	Win rate	Avg rating
nuke	S	27	18–9	67%	-0.01
inferno	C	26	10–16	38%	-0.00
overpass	S	13	10–3	77%	0.02
ancient	D	10	3–7	30%	0.01
train	C	10	4–6	40%	-0.00
dust2	D	7	2–5	29%	-0.01
anubis	—	4	3–1	75%	-0.00
vertigo	—	2	1–1	50%	0.00
cache	—	1	1–0	100%	-0.06

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,227Matches

50%Win rate

0.91Avg K/D

71.4ADR

35%Headshot %

Clutches & streaks

34%1v1 clutch win

19%1v2 clutch win

11Longest win streak

Recent Faceit resultsLLWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Nuke	152	60%	1.03	14.2
Inferno	127	47%	0.94	14.4
Ancient	95	44%	0.89	14.0
Overpass	62	63%	1.02	14.7
Dust2	44	32%	0.77	11.9
Train	40	42%	0.91	12.8
Vertigo	31	45%	0.79	11.8
Anubis	17	47%	0.82	13.2

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.

16.1%Headshot accuracy

35.9%Accuracy (enemy spotted)

37.6%Spray accuracy

63.6%Counter-strafing

13.0°Preaim

570msReaction time

22.4%T opening success

51.6%CT opening success

0.52Enemies flashed / flash

5.1%Flash assists

9.98HE damage / grenade

10.58Flashes / 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
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 13.0325° — above the 12° mark we flag
Aim Training →

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.

29% win rate across 7 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
vertigo	13–3	0.03	5%	26 Aug →
inferno	11–13	-0.04	10%	22 Aug →
nuke	9–7	0.05	16%	11 May →
vertigo	10–13	-0.02	24%	6 May →
cache	13–11	-0.06	28%	5 May →
nuke	13–5	-0.00	13%	3 May →
ancient	13–5	0.04	16%	3 May →
nuke	8–13	-0.08	30%	14 Mar →
nuke	13–10	0.01	18%	21 Jan →
nuke	13–6	-0.03	17%	21 Jan →
inferno	25–22	-0.01	17%	20 Jan →
overpass	10–13	-0.03	13%	20 Jan →
dust2	10–13	0.00	31%	19 Jan →
ancient	9–13	0.05	13%	18 Jan →
inferno	5–13	-0.07	18%	18 Jan →
overpass	13–7	0.04	9%	17 Jan →
anubis	13–9	0.05	6%	17 Jan →
inferno	13–11	0.00	11%	17 Jan →
nuke	18–22	-0.02	10%	17 Jan →
ancient	7–13	-0.03	11%	17 Jan →
nuke	13–10	0.04	17%	17 Jan →
inferno	13–7	0.02	27%	17 Jan →
inferno	9–13	-0.03	13%	17 Jan →
anubis	5–13	-0.02	15%	16 Jan →
ancient	9–13	0.04	24%	16 Jan →
nuke	13–7	-0.03	14%	15 Jan →
nuke	13–5	0.00	11%	15 Jan →
anubis	13–10	-0.02	5%	15 Jan →
train	13–2	0.03	22%	15 Jan →
dust2	13–6	0.01	12%	15 Jan →
nuke	6–13	-0.03	28%	14 Jan →
inferno	13–4	0.05	6%	13 Jan →
dust2	6–13	-0.03	14%	13 Jan →
train	13–6	0.01	9%	13 Jan →
anubis	22–20	-0.03	15%	13 Jan →
train	13–7	-0.03	24%	12 Jan →
inferno	11–13	-0.00	16%	12 Jan →
overpass	6–13	-0.03	8%	12 Jan →
inferno	11–13	-0.00	9%	11 Jan →
inferno	13–7	0.03	20%	11 Jan →
inferno	8–13	-0.07	10%	11 Jan →
nuke	8–13	-0.01	14%	11 Jan →
nuke	13–6	0.04	11%	11 Jan →
inferno	20–22	0.03	16%	10 Jan →
train	6–13	-0.03	16%	10 Jan →
nuke	13–2	0.05	7%	10 Jan →
ancient	13–11	0.01	13%	10 Jan →
dust2	11–13	-0.06	19%	10 Jan →
nuke	6–13	-0.09	7%	10 Jan →
inferno	10–13	-0.01	29%	10 Jan →
overpass	13–10	0.05	5%	10 Jan →
train	13–8	-0.04	27%	10 Jan →
nuke	6–13	-0.10	13%	9 Jan →
nuke	13–7	0.01	6%	9 Jan →
nuke	13–11	0.03	18%	8 Jan →
overpass	13–8	-0.04	9%	8 Jan →
inferno	10–13	0.02	19%	8 Jan →
overpass	13–11	0.05	12%	8 Jan →
inferno	13–7	0.04	11%	7 Jan →
train	17–19	-0.02	14%	7 Jan →
nuke	13–10	0.01	11%	7 Jan →
nuke	13–11	0.00	10%	7 Jan →
overpass	13–11	0.03	11%	7 Jan →
inferno	9–13	-0.01	15%	7 Jan →
train	14–16	0.00	7%	6 Jan →
dust2	11–13	0.02	17%	6 Jan →
ancient	1–13	-0.01	13%	6 Jan →
nuke	11–13	0.00	10%	6 Jan →
overpass	13–10	-0.05	11%	5 Jan →
inferno	11–13	-0.01	21%	5 Jan →
ancient	4–13	-0.03	17%	5 Jan →
inferno	8–13	0.05	16%	5 Jan →
nuke	14–16	-0.05	8%	5 Jan →
inferno	13–8	0.00	14%	4 Jan →
overpass	13–9	0.01	9%	4 Jan →
dust2	13–9	0.03	18%	4 Jan →
inferno	13–5	0.03	16%	4 Jan →
nuke	16–14	-0.02	8%	4 Jan →
overpass	13–9	0.07	15%	4 Jan →
overpass	11–13	0.04	18%	4 Jan →
ancient	11–13	-0.02	14%	4 Jan →
train	12–16	-0.03	16%	3 Jan →
overpass	13–3	0.10	20%	3 Jan →
inferno	14–16	-0.03	24%	3 Jan →
nuke	15–19	-0.06	19%	3 Jan →
inferno	13–11	0.03	17%	3 Jan →
nuke	13–8	0.00	14%	3 Jan →
nuke	13–11	0.03	6%	3 Jan →
nuke	13–11	-0.06	11%	3 Jan →
inferno	7–13	-0.05	16%	3 Jan →
nuke	13–7	0.03	24%	3 Jan →
ancient	8–13	0.06	11%	3 Jan →
inferno	16–13	0.01	16%	3 Jan →
dust2	3–13	-0.07	28%	2 Jan →
train	9–13	-0.01	31%	2 Jan →
overpass	16–14	0.01	13%	2 Jan →
inferno	8–13	0.00	5%	2 Dec →
ancient	13–11	0.00	5%	2 Dec →
train	8–13	0.06	17%	2 Dec →
inferno	7–13	0.02	18%	2 Dec →