nakii — CS2 Stats

76561198276112974[U:1:315847246]Steam profile ↗✓ No bans

509Tracked matches53%Win rate2022Tracked since

CSDB Rating4.8 DevelopingHybrid Rifler

FaceitLevel 5 · 1,101 ELOTop 67.6% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim69

Positioning42

Utility35

0–100 skill scores via Leetify.

Recent form

STEADY53–47Last 10053%Win rateWWLLLWLLWW

Last 10 vs previous 10: +0pp win rate · -0.02 avg rating

Player DNA

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

Aim6.9

Aggression5.6

Utility3.5

Positioning4.2

Opening Duels1.6

Clutch4.0

Strong CT-side opener

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 82% playstyle similarity

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

Where you differ: lower aim profile; lower utility contribution.

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

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

T-side openings. Opening success drops from 46% on CT to 27% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim6.9

Positioning4.2

Utility3.5

Mechanics7.0

Opening Duels2.0

Win Impact6.1

Composite 4.8/10 (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 rating0.01−0.01

first ⅓ avg 0.03 → last ⅓ avg 0.01

Reaction time588ms+0ms

first ⅓ avg 587ms → last ⅓ avg 588ms

Headshot accuracy26.7%+3.0%

first ⅓ avg 23.7% → 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 — nuke 13–5

13–1Biggest win — inferno

7Longest win streak

W2Current streak

4–9In matches decided by ≤2 rounds

7Overtime games

Map breakdown

infernoBest map · 61% over 28dust2Weakest map · 44% over 18

Map	Grade	Played	Record	Win rate	Avg rating
inferno	A	28	17–11	61%	0.02
mirage	B	25	12–13	48%	0.02
dust2	C	18	8–10	44%	0.02
nuke	B	13	7–6	54%	0.04
ancient	A	9	5–4	56%	0.01
overpass	—	3	2–1	67%	0.01
train	—	2	1–1	50%	0.08
anubis	—	2	1–1	50%	-0.04

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (44% over 18). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

299Matches

47%Win rate

1.11Avg K/D

84.7ADR

51%Headshot %

Clutches & streaks

40%1v1 clutch win

23%1v2 clutch win

9Longest win streak

Recent Faceit resultsLLWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	105	50%	1.22	17.0
Dust2	75	49%	1.08	17.4
Inferno	51	49%	1.13	16.6
Nuke	26	31%	1.01	17.2
Overpass	12	33%	0.95	16.3
Ancient	9	56%	1.21	17.6
Anubis	1	100%	1.40	21.0

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.

26.5%Headshot accuracy

28.7%Accuracy (enemy spotted)

26.2%Spray accuracy

81.4%Counter-strafing

8.3°Preaim

592msReaction time

27.3%T opening success

45.8%CT opening success

0.61Enemies flashed / flash

5.2%Flash assists

9.83HE damage / grenade

8.45Flashes / 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 27.3383% — below the 40% mark we flag

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.

44% win rate across 18 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
mirage	13–7	-0.00	15%	9 Aug →
inferno	13–5	-0.01	25%	31 Dec →
mirage	3–13	-0.08	29%	30 Dec →
mirage	11–13	-0.04	12%	30 Dec →
dust2	6–13	-0.07	28%	29 Dec →
inferno	13–10	0.01	20%	29 Dec →
dust2	10–13	-0.02	29%	28 Dec →
dust2	16–19	-0.02	29%	24 Dec →
mirage	13–7	0.06	33%	22 Dec →
inferno	13–9	0.03	38%	20 Dec →
nuke	13–6	0.02	31%	16 Dec →
ancient	2–10	-0.07	33%	16 Dec →
mirage	11–13	0.06	34%	11 Aug →
inferno	13–4	-0.02	18%	11 Aug →
overpass	13–7	-0.02	31%	11 Aug →
mirage	7–13	-0.03	30%	11 Aug →
mirage	9–13	0.02	18%	10 Aug →
inferno	11–13	0.01	33%	7 Aug →
nuke	13–5	0.01	23%	5 Aug →
overpass	13–5	0.07	30%	5 Aug →
mirage	13–7	0.05	24%	5 Aug →
inferno	7–13	-0.01	32%	5 Aug →
nuke	13–5	0.24	21%	4 Aug →
dust2	12–16	-0.07	24%	3 Aug →
dust2	4–13	-0.04	15%	3 Aug →
dust2	13–10	0.04	21%	3 Aug →
inferno	7–13	-0.04	22%	30 Jul →
inferno	13–7	0.05	32%	29 Jul →
mirage	13–8	0.13	34%	29 Jul →
inferno	13–5	-0.04	29%	28 Jul →
dust2	13–8	0.13	29%	27 Jul →
mirage	13–6	0.07	29%	26 Jul →
inferno	13–6	0.06	28%	24 Jul →
inferno	13–10	0.14	20%	23 Jul →
mirage	13–16	0.04	28%	21 Jul →
inferno	5–13	-0.08	9%	18 Jul →
overpass	10–13	-0.01	31%	18 Jul →
inferno	8–13	-0.05	16%	15 Jul →
dust2	13–9	0.01	25%	14 Jul →
inferno	5–13	-0.01	39%	14 Jul →
mirage	13–10	0.11	30%	14 Jul →
inferno	13–5	0.00	20%	14 Jul →
inferno	16–12	0.02	37%	14 Jul →
train	0–3	0.09	100%	14 Jul →
inferno	2–13	0.01	22%	14 Jul →
nuke	6–13	0.01	15%	12 Jul →
inferno	13–11	0.10	23%	11 Jul →
dust2	9–13	0.03	16%	11 Jul →
nuke	3–13	-0.06	42%	11 Jul →
dust2	13–5	0.08	30%	11 Jul →
mirage	8–13	-0.06	6%	11 Jul →
dust2	13–7	-0.01	30%	10 Jul →
dust2	6–13	-0.03	10%	9 Jul →
nuke	13–8	0.05	23%	9 Jul →
inferno	10–13	-0.04	28%	8 Jul →
nuke	13–3	0.01	29%	8 Jul →
dust2	13–11	0.10	26%	7 Jul →
mirage	13–10	-0.01	17%	5 Jul →
dust2	13–2	0.16	30%	3 Jul →
mirage	6–13	-0.01	34%	1 Jul →
ancient	5–13	0.06	34%	30 Jun →
mirage	13–8	0.06	23%	30 Jun →
train	13–8	0.07	18%	30 Jun →
mirage	6–13	-0.01	27%	30 Jun →
anubis	13–9	-0.02	21%	29 Jun →
ancient	13–9	0.00	19%	29 Jun →
inferno	13–6	0.02	24%	28 Jun →
ancient	9–13	-0.02	21%	28 Jun →
dust2	13–8	0.00	30%	28 Jun →
mirage	13–5	0.08	17%	28 Jun →
nuke	11–13	-0.02	25%	27 Jun →
mirage	9–13	0.04	27%	27 Jun →
inferno	5–13	-0.10	22%	27 Jun →
inferno	13–8	0.11	21%	25 Jun →
inferno	13–5	0.12	14%	24 Jun →
mirage	14–16	0.06	22%	24 Jun →
ancient	13–6	0.00	17%	24 Jun →
nuke	13–8	0.01	10%	24 Jun →
inferno	11–13	0.03	20%	23 Jun →
nuke	9–13	0.06	15%	23 Jun →
dust2	11–13	0.04	29%	23 Jun →
anubis	4–13	-0.05	29%	22 Jun →
ancient	13–9	0.09	16%	22 Jun →
mirage	16–14	0.01	32%	22 Jun →
ancient	13–10	-0.09	18%	21 Jun →
inferno	13–1	0.10	43%	21 Jun →
nuke	13–3	0.12	37%	21 Jun →
dust2	6–13	-0.04	18%	17 Jun →
nuke	9–13	0.01	14%	15 Jun →
inferno	13–11	0.06	25%	15 Jun →
ancient	13–10	0.11	23%	14 Jun →
dust2	14–16	0.02	16%	14 Jun →
mirage	11–13	0.04	21%	10 Jun →
mirage	13–2	0.02	17%	10 Jun →
mirage	10–13	-0.05	17%	10 Jun →
inferno	13–10	0.06	42%	9 Jun →
nuke	8–13	0.01	17%	9 Jun →
ancient	7–13	0.00	35%	7 Jun →
inferno	5–13	-0.00	50%	6 Jun →
mirage	13–4	0.02	21%	6 Jun →