KUWNA — CS2 Stats

US76561198017956412[U:1:57690684]Steam profile ↗✓ No bans

1,102Tracked matches47%Win rate2020Tracked since

2,881Hours in CS2Hrs last 2 wks

CSDB Rating5.9 SolidHybrid Rifler

WingmanMaster Guardian Elite

Ladder ranks via Leetify

Performance scores

Aim67

Positioning52

Utility56

0–100 skill scores via Leetify.

Recent form

STEADY53–41–6Last 10053%Win rateLWWLWWWLLL

Last 10 vs previous 10: +40pp win rate · +0.00 avg rating

Player DNA

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

Aim6.7

Aggression5.8

Utility5.6

Positioning5.2

Opening Duels2.1

Clutch0.0

Excellent counter-strafingStrong CT-side openerEffective flashes

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 89% playstyle similarity

Most alike: opening-fight frequency, 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

Strengths

Flashes. 0.80 enemies blinded per flash — utility that consistently lands.

Areas to improve

T-side openings. Opening success drops from 50% on CT to 27% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 648ms 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

Aim6.7

Positioning5.2

Utility5.6

Mechanics8.8

Opening Duels2.5

Win Impact3.9

Composite 5.9/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.03

first ⅓ avg 0.01 → last ⅓ avg -0.02

Reaction time650ms+46ms

first ⅓ avg 604ms → last ⅓ avg 650ms

Headshot accuracy22.5%−0.5%

first ⅓ avg 23.0% → last ⅓ avg 22.5%

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

0.15Best rating — ancient 13–1

13–1Biggest win — dust2

7Longest win streak

11–7In matches decided by ≤2 rounds

14Overtime games

Map breakdown

ancientBest map · 67% over 12trainWeakest map · 14% over 7

Map	Grade	Played	Record	Win rate	Avg rating
dust2	S	29	19–10	66%	-0.00
mirage	B	23	12–11	52%	-0.01
inferno	B	22	10–12	45%	-0.02
ancient	S	12	8–4	67%	0.01
train	D	7	1–6	14%	0.02
overpass	—	2	0–2	0%	-0.01
nuke	—	2	2–0	100%	-0.02
cache	—	1	0–1	0%	-0.02
edin	—	1	0–1	0%	-0.02
office	—	1	1–0	100%	0.07

Across the last 100 tracked matches.

Lifetime stats

89,578Lifetime kills

1.25K/D · Top 25% of tracked players

5,282Matches

56.9%Match win rate · Top 5% of tracked players

54.1%Headshot % · Top 25% of tracked players

18.9%Shot accuracy · Top 10% of tracked players

12,253MVPs

1,838Hours (in match)

2,707Bombs planted

818Bombs defused

Most-used weapons

AK-4734,146

M4A4 / M4A1-S13,806

P2000 / USP-S5,951

AWP4,317

Desert Eagle4,068

Glock-183,692

MP92,791

AUG2,764

P901,780

Galil AR1,684

Lifetime map wins

8,537inferno

4,371dust2

1,884vertigo

728nuke

722train

442office

353cbble

214aztec

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

Faceit stats

Combat

370Matches

52%Win rate

1.12Avg K/D

94.5ADR

49%Headshot %

Clutches & streaks

0%1v1 clutch win

0%1v2 clutch win

7Longest win streak

Recent Faceit resultsLLLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	28	57%	0.92	16.6
Ancient	12	25%	0.86	13.8
Inferno	12	42%	0.97	16.5
Anubis	8	62%	1.12	19.4
Overpass	7	57%	1.49	20.4
Vertigo	4	50%	0.88	11.8
Nuke	1	0%	0.71	10.0
Cache	1	0%	0.71	12.0

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.

21.5%Headshot accuracy

30.3%Accuracy (enemy spotted)

30.9%Spray accuracy

89.8%Counter-strafing

9.2°Preaim

648msReaction time

27.2%T opening success

49.8%CT opening success

0.80Enemies flashed / flash

7.2%Flash assists

9.20HE damage / grenade

12.15Flashes / 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 27.2218% — below the 40% mark we flag

Spend your practice time on Train

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

14% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
cache	10–13	-0.02	21%	22 Aug →
dust2	16–14	-0.01	24%	6 Jun →
mirage	16–14	0.02	25%	6 Jun →
overpass	7–13	-0.06	22%	6 Jun →
ancient	13–8	-0.07	4%	6 Jun →
inferno	13–8	-0.06	13%	6 Jun →
dust2	13–5	0.03	20%	6 Jun →
inferno	10–13	-0.02	15%	6 Jun →
mirage	8–13	-0.06	23%	18 Apr →
dust2	3–13	-0.03	24%	18 Apr →
inferno	16–14	0.04	29%	18 Apr →
dust2	7–13	-0.04	11%	20 Dec →
dust2	10–13	-0.05	22%	20 Dec →
inferno	10–13	-0.07	6%	20 Dec →
overpass	9–13	0.05	19%	20 Dec →
mirage	10–13	-0.03	14%	20 Dec →
dust2	6–13	-0.09	34%	20 Dec →
inferno	0–13	-0.08	22%	20 Dec →
dust2	10–13	-0.04	28%	14 Dec →
ancient	10–13	0.01	37%	8 Jul →
dust2	6–13	-0.09	21%	8 Jul →
mirage	13–11	0.01	18%	7 Jun →
inferno	13–5	0.01	19%	6 Jun →
nuke	13–8	-0.03	22%	6 Jun →
dust2	13–9	0.01	26%	6 Jun →
ancient	13–7	-0.03	28%	6 Jun →
mirage	13–8	0.03	23%	31 May →
inferno	13–4	-0.01	18%	31 May →
inferno	11–13	-0.02	26%	31 May →
mirage	13–4	0.02	30%	31 May →
inferno	9–13	-0.06	25%	31 May →
dust2	6–13	-0.04	38%	31 May →
mirage	13–8	0.04	36%	31 May →
dust2	13–6	-0.01	40%	30 May →
dust2	13–1	-0.01	14%	30 May →
inferno	10–13	-0.03	26%	30 May →
mirage	13–11	-0.04	18%	30 May →
train	10–13	0.06	18%	21 May →
train	2–13	0.14	25%	21 May →
train	2–13	-0.01	24%	21 May →
dust2	10–13	-0.03	21%	18 May →
inferno	8–13	-0.02	33%	18 May →
dust2	13–6	0.00	22%	18 May →
mirage	13–16	-0.01	13%	17 May →
mirage	14–16	-0.01	15%	17 May →
mirage	16–13	0.00	27%	17 May →
inferno	13–8	0.00	31%	17 May →
dust2	13–8	0.01	23%	17 May →
ancient	11–13	-0.04	18%	17 May →
mirage	14–16	0.05	22%	26 Apr →
ancient	16–13	-0.05	13%	26 Apr →
mirage	9–13	-0.03	11%	16 Mar →
inferno	12–12	-0.03	18%	16 Mar →
inferno	13–11	0.08	24%	15 Mar →
train	13–6	0.12	28%	15 Mar →
mirage	13–3	0.04	16%	15 Mar →
dust2	15–15	-0.04	40%	15 Mar →
mirage	13–5	0.06	28%	15 Mar →
dust2	13–9	0.01	24%	15 Mar →
ancient	9–13	0.01	20%	15 Mar →
dust2	13–2	0.04	29%	8 Feb →
dust2	13–11	-0.04	15%	8 Feb →
inferno	10–13	-0.04	23%	8 Feb →
mirage	7–13	0.00	29%	4 Feb →
dust2	13–8	-0.03	21%	2 Feb →
inferno	8–13	-0.02	24%	2 Feb →
inferno	7–13	-0.09	17%	1 Feb →
train	14–16	-0.08	24%	1 Feb →
mirage	14–16	-0.01	16%	1 Feb →
inferno	16–14	-0.01	19%	1 Feb →
ancient	5–13	-0.01	11%	29 Jan →
dust2	13–8	0.01	13%	29 Jan →
inferno	13–4	-0.01	14%	29 Jan →
inferno	12–12	0.04	31%	18 Jan →
mirage	13–8	0.02	29%	18 Jan →
ancient	13–8	0.03	26%	18 Jan →
dust2	12–12	0.06	22%	18 Jan →
dust2	13–2	0.05	24%	18 Jan →
ancient	13–8	0.03	23%	11 Jan →
dust2	13–4	0.03	21%	11 Jan →
train	12–12	-0.03	20%	11 Jan →
edin	5–13	-0.02	22%	11 Jan →
mirage	10–13	-0.08	31%	11 Jan →
inferno	16–14	-0.07	20%	11 Jan →
mirage	13–6	-0.07	29%	11 Jan →
mirage	14–16	-0.07	33%	11 Jan →
ancient	13–11	0.07	24%	5 Jan →
dust2	13–5	0.04	30%	5 Jan →
mirage	12–12	-0.01	21%	5 Jan →
dust2	13–10	-0.01	39%	5 Jan →
office	13–6	0.07	18%	5 Jan →
nuke	13–10	-0.01	19%	5 Jan →
inferno	13–4	0.04	24%	5 Jan →
mirage	13–11	0.01	16%	5 Jan →
ancient	13–8	-0.01	17%	5 Jan →
train	3–13	-0.04	27%	4 Jan →
dust2	13–8	0.13	37%	4 Jan →
dust2	13–7	-0.02	21%	14 Dec →
dust2	13–7	0.04	10%	14 Dec →
ancient	13–1	0.15	32%	14 Dec →