[KRG] GangBツツ — CS2 Stats

DK76561199189509241[U:1:1229243513]Steam profile ↗

239Tracked matches41%Win rate2023Tracked since

853Hours in CS3Hrs last 2 wks

CSDB Rating4.8 DevelopingHybrid Rifler

Premier CS Rating14,643Blue band · top ~30.3% of ranked players (population est.)

CSDB Leaderboard#17815 of 27735 tracked

WingmanGold Nova Master

Ladder ranks via Leetify

How this compares with the same rank

Median values for Blue band among CSDB-tracked players (n=1,240), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

Metric	This player	Blue band median	Purple band median	vs Purple band
Headshot rate	43.6%	41.7%	44.1%	meets
Shot accuracy	11.6%	8.8%	11.4%	meets
Kill/death ratio	1.43	0.97	1.03	above
Match win rate	45.6%	43.8%	45.2%	meets

Across every metric we can compare, this profile already matches the typical Purple band player. Rank still comes from winning matches — this is a performance comparison, not a prediction.

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Performance scores

Aim72

Positioning51

Utility44

0–100 skill scores via Leetify.

Recent form

COLD42–50–8Last 10042%Win rateWLTLLLTLLW

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

Player DNA

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

Aim7.2

Aggression4.8

Utility4.4

Positioning5.1

Opening Duels0.8

Clutch0.0

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 88% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

Where you differ: lower utility contribution; 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 41% on CT to 25% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 672ms 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

Aim7.2

Positioning5.1

Utility4.4

Mechanics5.8

Opening Duels1.4

Win Impact1.9

Composite 4.8/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.00−0.05

first ⅓ avg 0.05 → last ⅓ avg 0.00

Reaction time669ms−57ms

first ⅓ avg 726ms → last ⅓ avg 669ms

Headshot accuracy14.5%−6.8%

first ⅓ avg 21.3% → last ⅓ avg 14.5%

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

0.34Best rating — inferno 9–2

13–2Biggest win — ancient

7Longest win streak

2–6In matches decided by ≤2 rounds

5Overtime games

Map breakdown

ancientBest map · 67% over 9nukeWeakest map · 25% over 8

Map	Grade	Played	Record	Win rate	Avg rating
cache	C	21	9–12	43%	0.04
mirage	C	18	8–10	44%	-0.00
inferno	C	17	6–11	35%	0.02
anubis	D	10	3–7	30%	0.02
ancient	S	9	6–3	67%	0.01
nuke	D	8	2–6	25%	0.02
train	S	6	4–2	67%	0.04
dust2	A	5	3–2	60%	0.01
vertigo	—	3	0–3	0%	0.03
office	—	3	1–2	33%	0.03

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (25% over 8). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

24,890Lifetime kills

1.43K/D · Top 5% of Blue band

1,276Matches

45.6%Match win rate · Top 50% of Blue band

43.6%Headshot % · Top 50% of Blue band

11.6%Shot accuracy · Top 50% of Blue band

4,897MVPs

322Hours (in match)

1,095Bombs planted

517Bombs defused

Most-used weapons

AK-475,988

M4A4 / M4A1-S4,459

AWP2,669

P2000 / USP-S2,204

Desert Eagle1,627

Glock-181,387

Galil AR901

MP9676

MP7609

FAMAS514

Lifetime map wins

2,298inferno

1,841nuke

709dust2

500office

452vertigo

439train

116lake

60cbble

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

Faceit stats

Combat

2Matches

50%Win rate

0.86Avg K/D

62.2ADR

45%Headshot %

Clutches & streaks

20%1v1 clutch win

25%1v2 clutch win

1Longest win streak

Recent Faceit resultsLLLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Nuke	1	100%	1.00	20.0
Overpass	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.

14.6%Headshot accuracy

41.2%Accuracy (enemy spotted)

41.6%Spray accuracy

76.3%Counter-strafing

8.6°Preaim

672msReaction time

25.0%T opening success

41.3%CT opening success

0.54Enemies flashed / flash

3.9%Flash assists

7.54HE damage / grenade

5.23Flashes / 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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 14.6307% — below the 15% mark we flag
Aim Training →
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 25.0282% — below the 40% mark we flag

Spend your practice time on Nuke

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

25% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
mirage	13–8	0.02	13%	28 Aug →
nuke	8–13	-0.00	8%	22 Aug →
mirage	12–12	-0.01	14%	8 Aug →
ancient	4–13	-0.06	27%	8 Aug →
vertigo	8–13	0.08	10%	31 Jul →
vertigo	1–13	-0.04	13%	31 Jul →
vertigo	12–12	0.05	14%	31 Jul →
inferno	7–13	0.01	29%	28 Jul →
mirage	2–13	-0.02	7%	28 Jul →
nuke	13–6	0.01	5%	28 Jul →
anubis	3–13	-0.06	9%	27 Jul →
inferno	10–13	0.05	13%	27 Jul →
anubis	13–5	0.04	13%	26 Jul →
ancient	13–2	0.03	19%	26 Jul →
nuke	15–15	0.01	9%	25 Jul →
dust2	10–13	-0.07	11%	25 Jul →
mirage	3–13	-0.03	14%	25 Jul →
cache	13–4	-0.05	10%	25 Jul →
ancient	8–13	0.05	23%	24 Jul →
inferno	6–13	-0.04	22%	24 Jul →
inferno	13–11	-0.05	21%	24 Jul →
mirage	13–8	0.07	20%	24 Jul →
anubis	6–8	-0.06	15%	22 Jul →
anubis	13–3	0.04	12%	22 Jul →
ancient	13–9	-0.03	6%	22 Jul →
anubis	9–13	0.01	15%	22 Jul →
anubis	8–13	0.12	13%	22 Jul →
inferno	7–13	-0.04	22%	20 Jul →
cache	13–6	0.04	18%	19 Jul →
inferno	13–6	0.07	17%	19 Jul →
inferno	4–13	-0.08	13%	19 Jul →
cache	4–13	-0.04	13%	19 Jul →
ancient	13–6	-0.00	15%	19 Jul →
mirage	13–10	0.07	14%	19 Jul →
mirage	16–12	0.05	14%	18 Jul →
ancient	13–9	-0.01	16%	18 Jul →
mirage	13–9	0.01	14%	18 Jul →
ancient	11–1	0.13	4%	18 Jul →
inferno	13–7	0.02	15%	18 Jul →
mirage	6–13	-0.08	9%	18 Jul →
mirage	2–13	-0.11	26%	18 Jul →
cache	13–10	0.03	17%	17 Jul →
dust2	15–15	0.00	13%	17 Jul →
cache	9–13	0.10	9%	16 Jul →
cache	13–6	-0.00	16%	16 Jul →
inferno	9–3	0.16	14%	15 Jul →
inferno	7–9	-0.05	11%	15 Jul →
dust2	13–4	-0.00	10%	15 Jul →
dust2	13–9	-0.00	25%	14 Jul →
mirage	13–8	-0.02	15%	14 Jul →
inferno	12–12	-0.02	17%	14 Jul →
cache	9–13	-0.01	24%	13 Jul →
ancient	11–5	0.03	21%	13 Jul →
inferno	11–13	0.04	24%	12 Jul →
mirage	13–8	-0.00	23%	12 Jul →
cache	11–13	0.00	22%	12 Jul →
nuke	4–9	-0.06	32%	12 Jul →
ancient	9–13	-0.01	22%	11 Jul →
mirage	7–13	-0.04	13%	11 Jul →
anubis	13–9	0.07	27%	11 Jul →
office	5–13	0.12	25%	11 Jul →
mirage	14–16	-0.06	19%	9 Jul →
inferno	15–15	-0.02	9%	9 Jul →
nuke	2–13	-0.01	11%	9 Jul →
office	4–11	-0.04	19%	9 Jul →
office	13–11	0.00	22%	9 Jul →
cache	2–13	0.01	22%	8 Jul →
cache	12–12	0.00	23%	7 Jul →
train	13–8	0.03	15%	18 Jun →
train	10–13	0.03	11%	18 Jun →
train	9–13	0.03	28%	17 Jun →
nuke	9–3	0.20	15%	16 Jun →
cache	5–13	0.03	10%	16 Jun →
cache	13–8	0.12	23%	14 Jun →
mirage	8–11	0.10	24%	7 Jun →
inferno	13–7	0.07	24%	4 Jun →
mirage	7–13	-0.03	11%	3 Jun →
inferno	4–9	-0.09	6%	2 Jun →
train	13–2	0.01	21%	2 Jun →
anubis	7–13	-0.01	8%	1 Jun →
anubis	5–13	0.00	11%	28 May →
nuke	7–9	0.04	13%	27 May →
cache	9–13	0.08	39%	20 May →
cache	12–12	0.01	14%	20 May →
cache	8–13	0.03	28%	18 May →
inferno	9–2	0.34	29%	12 May →
dust2	13–9	0.14	21%	11 May →
mirage	3–13	-0.05	28%	11 May →
anubis	5–13	-0.00	26%	11 May →
cache	13–8	0.05	38%	7 May →
cache	13–4	0.22	14%	7 May →
cache	13–8	0.06	28%	7 May →
cache	10–4	0.09	27%	6 May →
cache	4–13	0.10	23%	4 May →
mirage	13–8	0.10	31%	30 Apr →
nuke	2–9	-0.05	7%	30 Apr →
cache	10–13	0.02	33%	30 Apr →
train	13–8	0.01	16%	25 Apr →
inferno	6–9	-0.08	12%	25 Apr →
train	11–0	0.13	47%	24 Apr →