GGhin_Ping — CS2 Stats

76561198112851675[U:1:152585947]

655Tracked matches44%Win rate2021Tracked since

CSDB Rating4.1 Developing

FaceitLevel 4Top 81.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim41

Positioning44

Utility54

0–100 skill scores via Leetify.

Recent form

STEADY49–42–9Last 10049%Win rateLWWLTWWLLL

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

Player DNA

Aim4.1

Aggression4.0

Utility5.4

Positioning4.4

Opening Duels0.7

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 80% 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 49% on CT to 17% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 640ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% 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

Aim4.1

Positioning4.4

Utility5.4

Mechanics4.3

Opening Duels2.4

Win Impact3.1

Composite 4.1/10 (Developing), 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-0.01+0.01

first ⅓ avg -0.02 → last ⅓ avg -0.01

Reaction time662ms−6ms

first ⅓ avg 669ms → last ⅓ avg 662ms

Headshot accuracy10.5%−3.3%

first ⅓ avg 13.8% → last ⅓ avg 10.5%

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 — nuke 13–1

13–1Biggest win — nuke

7Longest win streak

9–4In matches decided by ≤2 rounds

2Overtime games

Map breakdown

officeBest map · 67% over 9trainWeakest map · 33% over 6

Map	Grade	Played	Record	Win rate	Avg rating
cache	B	34	17–17	50%	-0.01
nuke	C	13	5–8	38%	-0.00
inferno	B	11	5–6	45%	-0.03
office	S	9	6–3	67%	0.02
vertigo	A	9	5–4	56%	-0.04
mirage	A	8	5–3	63%	-0.02
train	D	6	2–4	33%	-0.03
dust2	—	3	2–1	67%	0.01
ancient	—	3	1–2	33%	-0.00
anubis	—	2	1–1	50%	0.00
overpass	—	2	0–2	0%	-0.04

Across the last 100 tracked matches.

Faceit stats

Combat

9Matches

22%Win rate

0.91Avg K/D

—ADR

21%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

1Longest win streak

Recent Faceit resultsLLLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Overpass	3	0%	0.76	12.0
Mirage	2	50%	1.06	19.5
Vertigo	2	0%	1.22	20.5
Inferno	1	100%	1.00	14.0
Ancient	1	0%	0.36	5.0

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.

10.4%Headshot accuracy

35.9%Accuracy (enemy spotted)

37.4%Spray accuracy

69.3%Counter-strafing

12.2°Preaim

640msReaction time

16.6%T opening success

48.8%CT opening success

0.51Enemies flashed / flash

6.0%Flash assists

9.79HE damage / grenade

8.09Flashes / 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 12.1603° — above the 12° mark we flag
Aim Training →
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 10.3527% — below the 15% mark we flag
Aim Training →

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.

33% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
nuke	9–13	-0.01	17%	11 Jul →
inferno	13–11	-0.08	5%	11 Jul →
dust2	13–7	0.03	2%	11 Jul →
cache	3–13	-0.05	15%	11 Jul →
ancient	12–12	-0.03	5%	10 Jul →
mirage	13–11	0.02	12%	10 Jul →
office	13–10	0.01	19%	10 Jul →
office	6–13	-0.06	17%	10 Jul →
mirage	10–13	-0.03	7%	10 Jul →
inferno	9–13	-0.07	9%	8 Jul →
ancient	9–13	0.00	7%	7 Jul →
nuke	13–7	0.04	15%	7 Jul →
cache	13–8	0.02	22%	7 Jul →
office	12–12	0.09	25%	3 Jul →
cache	3–13	-0.06	19%	3 Jul →
cache	13–9	0.11	8%	2 Jul →
cache	3–13	-0.04	7%	2 Jul →
cache	0–13	-0.09	9%	1 Jul →
cache	6–13	-0.06	3%	1 Jul →
nuke	9–13	-0.05	12%	26 Jun →
nuke	8–13	0.06	7%	25 Jun →
cache	12–12	-0.01	5%	24 Jun →
cache	13–5	0.04	10%	24 Jun →
inferno	2–13	-0.05	0%	23 Jun →
nuke	13–1	0.15	5%	23 Jun →
ancient	13–10	0.02	11%	22 Jun →
office	13–11	0.04	7%	21 Jun →
cache	7–13	-0.04	7%	20 Jun →
mirage	10–13	-0.11	10%	19 Jun →
cache	13–3	-0.01	11%	19 Jun →
train	7–13	-0.04	3%	18 Jun →
train	2–13	-0.08	22%	18 Jun →
train	13–1	0.01	14%	18 Jun →
inferno	13–5	0.00	10%	12 Jun →
cache	13–7	0.02	14%	12 Jun →
cache	13–8	-0.03	20%	9 Jun →
nuke	8–13	-0.04	10%	9 Jun →
cache	12–12	-0.01	8%	8 Jun →
vertigo	12–12	-0.01	11%	3 Jun →
vertigo	13–5	-0.08	10%	3 Jun →
vertigo	8–13	0.07	9%	3 Jun →
cache	4–1	-0.01	23%	2 Jun →
cache	11–13	-0.03	9%	2 Jun →
inferno	13–10	-0.04	6%	2 Jun →
cache	6–13	0.01	22%	1 Jun →
anubis	7–13	-0.06	17%	1 Jun →
mirage	9–13	-0.07	11%	1 Jun →
anubis	13–9	0.07	10%	31 May →
vertigo	13–9	-0.08	13%	25 May →
cache	13–8	0.06	8%	24 May →
mirage	13–6	0.00	16%	23 May →
cache	13–10	0.05	6%	22 May →
cache	13–6	0.11	9%	21 May →
cache	13–5	0.00	18%	21 May →
cache	11–13	-0.03	17%	16 May →
cache	13–7	0.05	13%	15 May →
cache	9–13	-0.05	17%	15 May →
cache	1–8	-0.04	21%	15 May →
office	13–3	0.07	18%	14 May →
office	13–9	0.11	15%	14 May →
office	7–13	-0.10	20%	14 May →
cache	13–2	0.07	15%	8 May →
cache	13–10	-0.07	13%	7 May →
cache	13–11	-0.00	12%	7 May →
cache	7–13	0.01	9%	1 May →
cache	3–13	-0.03	11%	1 May →
cache	9–13	0.01	18%	29 Apr →
cache	8–2	-0.07	29%	29 Apr →
cache	11–13	-0.04	20%	29 Apr →
cache	13–6	0.00	21%	28 Apr →
inferno	13–10	-0.02	18%	28 Apr →
vertigo	12–12	-0.01	13%	27 Apr →
office	13–11	0.01	14%	22 Apr →
inferno	6–13	-0.04	16%	22 Apr →
train	8–13	-0.03	7%	22 Apr →
train	6–13	-0.02	22%	22 Apr →
nuke	12–12	-0.08	3%	22 Apr →
dust2	16–14	-0.03	16%	21 Apr →
vertigo	13–2	-0.04	7%	21 Apr →
nuke	7–13	0.02	13%	21 Apr →
mirage	13–10	-0.00	16%	21 Apr →
mirage	13–6	0.00	11%	21 Apr →
mirage	13–3	0.05	17%	21 Apr →
inferno	6–13	-0.02	12%	20 Apr →
inferno	13–4	0.02	14%	20 Apr →
overpass	5–13	-0.04	10%	20 Apr →
inferno	15–15	-0.01	5%	20 Apr →
office	13–11	-0.00	11%	19 Apr →
train	13–7	-0.01	19%	19 Apr →
nuke	13–10	-0.02	17%	15 Apr →
nuke	13–11	0.05	6%	14 Apr →
nuke	13–10	-0.06	16%	14 Apr →
nuke	4–13	-0.04	14%	13 Apr →
dust2	5–13	0.03	16%	13 Apr →
vertigo	13–9	-0.12	10%	9 Apr →
vertigo	3–13	-0.02	10%	9 Apr →
vertigo	13–11	-0.05	6%	9 Apr →
nuke	12–12	-0.03	15%	6 Apr →
inferno	7–13	-0.05	24%	6 Apr →
overpass	11–13	-0.03	8%	6 Apr →