Pinhas ❟❛❟ — CS2 Stats

PT76561199152164126[U:1:1191898398]Steam profile ↗community banned

1,721Tracked matches62%Win rate2021Tracked since

CSDB Rating5.6 SolidHybrid Rifler

FaceitLevel 8 · 1,815 ELOTop 31.2% of ranked FACEIT players

WingmanGold Nova Master

Ladder ranks via Leetify

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Performance scores

Aim63

Positioning63

Utility28

0–100 skill scores via Leetify.

Recent form

STEADY52–44–4Last 10052%Win rateLWWLLLWWWW

Last 10 vs previous 10: +0pp win rate · +0.03 avg rating

Player DNA

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

Aim6.3

Aggression10.0

Utility2.8

Positioning6.3

Opening Duels4.6

Clutch2.0

Limited utility dependence

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 device 84% playstyle similarity

Most alike: positioning profile, opening-fight frequency.

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.

Reaction time. 600ms 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

Aim6.3

Positioning6.3

Utility2.8

Mechanics6.6

Opening Duels4.6

Win Impact9.0

Composite 5.6/10 (Solid), 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 rating0.01+0.01

first ⅓ avg 0.01 → last ⅓ avg 0.01

Reaction time623ms−47ms

first ⅓ avg 669ms → last ⅓ avg 623ms

Headshot accuracy21.0%+0.2%

first ⅓ avg 20.8% → last ⅓ avg 21.0%

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 — ancient 9–13

13–1Biggest win — ancient

7Longest win streak

12–7In matches decided by ≤2 rounds

15Overtime games

Map breakdown

trainBest map · 71% over 7ancientWeakest map · 33% over 12

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	40	19–21	48%	0.01
ancient	D	12	4–8	33%	0.02
nuke	A	12	7–5	58%	-0.01
inferno	S	10	7–3	70%	0.03
dust2	A	10	6–4	60%	0.01
train	S	7	5–2	71%	-0.00
anubis	—	4	2–2	50%	0.01
vertigo	—	2	0–2	0%	-0.01
overpass	—	2	1–1	50%	-0.02
cache	—	1	1–0	100%	0.02

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (33% over 12). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

614Matches

52%Win rate

1.17Avg K/D

87.9ADR

41%Headshot %

Clutches & streaks

30%1v1 clutch win

21%1v2 clutch win

9Longest win streak

Recent Faceit resultsWLWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	157	55%	1.31	19.4
Ancient	80	59%	1.20	19.2
Dust2	43	47%	1.17	19.6
Inferno	33	52%	1.07	15.9
Nuke	27	41%	0.95	16.7
Anubis	26	38%	1.01	17.4
Vertigo	20	35%	1.11	18.0
Train	16	44%	1.20	16.9

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.

18.5%Headshot accuracy

33.7%Accuracy (enemy spotted)

31.7%Spray accuracy

79.7%Counter-strafing

10.0°Preaim

600msReaction time

49.1%T opening success

47.8%CT opening success

0.27Enemies flashed / flash

8.7%Flash assists

9.80HE damage / grenade

3.09Flashes / 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.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.2719 — below the 0.5 mark we flag
Grenade Lineups →

Spend your practice time on Ancient

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 12 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
vertigo	6–13	-0.05	11%	22 Aug →
mirage	13–7	0.11	15%	22 Aug →
mirage	13–2	0.10	23%	20 Aug →
vertigo	9–13	0.04	18%	18 Aug →
mirage	11–13	0.03	10%	18 Aug →
anubis	7–13	-0.02	16%	14 Aug →
inferno	13–11	0.04	21%	26 Jul →
ancient	13–1	0.13	22%	25 Jul →
ancient	13–11	0.01	13%	4 Jul →
anubis	13–9	-0.01	17%	4 Jul →
mirage	13–4	0.04	22%	17 Jun →
nuke	16–14	-0.03	17%	4 Jun →
nuke	13–8	-0.00	33%	24 May →
mirage	3–13	-0.06	14%	16 May →
cache	13–10	0.02	15%	1 May →
mirage	15–15	-0.05	23%	26 Apr →
mirage	13–3	0.01	29%	24 Apr →
dust2	7–13	0.02	19%	11 Apr →
inferno	13–5	0.09	34%	5 Apr →
inferno	7–13	0.03	100%	28 Mar →
nuke	10–13	-0.10	11%	28 Mar →
mirage	13–3	-0.05	22%	21 Mar →
mirage	13–11	0.06	15%	21 Mar →
ancient	8–13	0.00	15%	14 Mar →
nuke	7–13	-0.04	15%	14 Mar →
mirage	11–13	0.11	21%	11 Mar →
mirage	13–11	0.01	15%	11 Mar →
ancient	13–6	-0.05	22%	11 Mar →
inferno	13–6	0.02	16%	7 Mar →
mirage	13–4	0.00	12%	7 Mar →
dust2	13–7	0.03	16%	7 Mar →
inferno	13–8	0.02	4%	6 Mar →
nuke	9–2	0.04	37%	27 Feb →
mirage	11–13	0.01	14%	27 Feb →
ancient	9–13	0.01	19%	27 Feb →
mirage	6–13	0.09	34%	27 Feb →
dust2	10–13	0.03	19%	17 Feb →
mirage	13–16	0.01	17%	4 Feb →
mirage	6–13	0.02	23%	25 Jan →
mirage	11–13	0.03	17%	24 Jan →
dust2	8–0	0.02	50%	23 Jan →
mirage	13–7	0.02	30%	23 Jan →
inferno	13–8	0.09	23%	12 Jan →
mirage	2–13	-0.09	20%	22 Dec →
mirage	5–13	-0.04	22%	6 Dec →
nuke	2–13	0.00	0%	1 Dec →
ancient	15–15	-0.01	17%	29 Nov →
dust2	16–14	0.01	11%	29 Nov →
train	7–13	-0.01	12%	22 Nov →
mirage	8–13	-0.01	24%	22 Nov →
mirage	13–1	-0.01	6%	21 Nov →
mirage	3–13	-0.07	40%	21 Nov →
overpass	13–10	-0.03	18%	15 Nov →
inferno	1–9	-0.07	21%	26 Oct →
train	13–11	-0.02	27%	26 Oct →
mirage	6–13	0.07	11%	24 Oct →
mirage	16–12	0.02	11%	24 Oct →
ancient	2–13	-0.11	21%	24 Oct →
nuke	9–4	-0.02	29%	24 Oct →
mirage	16–12	-0.04	21%	17 Oct →
mirage	13–8	0.01	17%	17 Oct →
dust2	13–6	0.00	43%	17 Oct →
mirage	13–9	-0.03	11%	11 Oct →
mirage	6–13	-0.00	24%	10 Oct →
mirage	13–3	0.04	11%	10 Oct →
dust2	13–9	0.02	11%	10 Oct →
train	16–14	0.01	22%	4 Oct →
dust2	11–13	-0.04	25%	4 Oct →
inferno	13–5	0.03	21%	4 Oct →
mirage	4–13	-0.05	43%	3 Oct →
train	13–9	-0.02	15%	26 Sept →
overpass	10–13	-0.01	19%	26 Sept →
mirage	13–9	-0.04	14%	26 Sept →
nuke	3–9	-0.12	10%	22 Sept →
ancient	10–13	-0.07	11%	17 Sept →
mirage	7–13	-0.03	19%	17 Sept →
nuke	13–1	0.08	24%	17 Sept →
mirage	16–12	-0.03	4%	15 Sept →
mirage	5–13	-0.06	41%	12 Sept →
ancient	8–13	0.02	24%	10 Sept →
ancient	13–6	0.06	28%	10 Sept →
train	13–3	0.05	22%	26 Aug →
mirage	13–9	0.07	19%	28 Jul →
train	13–11	0.01	27%	28 Jul →
mirage	15–15	0.01	17%	23 Jul →
anubis	16–13	0.08	20%	10 Jul →
train	15–15	-0.03	20%	9 Jul →
dust2	16–14	-0.02	29%	9 Jul →
ancient	9–13	0.24	24%	6 Jul →
ancient	12–16	0.02	22%	3 Jul →
inferno	9–7	0.08	8%	29 Jun →
mirage	14–16	0.07	18%	22 Jun →
nuke	13–7	0.04	17%	19 Jun →
anubis	6–13	-0.00	30%	14 Jun →
nuke	10–13	-0.09	23%	1 Jun →
mirage	3–13	-0.07	0%	1 Jun →
inferno	11–13	-0.04	20%	25 May →
dust2	6–13	-0.01	23%	14 May →
nuke	9–7	0.09	24%	2 May →
mirage	13–10	0.02	27%	1 May →