PA1N — CS2 Stats

US76561198110580276[U:1:150314548]Steam profile ↗✓ No bans

1,236Tracked matches55%Win rate2020Tracked since

CSDB Rating5.5 SolidHybrid Rifler

Premier CS Rating21,104Top 50% of 17,162 CSDB-tracked playersPink band · top ~7.3% of ranked players (population est.)

Ladder ranks via Leetify

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Performance scores

Aim60

Positioning57

Utility30

0–100 skill scores via Leetify.

Recent form

HOT56–42–2Last 10056%Win rateWWWWWWLWLW

Last 10 vs previous 10: +50pp win rate · +0.01 avg rating

Player DNA

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

Aim6.0

Aggression7.1

Utility3.0

Positioning5.7

Opening Duels2.6

Clutch7.0

Limited utility dependenceReliable in 1v1s

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 ropz 83% 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

Reaction time. 619ms 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

Aim6.0

Positioning5.7

Utility3.0

Mechanics7.0

Opening Duels2.6

Win Impact6.7

Composite 5.5/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.00

first ⅓ avg -0.00 → last ⅓ avg -0.01

Reaction time616ms−15ms

first ⅓ avg 631ms → last ⅓ avg 616ms

Headshot accuracy16.0%+0.3%

first ⅓ avg 15.7% → last ⅓ avg 16.0%

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

0.11Best rating — ancient 13–5

13–2Biggest win — overpass

6Longest win streak

W6Current streak

9–10In matches decided by ≤2 rounds

11Overtime games

Map breakdown

mirageBest map · 67% over 15infernoWeakest map · 48% over 21

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	22	13–9	59%	-0.00
inferno	B	21	10–11	48%	-0.01
ancient	A	16	9–7	56%	0.00
mirage	S	15	10–5	67%	0.00
anubis	A	11	6–5	55%	0.01
nuke	B	10	5–5	50%	-0.00
cache	—	3	1–2	33%	-0.02
overpass	—	2	2–0	100%	0.06

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (48% over 21). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

220Matches

51%Win rate

1.32Avg K/D

89.0ADR

45%Headshot %

Clutches & streaks

55%1v1 clutch win

27%1v2 clutch win

8Longest win streak

Recent Faceit resultsLLWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	38	68%	1.61	17.8
Mirage	34	50%	1.28	18.6
Dust2	31	39%	1.22	15.3
Anubis	28	46%	1.19	16.8
Ancient	22	41%	1.15	16.1
Nuke	15	47%	1.33	18.1
Vertigo	7	57%	1.12	16.7
Overpass	2	50%	2.06	25.5

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.

16.6%Headshot accuracy

32.1%Accuracy (enemy spotted)

32.1%Spray accuracy

81.3%Counter-strafing

9.4°Preaim

619msReaction time

44.9%T opening success

36.0%CT opening success

0.28Enemies flashed / flash

2.9%Flash assists

13.71HE damage / grenade

1.95Flashes / 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 0.2773 — below the 0.5 mark we flag
Grenade Lineups →
Advanced Mechanics
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 36.0298% — below the 40% mark we flag

Spend your practice time on Inferno

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

48% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
inferno	13–5	-0.02	17%	28 Aug →
ancient	13–7	0.02	30%	28 Aug →
mirage	13–7	0.08	17%	27 Aug →
mirage	13–9	-0.05	8%	26 Aug →
dust2	16–12	0.03	23%	21 Aug →
dust2	13–5	-0.03	28%	21 Aug →
cache	7–13	-0.02	24%	21 Aug →
inferno	13–10	-0.01	23%	21 Aug →
anubis	5–13	-0.02	5%	21 Aug →
ancient	13–5	0.03	11%	16 Aug →
cache	4–13	-0.04	11%	15 Aug →
anubis	13–8	0.02	17%	5 Aug →
mirage	13–11	0.04	18%	5 Aug →
cache	13–11	-0.01	13%	3 Aug →
ancient	11–13	-0.04	13%	3 Aug →
anubis	5–13	-0.04	13%	26 Jul →
ancient	14–16	-0.01	15%	10 Jul →
anubis	9–13	0.01	19%	19 Jun →
inferno	15–15	-0.02	33%	25 May →
inferno	3–13	0.03	15%	22 May →
dust2	5–13	-0.06	14%	25 Apr →
inferno	0–13	-0.04	11%	17 Apr →
nuke	3–13	-0.04	7%	16 Apr →
ancient	13–10	-0.05	9%	10 Apr →
inferno	13–7	0.03	23%	5 Apr →
mirage	13–9	0.00	10%	2 Apr →
ancient	3–13	-0.05	6%	2 Apr →
ancient	2–13	-0.03	30%	2 Apr →
anubis	13–9	0.05	16%	31 Mar →
ancient	13–8	0.02	9%	15 Mar →
dust2	13–5	0.01	17%	15 Mar →
anubis	13–9	0.04	14%	15 Mar →
inferno	6–13	-0.03	13%	13 Mar →
inferno	16–14	-0.01	16%	12 Mar →
nuke	13–10	0.04	22%	12 Mar →
inferno	9–1	0.04	29%	12 Mar →
nuke	13–8	0.03	17%	10 Mar →
mirage	13–7	0.06	18%	9 Mar →
inferno	13–11	-0.02	22%	6 Mar →
inferno	11–13	0.00	14%	5 Mar →
inferno	13–6	0.04	16%	26 Feb →
nuke	11–13	-0.06	16%	25 Feb →
mirage	13–10	0.04	19%	24 Feb →
ancient	17–19	-0.04	12%	24 Feb →
anubis	13–7	0.05	16%	17 Feb →
anubis	13–9	-0.02	15%	12 Feb →
mirage	13–9	0.01	16%	11 Feb →
inferno	8–13	-0.01	17%	10 Feb →
dust2	13–6	0.08	31%	10 Feb →
overpass	13–2	0.06	16%	5 Feb →
mirage	5–13	-0.07	4%	5 Feb →
ancient	13–7	0.04	30%	5 Feb →
inferno	11–13	0.01	20%	8 Jan →
nuke	14–16	0.04	22%	4 Jan →
dust2	13–7	0.06	27%	4 Jan →
nuke	10–13	-0.01	17%	28 Oct →
dust2	10–13	-0.01	0%	28 Oct →
dust2	8–13	-0.05	33%	24 Oct →
dust2	13–4	0.07	20%	23 Oct →
dust2	2–13	-0.08	27%	10 Oct →
overpass	13–11	0.06	17%	10 Oct →
mirage	9–13	0.00	9%	12 Sept →
mirage	13–9	0.06	14%	29 Aug →
dust2	13–11	-0.03	17%	15 Aug →
inferno	13–8	-0.02	7%	14 Aug →
nuke	16–12	-0.03	14%	14 Aug →
dust2	11–13	0.02	19%	13 Aug →
dust2	10–13	-0.02	12%	17 Jul →
dust2	13–10	-0.04	15%	16 Jul →
nuke	13–3	0.08	11%	16 Jul →
ancient	6–13	-0.01	17%	10 Jul →
nuke	8–13	0.00	22%	8 Jul →
inferno	7–13	0.00	27%	8 Jul →
inferno	13–5	0.02	10%	7 Jul →
dust2	8–13	-0.06	25%	4 Jul →
ancient	13–5	0.11	20%	4 Jul →
dust2	19–17	-0.07	14%	3 Jul →
nuke	13–10	-0.05	6%	26 Jun →
mirage	10–13	-0.04	12%	12 Jun →
ancient	13–9	-0.02	7%	12 Jun →
dust2	13–5	0.02	19%	6 Jun →
dust2	7–13	0.02	15%	5 Jun →
anubis	13–11	0.08	6%	5 Jun →
dust2	13–5	0.05	24%	4 Jun →
anubis	11–13	-0.04	14%	3 Jun →
inferno	7–13	-0.03	21%	3 Jun →
mirage	13–7	-0.06	11%	3 Jun →
mirage	16–13	-0.03	27%	29 May →
ancient	13–5	0.04	14%	29 May →
mirage	7–13	0.01	13%	26 May →
dust2	13–10	0.09	19%	17 May →
inferno	13–4	0.03	9%	17 May →
anubis	1–13	-0.06	8%	17 May →
inferno	3–13	-0.03	23%	10 May →
mirage	15–15	-0.02	12%	3 May →
dust2	14–16	-0.06	26%	3 May →
ancient	6–13	-0.04	17%	2 May →
inferno	10–13	-0.06	14%	30 Apr →
dust2	13–10	0.02	14%	30 Apr →
ancient	13–11	0.06	19%	30 Apr →