pk — CS2 Stats

76561198189118237[U:1:228852509]

4,664Tracked matches50%Win rate2020Tracked since

CSDB Rating5.2 DevelopingHybrid Rifler

FaceitLevel 10 · 2,018 ELOTop 12.4% of ranked FACEIT players

WingmanGold Nova I

Ladder ranks via Leetify

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Performance scores

Aim64

Positioning54

Utility48

0–100 skill scores via Leetify.

Recent form

STEADY53–46–1Last 10053%Win rateLWLLWWWLLL

Last 10 vs previous 10: -20pp win rate · +0.02 avg rating

Player DNA

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

Aim6.4

Aggression7.0

Utility4.8

Positioning5.4

Opening Duels3.0

Clutch2.8

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 88% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

Where you differ: lower opening-duel success; 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. 586ms 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

Aim6.4

Positioning5.4

Utility4.8

Mechanics4.4

Opening Duels3.0

Win Impact5.0

Composite 5.2/10 (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-0.01−0.02

first ⅓ avg 0.01 → last ⅓ avg -0.01

Reaction time591ms+50ms

first ⅓ avg 541ms → last ⅓ avg 591ms

Headshot accuracy16.2%−2.5%

first ⅓ avg 18.6% → last ⅓ avg 16.2%

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 — overpass 13–10

13–1Biggest win — nuke

5Longest win streak

10–6In matches decided by ≤2 rounds

8Overtime games

Map breakdown

mirageBest map · 75% over 12infernoWeakest map · 26% over 19

Map	Grade	Played	Record	Win rate	Avg rating
nuke	A	20	12–8	60%	0.02
inferno	D	19	5–14	26%	-0.01
anubis	C	18	8–10	44%	-0.01
mirage	S	12	9–3	75%	0.01
cache	A	10	6–4	60%	0.02
overpass	A	8	5–3	63%	0.00
ancient	C	7	3–4	43%	0.01
dust2	—	3	3–0	100%	0.01
train	—	2	1–1	50%	0.01
vertigo	—	1	1–0	100%	0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (26% over 19). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

4,064Matches

50%Win rate

0.98Avg K/D

73.9ADR

43%Headshot %

Clutches & streaks

34%1v1 clutch win

18%1v2 clutch win

10Longest win streak

Recent Faceit resultsWWLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	312	53%	1.00	15.4
Anubis	264	47%	1.02	15.1
Nuke	216	60%	1.06	14.9
Mirage	184	47%	0.86	12.9
Ancient	137	38%	0.84	13.3
Train	59	61%	1.00	15.8
Overpass	41	41%	0.88	13.8
Vertigo	37	46%	0.85	14.1

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.

16.2%Headshot accuracy

34.7%Accuracy (enemy spotted)

40.2%Spray accuracy

70.0%Counter-strafing

9.5°Preaim

586msReaction time

37.1%T opening success

46.7%CT opening success

0.43Enemies flashed / flash

3.7%Flash assists

8.58HE damage / grenade

9.78Flashes / 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 0.4303 — below the 0.5 mark we flag
Grenade Lineups →
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 37.0886% — 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.

26% win rate across 19 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
anubis	6–13	-0.07	4%	26 Aug →
cache	13–11	0.01	16%	26 Aug →
inferno	6–13	-0.05	24%	26 Aug →
cache	19–22	-0.02	13%	22 Aug →
cache	13–11	-0.02	8%	13 Aug →
anubis	13–7	0.01	21%	11 Aug →
cache	13–3	0.04	17%	11 Aug →
cache	9–13	0.03	32%	28 Jul →
inferno	3–6	0.05	19%	27 Jul →
inferno	0–4	-0.03	0%	26 Jul →
anubis	10–13	0.02	21%	26 Jul →
train	5–13	-0.09	6%	23 Jul →
mirage	13–6	-0.01	10%	20 Jul →
anubis	16–14	-0.03	23%	20 Jul →
overpass	3–13	-0.09	11%	1 Jul →
dust2	13–9	-0.01	24%	24 Jun →
inferno	13–4	-0.02	14%	24 Jun →
inferno	13–10	-0.00	16%	21 Jun →
nuke	13–9	-0.01	11%	17 Jun →
nuke	2–13	0.02	12%	13 Jun →
mirage	13–6	0.06	20%	9 Jun →
inferno	9–13	-0.07	16%	27 May →
inferno	6–13	0.09	10%	24 May →
cache	13–11	0.07	19%	21 May →
inferno	11–13	-0.02	20%	12 May →
inferno	13–7	-0.04	15%	11 May →
cache	9–13	0.01	18%	8 May →
cache	13–9	0.06	12%	8 May →
cache	8–13	-0.07	6%	7 May →
overpass	13–3	0.01	35%	7 May →
mirage	15–15	0.02	14%	27 Apr →
inferno	11–13	-0.05	29%	24 Apr →
inferno	11–13	-0.02	17%	23 Apr →
mirage	13–11	-0.05	16%	23 Apr →
overpass	13–4	0.00	11%	23 Apr →
mirage	9–13	-0.02	15%	23 Apr →
cache	13–8	0.06	6%	23 Apr →
mirage	13–8	-0.03	10%	23 Apr →
dust2	13–7	-0.01	6%	22 Apr →
mirage	13–6	0.05	24%	22 Apr →
anubis	13–10	-0.05	15%	16 Apr →
ancient	10–13	-0.01	15%	16 Apr →
nuke	13–2	0.02	30%	16 Apr →
ancient	13–9	0.04	18%	15 Apr →
nuke	13–9	0.10	19%	15 Apr →
overpass	3–13	-0.04	20%	14 Apr →
inferno	16–14	-0.05	7%	13 Apr →
vertigo	13–11	0.01	24%	10 Apr →
dust2	16–13	0.04	20%	9 Apr →
anubis	13–16	-0.05	6%	9 Apr →
nuke	1–13	-0.09	15%	9 Apr →
anubis	6–13	-0.01	5%	3 Apr →
mirage	5–13	-0.02	15%	1 Apr →
mirage	13–2	0.04	12%	1 Apr →
nuke	9–1	0.09	15%	1 Apr →
anubis	13–8	0.01	15%	1 Apr →
anubis	9–13	-0.03	27%	1 Apr →
ancient	3–13	-0.03	17%	30 Mar →
anubis	6–13	-0.10	9%	30 Mar →
inferno	19–22	-0.03	17%	29 Mar →
mirage	13–9	-0.03	14%	29 Mar →
overpass	8–13	0.04	16%	23 Mar →
ancient	11–0	0.10	8%	23 Mar →
overpass	13–10	0.11	14%	22 Mar →
anubis	13–9	0.02	15%	22 Mar →
anubis	13–7	0.07	6%	21 Mar →
nuke	6–13	-0.02	9%	21 Mar →
inferno	11–13	0.04	25%	21 Mar →
anubis	3–13	0.02	14%	21 Mar →
nuke	7–13	-0.06	17%	21 Mar →
inferno	6–13	0.04	31%	20 Mar →
anubis	13–4	0.08	12%	20 Mar →
nuke	3–0	0.06	18%	20 Mar →
ancient	9–13	-0.02	13%	20 Mar →
overpass	13–5	-0.07	5%	19 Mar →
nuke	13–7	0.03	32%	19 Mar →
nuke	7–13	0.04	14%	19 Mar →
nuke	13–10	-0.01	17%	19 Mar →
nuke	11–13	0.02	21%	18 Mar →
inferno	5–13	0.01	25%	17 Mar →
nuke	13–1	0.07	26%	17 Mar →
mirage	13–8	0.05	20%	17 Mar →
anubis	6–13	-0.06	17%	16 Mar →
mirage	13–5	0.09	12%	15 Mar →
ancient	13–6	0.06	11%	13 Mar →
ancient	5–13	-0.04	20%	13 Mar →
nuke	11–13	0.04	24%	13 Mar →
overpass	13–5	0.03	17%	12 Mar →
train	13–1	0.11	15%	12 Mar →
nuke	4–13	-0.04	29%	12 Mar →
nuke	19–17	-0.02	22%	11 Mar →
anubis	13–5	-0.01	10%	11 Mar →
anubis	7–13	-0.02	13%	10 Mar →
nuke	13–6	0.07	18%	9 Mar →
inferno	9–13	0.00	18%	9 Mar →
nuke	13–11	0.02	26%	7 Mar →
inferno	7–13	0.01	15%	6 Mar →
nuke	13–8	-0.00	17%	5 Mar →
inferno	13–11	-0.03	18%	5 Mar →
anubis	9–13	-0.04	22%	5 Mar →