Pal0kaz — CS2 Stats

76561198111727484[U:1:151461756]✓ No bans

1,632Tracked matches59%Win rate2020Tracked since

CSDB Rating6.4 SolidHybrid Rifler

FaceitLevel 10 · 2,289 ELOTop 12.4% of ranked FACEIT players

WingmanSupreme Master First Class

Ladder ranks via Leetify

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Performance scores

Aim85

Positioning51

Utility56

0–100 skill scores via Leetify.

Recent form

COLD53–37–10Last 10053%Win rateTLLLWLLWTW

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.

Aim8.5

Aggression5.5

Utility5.6

Positioning5.1

Opening Duels1.9

Clutch3.2

Sharp aimerStrong 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 93% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

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

Strengths

Aim. Aim score of 85 — the mechanical foundation is a clear strength.

Areas to improve

Positioning. Positioning trails aim by 35 points — deaths here waste a strong aim profile.

T-side openings. Opening success drops from 47% on CT to 28% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 590ms 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

Aim8.5

Positioning5.1

Utility5.6

Mechanics6.6

Opening Duels2.1

Win Impact8.1

Composite 6.4/10 (Solid), 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 rating0.03+0.00

first ⅓ avg 0.03 → last ⅓ avg 0.03

Reaction time579ms+23ms

first ⅓ avg 556ms → last ⅓ avg 579ms

Headshot accuracy27.1%−2.0%

first ⅓ avg 29.1% → last ⅓ avg 27.1%

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

0.20Best rating — overpass 9–0

13–1Biggest win — cache

8Longest win streak

8–2In matches decided by ≤2 rounds

9Overtime games

Map breakdown

cacheBest map · 67% over 9anubisWeakest map · 40% over 5

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	30	15–15	50%	0.04
dust2	A	21	13–8	62%	0.04
inferno	C	14	6–8	43%	0.04
cache	S	9	6–3	67%	0.02
ancient	A	7	4–3	57%	0.03
anubis	C	5	2–3	40%	0.03
overpass	—	4	3–1	75%	0.08
poseidon	—	3	0–3	0%	-0.02
nuke	—	3	1–2	33%	-0.00
vertigo	—	2	2–0	100%	0.11
office	—	2	1–1	50%	0.10

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (40% over 5). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,945Matches

53%Win rate

1.21Avg K/D

78.5ADR

55%Headshot %

Clutches & streaks

36%1v1 clutch win

24%1v2 clutch win

10Longest win streak

Recent Faceit resultsLWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	90	56%	1.56	16.5
Dust2	79	51%	1.18	15.8
Ancient	63	57%	1.24	15.9
Inferno	61	56%	1.19	15.4
Anubis	28	57%	1.27	18.9
Nuke	26	65%	1.51	17.2
Overpass	26	69%	1.11	14.5
Train	19	47%	1.19	13.5

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.

27.0%Headshot accuracy

37.1%Accuracy (enemy spotted)

36.0%Spray accuracy

79.5%Counter-strafing

7.9°Preaim

590msReaction time

28.5%T opening success

46.8%CT opening success

0.60Enemies flashed / flash

5.8%Flash assists

6.99HE damage / grenade

7.01Flashes / 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
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 28.4976% — below the 40% mark we flag

Spend your practice time on Anubis

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

40% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
ancient	12–12	0.03	38%	7 Aug →
anubis	9–13	0.10	24%	25 Jul →
mirage	10–13	0.03	20%	24 Jul →
mirage	4–13	-0.05	21%	24 Jul →
mirage	13–9	0.06	33%	24 Jul →
dust2	6–13	0.05	43%	23 Jul →
ancient	10–13	0.04	31%	23 Jul →
cache	13–11	-0.04	25%	22 Jul →
mirage	15–15	0.05	23%	22 Jul →
mirage	13–2	0.02	25%	22 Jul →
cache	10–13	0.02	19%	20 Jul →
cache	13–11	0.07	32%	19 Jul →
vertigo	10–4	0.03	24%	12 Jul →
office	13–8	0.14	37%	12 Jul →
ancient	13–3	-0.04	12%	11 Jul →
dust2	12–12	0.06	26%	1 Jul →
cache	7–13	-0.00	31%	1 Jul →
mirage	2–13	0.04	26%	1 Jul →
mirage	3–9	-0.07	73%	30 Jun →
poseidon	5–9	-0.03	30%	26 Jun →
anubis	4–0	0.02	33%	26 Jun →
cache	13–8	-0.08	29%	26 Jun →
dust2	7–13	-0.01	24%	17 Jun →
anubis	19–16	0.00	16%	16 Jun →
mirage	12–16	-0.04	20%	16 Jun →
dust2	13–9	0.08	26%	15 Jun →
mirage	13–11	0.01	14%	15 Jun →
dust2	13–8	0.06	28%	15 Jun →
dust2	13–5	-0.02	33%	14 Jun →
overpass	13–7	0.15	34%	14 Jun →
inferno	9–0	0.00	0%	11 Jun →
mirage	13–3	0.13	24%	11 Jun →
ancient	13–8	0.09	20%	11 Jun →
mirage	6–13	-0.11	36%	11 Jun →
overpass	9–0	0.20	39%	10 Jun →
mirage	13–3	0.06	32%	6 Jun →
inferno	16–14	0.06	28%	4 Jun →
dust2	11–3	0.05	25%	4 Jun →
ancient	13–9	0.05	24%	31 May →
office	12–12	0.06	23%	27 May →
mirage	13–9	0.01	28%	23 May →
anubis	11–13	0.03	23%	15 May →
cache	13–8	0.05	22%	14 May →
poseidon	3–9	-0.02	42%	13 May →
ancient	4–13	0.02	35%	13 May →
mirage	13–9	0.10	33%	11 May →
inferno	8–8	0.06	25%	10 May →
inferno	5–13	-0.03	32%	7 May →
mirage	13–10	0.16	42%	1 May →
cache	13–1	0.13	21%	1 May →
cache	2–13	-0.06	37%	1 May →
cache	13–8	0.06	52%	29 Apr →
inferno	15–15	0.10	26%	27 Apr →
dust2	16–13	0.13	40%	21 Apr →
mirage	9–13	0.02	26%	17 Apr →
inferno	13–1	0.02	20%	16 Apr →
dust2	13–8	0.07	25%	12 Apr →
dust2	13–1	0.03	38%	12 Apr →
overpass	8–13	-0.03	35%	4 Apr →
mirage	13–5	0.08	56%	29 Mar →
mirage	16–14	0.05	28%	21 Mar →
dust2	11–13	-0.03	27%	21 Mar →
dust2	13–11	0.10	34%	21 Mar →
mirage	7–13	0.14	26%	21 Mar →
dust2	13–1	0.07	20%	21 Mar →
vertigo	9–3	0.18	42%	18 Mar →
dust2	15–15	0.04	35%	17 Mar →
inferno	5–13	0.08	23%	17 Mar →
mirage	10–13	-0.01	28%	11 Mar →
poseidon	6–9	0.01	20%	7 Mar →
nuke	13–8	0.05	37%	4 Mar →
mirage	13–5	0.05	31%	4 Mar →
dust2	6–1	0.12	23%	4 Mar →
dust2	13–5	-0.00	25%	25 Feb →
overpass	13–8	-0.03	23%	23 Feb →
nuke	3–13	-0.06	20%	18 Feb →
anubis	9–13	0.01	31%	17 Feb →
dust2	9–13	-0.02	32%	17 Feb →
mirage	8–13	-0.02	22%	16 Feb →
mirage	13–10	0.18	48%	16 Feb →
inferno	13–1	-0.01	45%	16 Feb →
dust2	6–13	0.01	43%	16 Feb →
mirage	12–12	0.05	31%	15 Feb →
inferno	1–13	0.02	30%	13 Feb →
mirage	13–16	0.02	32%	8 Feb →
inferno	6–13	-0.06	21%	7 Feb →
mirage	6–13	-0.04	50%	7 Feb →
dust2	13–10	-0.00	32%	3 Feb →
mirage	13–9	0.02	17%	3 Feb →
inferno	12–12	0.07	25%	31 Jan →
ancient	13–11	0.05	14%	14 Jan →
inferno	12–12	0.09	28%	13 Jan →
nuke	7–13	0.01	21%	9 Jan →
inferno	13–8	0.05	34%	7 Jan →
mirage	12–5	0.11	33%	6 Jan →
mirage	7–13	-0.04	34%	6 Jan →
mirage	13–8	0.14	34%	3 Jan →
inferno	13–5	0.06	24%	3 Jan →
dust2	13–11	0.04	25%	30 Dec →
dust2	8–13	-0.05	21%	30 Dec →