Panzerby (nie toxic) — CS2 Stats

DE76561198060774341[U:1:100508613]Steam profile ↗✓ No bans

1,677Tracked matches77%Win rate2020Tracked since

CSDB Rating6.7 SolidHybrid Rifler

WingmanSupreme Master First Class

Ladder ranks via Leetify

Performance scores

Aim77

Positioning57

Utility65

0–100 skill scores via Leetify.

Recent form

HOT63–36–1Last 10063%Win rateWWWWLWWWWL

Last 10 vs previous 10: +0pp win rate · -0.00 avg rating

Player DNA

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

Aim7.7

Aggression5.7

Utility6.5

Positioning5.7

Opening Duels1.4

Clutch4.4

Strong 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: utility contribution, positioning profile.

Where you differ: 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 46% on CT to 26% on T — the same duels are being taken with worse setups on the attacking side.

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

Aim7.7

Positioning5.7

Utility6.5

Mechanics7.4

Opening Duels2.0

Win Impact10.0

Composite 6.7/10 (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 rating0.00−0.00

first ⅓ avg 0.01 → last ⅓ avg 0.00

Reaction time541ms−62ms

first ⅓ avg 603ms → last ⅓ avg 541ms

Headshot accuracy14.5%−1.6%

first ⅓ avg 16.0% → last ⅓ avg 14.5%

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

0.18Best rating — inferno 13–1

13–1Biggest win — cache

8Longest win streak

W4Current streak

9–6In matches decided by ≤2 rounds

6Overtime games

Map breakdown

mirageBest map · 78% over 18dust2Weakest map · 47% over 17

Map	Grade	Played	Record	Win rate	Avg rating
ancient	S	20	13–7	65%	0.01
mirage	S	18	14–4	78%	0.02
anubis	S	18	13–5	72%	-0.00
dust2	B	17	8–9	47%	0.00
inferno	B	17	8–9	47%	-0.01
cache	A	8	5–3	63%	0.04
overpass	—	2	2–0	100%	0.03

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (47% over 17). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

4,208Matches

50%Win rate

1.11Avg K/D

73.1ADR

36%Headshot %

Clutches & streaks

42%1v1 clutch win

23%1v2 clutch win

11Longest win streak

Recent Faceit resultsWLWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	152	60%	1.10	13.9
Anubis	130	58%	1.07	13.7
Inferno	100	50%	1.17	14.4
Dust2	87	51%	1.18	15.2
Mirage	76	47%	0.98	14.4
Nuke	51	73%	1.11	13.8
Overpass	31	48%	1.22	16.1
Train	11	45%	0.98	11.4

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.

14.0%Headshot accuracy

36.0%Accuracy (enemy spotted)

38.1%Spray accuracy

83.4%Counter-strafing

8.5°Preaim

546msReaction time

25.7%T opening success

45.6%CT opening success

0.51Enemies flashed / flash

9.6%Flash assists

9.95HE damage / grenade

9.91Flashes / 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.

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 14.0195% — below the 15% mark we flag
Aim Training →
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 25.6821% — below the 40% mark we flag

Spend your practice time on Dust 2

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

47% win rate across 17 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
ancient	13–9	-0.03	15%	23 Aug →
mirage	13–2	0.15	18%	23 Aug →
dust2	13–11	-0.03	30%	16 Aug →
ancient	13–10	-0.01	14%	12 Aug →
anubis	7–13	-0.07	22%	10 Aug →
anubis	13–4	0.02	16%	29 Jul →
ancient	13–3	0.09	12%	29 Jul →
mirage	13–11	-0.01	11%	29 Jul →
ancient	16–12	0.01	15%	29 Jul →
inferno	3–13	-0.09	10%	23 Jul →
ancient	13–6	0.01	17%	19 Jul →
inferno	13–9	0.01	13%	15 Jul →
inferno	13–10	0.00	10%	14 Jul →
dust2	13–4	0.01	9%	14 Jul →
ancient	9–13	-0.04	11%	12 Jul →
dust2	10–13	0.01	16%	12 Jul →
inferno	13–11	-0.05	8%	10 Jul →
cache	13–4	0.07	9%	10 Jul →
ancient	13–9	-0.05	11%	9 Jul →
anubis	13–11	0.07	17%	9 Jul →
ancient	13–9	-0.01	14%	9 Jul →
anubis	13–2	0.06	6%	9 Jul →
cache	13–8	-0.02	12%	9 Jul →
ancient	13–4	0.01	16%	8 Jul →
mirage	10–13	-0.03	17%	7 Jul →
anubis	13–7	-0.07	17%	6 Jul →
dust2	10–13	-0.04	15%	6 Jul →
dust2	13–6	-0.01	7%	5 Jul →
ancient	10–13	0.01	9%	26 Jun →
mirage	13–9	-0.00	19%	24 Jun →
ancient	13–11	0.05	16%	23 Jun →
mirage	13–2	0.07	33%	23 Jun →
anubis	13–2	0.02	13%	22 Jun →
ancient	9–13	0.05	20%	18 Jun →
mirage	13–9	-0.00	19%	18 Jun →
anubis	13–8	-0.02	8%	17 Jun →
mirage	13–8	0.03	21%	11 Jun →
anubis	13–9	0.04	12%	10 Jun →
inferno	8–13	-0.06	10%	10 Jun →
inferno	4–13	-0.04	22%	9 Jun →
mirage	13–10	0.06	11%	7 Jun →
mirage	13–6	0.03	20%	4 Jun →
anubis	11–13	0.01	14%	4 Jun →
dust2	9–13	-0.05	15%	4 Jun →
cache	13–1	0.14	6%	4 Jun →
cache	13–4	0.02	8%	4 Jun →
cache	10–13	0.01	18%	28 May →
inferno	3–13	-0.06	18%	27 May →
ancient	13–4	0.01	12%	26 May →
dust2	13–2	0.06	16%	25 May →
ancient	8–13	0.05	9%	22 May →
dust2	13–7	0.07	19%	22 May →
dust2	13–7	0.06	17%	22 May →
mirage	16–19	-0.04	23%	21 May →
inferno	7–13	-0.01	13%	20 May →
mirage	13–10	0.03	15%	20 May →
inferno	13–2	0.03	21%	18 May →
ancient	8–13	-0.03	11%	18 May →
dust2	8–13	0.01	7%	10 May →
anubis	13–6	-0.04	17%	7 May →
inferno	11–13	-0.01	16%	29 Apr →
cache	13–5	0.01	34%	29 Apr →
cache	12–12	0.08	13%	29 Apr →
dust2	1–13	-0.06	14%	29 Apr →
cache	2–13	-0.02	19%	29 Apr →
anubis	13–11	-0.04	10%	27 Apr →
mirage	13–6	0.01	6%	27 Apr →
anubis	13–5	0.03	20%	26 Apr →
ancient	13–5	0.01	12%	26 Apr →
ancient	16–14	0.01	10%	22 Apr →
mirage	13–16	0.04	19%	21 Apr →
anubis	5–13	-0.06	15%	20 Apr →
anubis	9–3	-0.02	11%	14 Apr →
mirage	13–6	0.01	30%	9 Apr →
dust2	17–19	-0.02	11%	8 Apr →
dust2	6–13	-0.01	13%	8 Apr →
anubis	13–6	0.06	12%	30 Mar →
dust2	6–13	-0.06	16%	26 Mar →
ancient	13–3	0.04	17%	24 Mar →
inferno	13–9	0.04	13%	19 Mar →
overpass	13–11	0.00	10%	19 Mar →
dust2	11–13	0.06	34%	19 Mar →
inferno	13–1	0.18	18%	18 Mar →
mirage	13–11	-0.05	9%	18 Mar →
inferno	7–13	-0.08	18%	15 Mar →
inferno	11–13	-0.03	13%	15 Mar →
inferno	8–13	-0.03	12%	5 Mar →
inferno	13–5	0.06	14%	4 Mar →
anubis	11–13	-0.00	11%	3 Mar →
ancient	3–13	-0.05	15%	3 Mar →
mirage	13–9	0.02	26%	2 Mar →
inferno	13–8	-0.05	18%	1 Mar →
overpass	7–2	0.06	11%	1 Mar →
mirage	9–13	-0.00	17%	28 Feb →
dust2	13–5	0.04	20%	26 Feb →
ancient	6–13	-0.01	17%	25 Feb →
mirage	13–10	0.04	25%	25 Feb →
anubis	10–13	-0.01	18%	24 Feb →
anubis	16–13	-0.01	9%	23 Feb →
dust2	13–7	0.01	15%	23 Feb →