PanDDDa. — CS2 Stats

76561198118995799[U:1:158730071]✓ No bans

696Tracked matches55%Win rate2020Tracked since

CSDB Rating6.0 SolidHybrid Rifler

Premier CS Rating23,419Top 50% of 819 CSDB-tracked playersPink band · top ~4.7% of ranked players (population est.)

WingmanLegendary Eagle

Ladder ranks via Leetify

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Performance scores

Aim74

Positioning52

Utility54

0–100 skill scores via Leetify.

Recent form

STEADY45–52–3Last 10045%Win rateLLWLWWTWLW

Last 10 vs previous 10: -20pp win rate · +0.06 avg rating

Player DNA

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

Aim7.4

Aggression5.8

Utility5.4

Positioning5.2

Opening Duels2.0

Clutch5.2

Effective flashes

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 90% playstyle similarity

Most alike: opening-duel success, utility contribution.

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

Reaction time. 570ms 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

Aim7.4

Positioning5.2

Utility5.4

Mechanics6.6

Opening Duels2.0

Win Impact6.7

Composite 6.0/10 (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-0.01−0.02

first ⅓ avg 0.01 → last ⅓ avg -0.01

Reaction time580ms−2ms

first ⅓ avg 582ms → last ⅓ avg 580ms

Headshot accuracy13.7%−2.9%

first ⅓ avg 16.6% → last ⅓ avg 13.7%

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

0.16Best rating — dust2 13–5

13–0Biggest win — inferno

4Longest win streak

L2Current streak

6–7In matches decided by ≤2 rounds

7Overtime games

Map breakdown

anubisBest map · 60% over 5ancientWeakest map · 33% over 9

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	33	12–21	36%	0.01
inferno	B	21	10–11	48%	0.02
mirage	A	19	11–8	58%	0.02
ancient	D	9	3–6	33%	-0.02
cache	B	6	3–3	50%	0.01
anubis	A	5	3–2	60%	-0.03
nuke	—	4	3–1	75%	0.05
office	—	2	0–2	0%	-0.03
train	—	1	0–1	0%	0.01

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

216Matches

56%Win rate

1.25Avg K/D

90.9ADR

35%Headshot %

Clutches & streaks

46%1v1 clutch win

26%1v2 clutch win

7Longest win streak

Recent Faceit resultsWLWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	52	60%	1.35	18.7
Mirage	34	53%	1.37	19.7
Ancient	17	47%	1.20	16.6
Inferno	10	50%	1.22	19.5
Nuke	9	67%	1.30	24.4
Train	8	62%	1.22	21.8
Anubis	4	75%	1.22	19.3
Overpass	4	50%	1.04	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.

13.9%Headshot accuracy

36.8%Accuracy (enemy spotted)

40.3%Spray accuracy

79.5%Counter-strafing

8.8°Preaim

570msReaction time

32.9%T opening success

43.3%CT opening success

0.74Enemies flashed / flash

2.6%Flash assists

17.50HE damage / grenade

5.73Flashes / 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 13.9172% — 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 32.8874% — below the 40% mark we flag

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 9 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
ancient	9–13	-0.04	13%	27 Aug →
dust2	3–13	-0.00	7%	27 Aug →
ancient	13–11	-0.01	6%	26 Aug →
dust2	11–13	-0.01	20%	25 Aug →
nuke	13–5	0.08	12%	19 Aug →
inferno	13–3	0.11	26%	19 Aug →
mirage	15–15	0.03	12%	6 Aug →
inferno	13–2	0.11	15%	5 Aug →
cache	6–13	0.04	18%	4 Aug →
mirage	13–9	-0.02	22%	4 Aug →
inferno	13–8	-0.03	18%	4 Aug →
mirage	13–8	0.05	26%	2 Aug →
dust2	11–13	-0.01	9%	2 Aug →
mirage	13–5	-0.03	17%	2 Aug →
dust2	13–8	-0.06	17%	2 Aug →
mirage	1–13	-0.09	0%	2 Aug →
mirage	13–11	-0.07	16%	29 Jul →
anubis	13–5	0.01	7%	29 Jul →
dust2	13–5	0.01	10%	29 Jul →
anubis	10–13	-0.06	11%	23 Jul →
ancient	11–13	-0.04	13%	23 Jul →
mirage	13–4	0.01	17%	23 Jul →
dust2	16–13	-0.01	13%	19 Jul →
ancient	5–13	-0.08	12%	19 Jul →
inferno	6–13	0.02	27%	19 Jul →
nuke	1–9	-0.01	13%	19 Jul →
inferno	13–2	0.04	0%	14 Jul →
ancient	10–13	-0.01	9%	14 Jul →
mirage	13–6	-0.04	4%	14 Jul →
inferno	3–13	-0.04	21%	12 Jul →
ancient	7–13	-0.03	12%	12 Jul →
inferno	9–13	0.02	14%	12 Jul →
dust2	1–9	-0.04	13%	12 Jul →
mirage	6–13	-0.06	0%	12 Jul →
cache	9–13	-0.01	8%	12 Jul →
nuke	13–1	0.09	4%	12 Jul →
dust2	4–4	-0.05	6%	12 Jul →
mirage	13–5	0.06	33%	11 Jul →
dust2	13–10	0.04	20%	11 Jul →
inferno	2–13	-0.04	8%	11 Jul →
nuke	13–10	0.04	10%	10 Jul →
cache	13–11	-0.02	13%	8 Jul →
mirage	7–13	0.11	15%	8 Jul →
office	11–13	-0.04	21%	8 Jul →
inferno	13–7	-0.01	27%	6 Jul →
inferno	13–4	0.09	13%	4 Jul →
dust2	13–9	0.01	29%	4 Jul →
dust2	7–13	-0.04	17%	4 Jul →
anubis	13–9	0.07	19%	4 Jul →
mirage	13–8	0.10	11%	4 Jul →
inferno	10–13	0.07	8%	4 Jul →
dust2	7–13	-0.03	8%	4 Jul →
inferno	10–13	-0.02	14%	2 Jul →
dust2	13–5	0.16	7%	2 Jul →
inferno	13–0	0.10	15%	2 Jul →
mirage	13–16	0.02	15%	2 Jul →
inferno	13–1	0.13	12%	1 Jul →
cache	13–4	0.03	33%	1 Jul →
mirage	9–13	0.06	11%	30 Jun →
dust2	13–16	0.01	7%	30 Jun →
inferno	13–8	0.02	11%	28 Jun →
dust2	9–13	-0.05	10%	20 Jun →
dust2	13–6	0.05	26%	20 Jun →
dust2	15–15	-0.02	20%	20 Jun →
inferno	3–13	-0.07	6%	8 Jun →
mirage	10–13	0.06	21%	8 Jun →
ancient	10–13	0.02	11%	8 Jun →
dust2	13–9	0.01	18%	8 Jun →
ancient	13–9	0.08	20%	6 Jun →
mirage	16–13	0.10	13%	6 Jun →
dust2	13–4	0.08	10%	6 Jun →
dust2	6–13	0.01	12%	6 Jun →
dust2	8–13	-0.05	14%	3 Jun →
ancient	13–7	-0.03	12%	3 Jun →
inferno	11–13	0.01	11%	1 Jun →
dust2	13–2	0.06	24%	31 May →
anubis	1–13	-0.10	14%	29 May →
dust2	13–2	0.12	19%	29 May →
dust2	5–13	-0.02	16%	28 May →
dust2	14–16	0.01	5%	28 May →
dust2	13–6	0.04	20%	28 May →
dust2	12–12	0.03	14%	27 May →
inferno	9–13	0.05	28%	27 May →
dust2	6–13	0.08	9%	26 May →
dust2	6–13	0.03	22%	26 May →
inferno	1–13	-0.09	17%	26 May →
mirage	10–13	-0.01	23%	24 May →
inferno	8–13	-0.05	9%	20 May →
inferno	13–11	-0.00	9%	19 May →
dust2	10–13	-0.01	25%	18 May →
mirage	13–9	0.08	18%	17 May →
mirage	13–11	0.04	26%	16 May →
dust2	8–13	-0.01	20%	16 May →
cache	13–10	0.12	23%	14 May →
office	5–13	-0.02	27%	14 May →
train	9–13	0.01	19%	13 May →
cache	1–13	-0.08	8%	13 May →
dust2	3–13	-0.05	20%	10 May →
anubis	13–11	-0.04	11%	8 May →
dust2	10–13	0.05	14%	8 May →