panda- — CS2 Stats

US76561197960269673[U:1:3945]Steam profile ↗✓ No bans

3,916Tracked matches34%Win rate2020Tracked since

CSDB Rating4.6 DevelopingSupport

Premier CS Rating21,963Top 50% of 17,162 CSDB-tracked playersPink band · top ~6.3% of ranked players (population est.)

CSDB Leaderboard#7681 of 25029 tracked

FaceitLevel 7 · 1,534 ELOTop 42.3% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim56

Positioning42

Utility74

0–100 skill scores via Leetify.

Recent form

STEADY51–46–3Last 10051%Win rateWLLLWLWLLW

Last 10 vs previous 10: +20pp win rate · +0.04 avg rating

Player DNA

Primary style: Support — Utility contribution leads the profile while opening activity stays low.

Aim5.6

Aggression3.8

Utility7.4

Positioning4.2

Opening Duels1.1

Clutch4.2

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 83% playstyle similarity

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

Where you differ: lower positioning profile; 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. 675ms 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

Aim5.6

Positioning4.2

Utility7.4

Mechanics5.3

Opening Duels1.1

Win Impact0.0

Composite 4.6/10 (Developing), 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-0.01−0.01

first ⅓ avg 0.01 → last ⅓ avg -0.01

Reaction time685ms−1ms

first ⅓ avg 686ms → last ⅓ avg 685ms

Headshot accuracy17.0%−2.2%

first ⅓ avg 19.2% → last ⅓ avg 17.0%

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

0.16Best rating — anubis 13–3

13–0Biggest win — mirage

8Longest win streak

11–5In matches decided by ≤2 rounds

9Overtime games

Map breakdown

infernoBest map · 59% over 17nukeWeakest map · 44% over 9

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	21	11–10	52%	-0.00
ancient	B	17	8–9	47%	-0.00
inferno	A	17	10–7	59%	0.00
anubis	B	13	6–7	46%	-0.00
cache	B	12	6–6	50%	0.00
dust2	A	11	6–5	55%	0.02
nuke	C	9	4–5	44%	0.02

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (44% over 9). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

935Matches

49%Win rate

0.99Avg K/D

77.5ADR

42%Headshot %

Clutches & streaks

41%1v1 clutch win

23%1v2 clutch win

8Longest win streak

Recent Faceit resultsWLLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	182	43%	1.01	15.7
Ancient	113	46%	0.98	15.2
Inferno	112	53%	0.98	15.1
Anubis	77	51%	1.00	15.7
Dust2	49	41%	0.95	13.3
Nuke	43	58%	0.95	15.5
Cache	27	63%	0.98	15.0
Train	13	62%	1.16	17.2

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.

16.1%Headshot accuracy

40.8%Accuracy (enemy spotted)

43.9%Spray accuracy

74.1%Counter-strafing

14.0°Preaim

675msReaction time

35.7%T opening success

33.3%CT opening success

0.63Enemies flashed / flash

10.3%Flash assists

10.88HE damage / grenade

14.09Flashes / 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
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 13.9576° — above the 12° mark we flag
Aim Training →

Spend your practice time on Nuke

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

44% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
cache	13–10	-0.04	15%	29 Aug →
mirage	10–13	0.04	13%	28 Aug →
dust2	7–13	0.06	37%	26 Aug →
dust2	5–13	-0.04	17%	26 Aug →
anubis	13–9	0.03	20%	24 Aug →
nuke	8–13	0.00	12%	24 Aug →
anubis	13–10	-0.02	22%	24 Aug →
anubis	10–13	-0.05	13%	23 Aug →
cache	11–13	0.07	16%	23 Aug →
ancient	13–5	0.01	13%	22 Aug →
mirage	19–22	-0.01	16%	22 Aug →
cache	7–13	-0.05	21%	22 Aug →
ancient	4–13	-0.02	10%	22 Aug →
nuke	3–13	-0.02	18%	22 Aug →
inferno	1–13	-0.08	11%	22 Aug →
dust2	4–13	0.02	9%	22 Aug →
mirage	13–11	0.01	8%	21 Aug →
inferno	5–13	-0.06	12%	21 Aug →
mirage	13–7	0.01	17%	21 Aug →
inferno	0–13	-0.11	19%	21 Aug →
dust2	13–4	0.03	23%	20 Aug →
ancient	5–13	0.00	12%	20 Aug →
mirage	13–2	0.04	12%	20 Aug →
anubis	8–13	-0.05	18%	20 Aug →
dust2	4–13	-0.04	16%	19 Aug →
mirage	9–13	-0.05	17%	19 Aug →
inferno	13–5	0.05	11%	19 Aug →
dust2	13–8	0.04	21%	19 Aug →
dust2	12–12	0.07	24%	19 Aug →
anubis	13–16	-0.03	10%	8 Aug →
mirage	4–13	-0.04	50%	8 Aug →
inferno	13–11	-0.02	8%	8 Aug →
nuke	11–13	0.05	21%	7 Aug →
ancient	13–11	0.04	13%	7 Aug →
mirage	13–2	-0.03	14%	6 Aug →
cache	3–13	-0.01	16%	6 Aug →
ancient	15–15	-0.03	18%	5 Aug →
mirage	13–10	0.07	17%	4 Aug →
ancient	10–13	-0.02	17%	4 Aug →
ancient	9–13	-0.01	13%	3 Aug →
anubis	9–13	-0.06	19%	3 Aug →
inferno	13–11	0.12	24%	3 Aug →
nuke	9–13	-0.01	14%	2 Aug →
anubis	7–13	-0.07	20%	2 Aug →
mirage	13–8	0.00	14%	2 Aug →
ancient	7–13	-0.05	13%	2 Aug →
mirage	4–13	-0.05	18%	1 Aug →
inferno	13–10	0.06	15%	1 Aug →
cache	19–15	0.03	26%	1 Aug →
ancient	13–9	0.06	12%	1 Aug →
inferno	15–15	-0.02	15%	31 Jul →
inferno	3–13	-0.09	11%	30 Jul →
anubis	10–13	0.06	19%	29 Jul →
ancient	6–13	0.06	23%	29 Jul →
ancient	10–13	-0.07	21%	28 Jul →
nuke	13–16	0.01	24%	27 Jul →
mirage	13–8	0.04	19%	27 Jul →
dust2	13–10	-0.01	20%	27 Jul →
mirage	13–2	0.03	10%	27 Jul →
cache	13–11	0.05	16%	26 Jul →
mirage	13–11	0.03	17%	25 Jul →
cache	13–9	0.04	8%	25 Jul →
inferno	16–13	0.02	26%	25 Jul →
anubis	13–3	0.16	34%	25 Jul →
mirage	2–13	0.01	0%	24 Jul →
ancient	13–11	-0.00	14%	24 Jul →
cache	13–4	-0.04	21%	24 Jul →
anubis	13–11	-0.00	33%	23 Jul →
mirage	13–5	0.06	24%	22 Jul →
inferno	4–13	-0.04	19%	22 Jul →
anubis	8–13	0.01	23%	22 Jul →
mirage	6–13	-0.10	18%	22 Jul →
mirage	9–13	0.02	15%	22 Jul →
ancient	13–4	0.01	22%	21 Jul →
inferno	13–5	0.03	26%	21 Jul →
ancient	13–10	0.01	13%	21 Jul →
anubis	13–5	-0.04	13%	21 Jul →
ancient	13–11	-0.07	21%	20 Jul →
ancient	13–5	0.11	12%	19 Jul →
cache	13–11	0.03	18%	19 Jul →
inferno	13–8	-0.01	18%	19 Jul →
mirage	6–13	-0.05	17%	18 Jul →
inferno	13–8	-0.00	7%	18 Jul →
dust2	13–5	0.02	16%	18 Jul →
cache	14–16	0.06	22%	17 Jul →
cache	5–13	-0.08	24%	16 Jul →
mirage	13–0	0.01	33%	16 Jul →
dust2	13–7	0.05	21%	16 Jul →
mirage	1–13	-0.04	9%	16 Jul →
cache	11–13	-0.04	22%	16 Jul →
nuke	13–4	0.10	15%	15 Jul →
nuke	13–10	0.03	16%	15 Jul →
anubis	16–12	0.05	24%	15 Jul →
ancient	9–13	-0.07	5%	14 Jul →
nuke	13–8	0.08	22%	13 Jul →
inferno	13–11	0.09	13%	12 Jul →
dust2	13–5	-0.01	14%	12 Jul →
inferno	11–13	-0.00	27%	11 Jul →
inferno	13–4	0.10	14%	11 Jul →
nuke	13–4	-0.05	37%	10 Jul →