c0mplex — CS2 Stats

76561198851268520[U:1:891002792]✓ No bans

1,039Tracked matches63%Win rate2020Tracked since

CSDB Rating7.7 StrongAggressive Rifler

Premier CS Rating24,562Top 50% of 819 CSDB-tracked playersPink band · top ~3.5% of ranked players (population est.)

CSDB Leaderboard#3080 of 16867 tracked

FaceitLevel 8 · 1,640 ELOTop 31.2% of ranked FACEIT players

WingmanGold Nova Master

Ladder ranks via Leetify

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Performance scores

Aim79

Positioning66

Utility73

0–100 skill scores via Leetify.

Recent form

STEADY53–45–2Last 10053%Win rateWWLLLWLWWW

Last 10 vs previous 10: +0pp win rate · +0.01 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim7.9

Aggression9.7

Utility7.3

Positioning6.6

Opening Duels5.5

Clutch9.4

Excellent counter-strafingStrong CT-side openerReliable in 1v1s

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 ZywOo 92% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

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

Strengths

CT openings. 64% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

T-side openings. Opening success drops from 64% on CT to 39% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 659ms 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

Aim7.9

Positioning6.6

Utility7.3

Mechanics8.5

Opening Duels5.5

Win Impact9.4

Composite 7.7/10 (Strong), 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 rating0.02+0.01

first ⅓ avg 0.00 → last ⅓ avg 0.02

Reaction time660ms+1ms

first ⅓ avg 659ms → last ⅓ avg 660ms

Headshot accuracy27.0%+1.7%

first ⅓ avg 25.3% → last ⅓ avg 27.0%

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

0.12Best rating — inferno 13–5

13–1Biggest win — cache

7Longest win streak

W2Current streak

7–9In matches decided by ≤2 rounds

11Overtime games

Map breakdown

nukeBest map · 69% over 16infernoWeakest map · 33% over 15

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	23	11–12	48%	0.00
dust2	A	22	13–9	59%	-0.00
nuke	S	16	11–5	69%	0.03
inferno	D	15	5–10	33%	0.01
ancient	A	14	9–5	64%	0.04
cache	—	4	2–2	50%	-0.03
overpass	—	4	1–3	25%	0.01
anubis	—	2	1–1	50%	-0.02

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 15). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

256Matches

54%Win rate

1.13Avg K/D

83.5ADR

51%Headshot %

Clutches & streaks

67%1v1 clutch win

0%1v2 clutch win

9Longest win streak

Recent Faceit resultsWWLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	4	75%	1.85	18.8
Mirage	4	50%	1.24	15.8
Nuke	3	33%	1.19	15.3
Anubis	3	33%	0.68	10.7
Ancient	2	100%	1.20	24.5
Cache	1	0%	0.47	8.0

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.

26.6%Headshot accuracy

35.0%Accuracy (enemy spotted)

38.4%Spray accuracy

88.4%Counter-strafing

10.3°Preaim

659msReaction time

39.4%T opening success

64.3%CT opening success

0.67Enemies flashed / flash

8.1%Flash assists

14.09HE damage / grenade

14.70Flashes / 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 39.4334% — 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.

33% win rate across 15 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
mirage	13–7	0.04	38%	26 Aug →
dust2	13–10	-0.01	17%	26 Aug →
dust2	9–13	-0.00	34%	22 Aug →
inferno	9–13	-0.02	16%	22 Aug →
mirage	6–13	0.01	31%	22 Aug →
ancient	13–3	0.04	16%	22 Aug →
mirage	9–13	-0.05	24%	21 Aug →
nuke	13–9	0.01	17%	21 Aug →
ancient	13–9	0.06	18%	21 Aug →
mirage	13–10	0.05	25%	21 Aug →
mirage	13–9	0.03	39%	17 Aug →
cache	13–1	0.02	32%	27 Jul →
dust2	13–11	-0.01	24%	17 Jul →
mirage	13–6	0.09	18%	17 Jul →
ancient	8–13	0.01	30%	17 Jul →
dust2	13–8	0.00	29%	17 Jul →
inferno	11–13	-0.03	29%	16 Jul →
mirage	14–16	-0.04	24%	16 Jul →
cache	16–12	0.03	29%	15 Jul →
dust2	8–13	-0.04	28%	15 Jul →
mirage	10–13	0.07	26%	15 Jul →
nuke	13–8	0.07	32%	14 Jul →
dust2	13–4	0.02	39%	14 Jul →
nuke	13–6	0.02	37%	14 Jul →
dust2	16–12	0.00	25%	14 Jul →
ancient	13–8	0.04	15%	14 Jul →
mirage	13–6	0.10	30%	13 Jul →
ancient	9–13	0.03	22%	13 Jul →
cache	9–13	-0.08	31%	13 Jul →
mirage	16–13	-0.02	28%	12 Jul →
inferno	0–5	-0.02	33%	12 Jul →
dust2	13–11	0.06	35%	12 Jul →
ancient	15–15	0.03	20%	12 Jul →
nuke	11–13	0.05	41%	10 Jul →
nuke	13–3	0.04	17%	10 Jul →
mirage	12–16	-0.01	28%	9 Jul →
cache	6–13	-0.07	32%	9 Jul →
ancient	13–5	0.11	19%	9 Jul →
inferno	15–15	-0.02	21%	9 Jul →
dust2	6–13	0.02	26%	4 Jul →
mirage	8–13	-0.04	19%	4 Jul →
mirage	9–13	0.01	22%	4 Jul →
ancient	13–7	0.10	15%	4 Jul →
dust2	6–13	-0.01	26%	4 Jul →
nuke	16–14	0.06	25%	3 Jul →
inferno	2–13	-0.01	14%	3 Jul →
ancient	13–5	0.09	28%	3 Jul →
nuke	13–5	0.07	35%	3 Jul →
overpass	13–11	0.06	29%	3 Jul →
dust2	7–13	-0.06	20%	3 Jul →
nuke	11–13	0.07	29%	3 Jul →
mirage	13–10	-0.03	17%	2 Jul →
nuke	13–7	0.01	23%	2 Jul →
ancient	4–13	-0.00	28%	2 Jul →
ancient	13–8	0.01	49%	1 Jul →
nuke	13–2	0.10	36%	30 Jun →
overpass	3–13	0.02	35%	30 Jun →
dust2	13–8	-0.00	30%	30 Jun →
inferno	11–13	-0.02	27%	30 Jun →
dust2	11–13	-0.04	10%	30 Jun →
dust2	16–13	0.01	19%	28 Jun →
mirage	13–16	-0.01	26%	28 Jun →
dust2	13–10	0.08	38%	27 Jun →
mirage	6–13	-0.06	24%	27 Jun →
inferno	14–16	-0.02	33%	27 Jun →
mirage	13–3	-0.03	22%	27 Jun →
inferno	13–6	0.01	27%	26 Jun →
mirage	13–3	0.03	34%	26 Jun →
mirage	9–13	-0.05	23%	26 Jun →
nuke	6–13	-0.04	19%	25 Jun →
overpass	10–13	0.03	28%	25 Jun →
dust2	10–13	-0.05	24%	24 Jun →
dust2	13–10	0.03	30%	24 Jun →
mirage	13–10	-0.01	26%	24 Jun →
dust2	13–7	0.04	25%	24 Jun →
nuke	13–10	-0.01	20%	22 Jun →
nuke	13–6	0.05	24%	21 Jun →
anubis	7–13	-0.04	43%	9 Jun →
mirage	7–13	-0.01	37%	4 Jun →
inferno	10–13	-0.03	28%	4 Jun →
mirage	13–5	0.03	33%	4 Jun →
dust2	0–13	-0.12	0%	4 Jun →
inferno	9–13	0.02	24%	29 May →
dust2	13–9	0.00	16%	29 May →
ancient	11–13	0.08	23%	29 May →
nuke	13–11	0.02	24%	26 May →
dust2	8–13	-0.05	19%	26 May →
inferno	13–5	0.06	33%	26 May →
nuke	10–13	-0.04	22%	26 May →
overpass	11–13	-0.05	28%	26 May →
ancient	13–6	0.00	11%	26 May →
nuke	2–13	-0.08	30%	26 May →
mirage	4–13	-0.02	48%	25 May →
ancient	13–8	-0.02	21%	25 May →
inferno	13–11	-0.01	21%	25 May →
anubis	13–4	0.00	28%	25 May →
dust2	13–9	0.02	26%	25 May →
inferno	13–5	0.12	18%	24 May →
inferno	13–11	0.10	31%	24 May →
inferno	5–13	0.01	15%	15 May →