s0mplex — CS2 Stats

76561198124183500[U:1:163917772]

3,019Tracked matches53%Win rate2020Tracked since

CSDB Rating6.2 SolidAggressive Rifler

FaceitLevel 9 · 2,233 ELOTop 20.7% of ranked FACEIT players

WingmanGold Nova Master

Ladder ranks via Leetify

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Performance scores

Aim78

Positioning57

Utility53

0–100 skill scores via Leetify.

Recent form

HOT52–48Last 10052%Win rateWWWLWWWLWL

Last 10 vs previous 10: +20pp win rate · -0.03 avg rating

Player DNA

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

Aim7.8

Aggression6.7

Utility5.3

Positioning5.7

Opening Duels2.7

Clutch4.2

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 91% playstyle similarity

Most alike: opening-duel success, 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 56% on CT to 26% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 555ms 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

Aim7.8

Positioning5.7

Utility5.3

Mechanics6.7

Opening Duels3.2

Win Impact6.1

Composite 6.2/10 (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 rating0.01−0.01

first ⅓ avg 0.02 → last ⅓ avg 0.01

Reaction time567ms−15ms

first ⅓ avg 582ms → last ⅓ avg 567ms

Headshot accuracy23.7%+3.2%

first ⅓ avg 20.5% → last ⅓ avg 23.7%

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

0.17Best rating — ancient 13–5

11–0Biggest win — inferno

5Longest win streak

W3Current streak

10–9In matches decided by ≤2 rounds

12Overtime games

Map breakdown

cacheBest map · 64% over 14anubisWeakest map · 40% over 5

Map	Grade	Played	Record	Win rate	Avg rating
inferno	A	25	15–10	60%	0.01
ancient	C	23	10–13	43%	0.01
nuke	C	19	8–11	42%	0.01
cache	A	14	9–5	64%	0.01
vertigo	C	7	3–4	43%	-0.01
anubis	C	5	2–3	40%	0.01
mirage	—	4	4–0	100%	0.02
overpass	—	3	1–2	33%	0.00

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

4,360Matches

50%Win rate

1.11Avg K/D

86.2ADR

53%Headshot %

Clutches & streaks

41%1v1 clutch win

24%1v2 clutch win

12Longest win streak

Recent Faceit resultsWLWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	539	48%	1.12	17.7
Inferno	457	51%	1.13	17.6
Anubis	337	52%	1.19	18.3
Mirage	303	53%	1.08	16.4
Nuke	261	49%	1.10	18.2
Dust2	154	40%	1.05	16.7
Overpass	154	44%	1.12	18.3
Train	144	50%	1.16	18.3

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.

24.3%Headshot accuracy

35.3%Accuracy (enemy spotted)

34.2%Spray accuracy

80.3%Counter-strafing

9.9°Preaim

555msReaction time

26.3%T opening success

55.7%CT opening success

0.55Enemies flashed / flash

13.6%Flash assists

9.45HE damage / grenade

5.59Flashes / 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 26.2506% — 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
inferno	13–10	-0.01	30%	29 Aug →
mirage	13–10	0.06	29%	29 Aug →
vertigo	13–8	-0.03	20%	29 Aug →
ancient	7–13	-0.02	26%	29 Aug →
ancient	13–8	-0.01	20%	29 Aug →
inferno	13–3	-0.03	21%	29 Aug →
cache	13–4	0.05	30%	29 Aug →
nuke	3–13	-0.06	26%	28 Aug →
ancient	13–11	-0.02	18%	28 Aug →
inferno	11–13	0.03	29%	28 Aug →
vertigo	6–13	-0.01	29%	27 Aug →
nuke	9–13	-0.01	28%	27 Aug →
ancient	13–5	0.17	21%	27 Aug →
nuke	11–13	0.06	19%	27 Aug →
cache	13–6	0.03	19%	27 Aug →
cache	13–7	0.04	49%	27 Aug →
ancient	9–13	-0.01	26%	27 Aug →
ancient	9–13	-0.08	30%	22 Aug →
vertigo	16–13	0.03	24%	21 Aug →
inferno	13–11	0.02	26%	21 Aug →
vertigo	6–13	0.01	23%	21 Aug →
cache	6–13	-0.02	15%	21 Aug →
nuke	13–16	-0.00	14%	21 Aug →
vertigo	9–13	-0.04	23%	19 Aug →
inferno	7–13	0.05	14%	16 Aug →
cache	13–8	-0.01	34%	15 Aug →
mirage	13–5	-0.01	16%	15 Aug →
mirage	13–3	-0.00	20%	15 Aug →
inferno	13–5	0.10	26%	15 Aug →
inferno	6–13	0.05	27%	15 Aug →
nuke	13–11	-0.01	7%	13 Aug →
ancient	13–11	0.05	13%	9 Aug →
inferno	13–4	0.02	30%	8 Aug →
inferno	13–7	0.01	34%	8 Aug →
vertigo	13–11	-0.04	22%	8 Aug →
vertigo	10–13	0.05	37%	7 Aug →
ancient	4–13	-0.06	11%	7 Aug →
inferno	13–16	-0.04	24%	7 Aug →
inferno	4–13	-0.05	40%	1 Aug →
cache	13–16	-0.02	22%	1 Aug →
cache	4–13	-0.04	8%	31 Jul →
ancient	13–3	0.04	13%	31 Jul →
anubis	11–13	0.03	9%	31 Jul →
inferno	16–12	-0.01	19%	31 Jul →
nuke	13–4	-0.00	14%	31 Jul →
anubis	18–22	-0.03	18%	26 Jul →
inferno	13–10	-0.03	17%	26 Jul →
ancient	3–13	-0.09	17%	26 Jul →
cache	13–11	0.00	19%	25 Jul →
nuke	13–9	0.01	16%	25 Jul →
cache	13–7	0.03	39%	25 Jul →
inferno	13–11	-0.02	30%	25 Jul →
inferno	4–13	-0.05	22%	25 Jul →
anubis	13–6	-0.00	16%	25 Jul →
inferno	13–8	0.05	32%	24 Jul →
ancient	4–13	-0.03	35%	23 Jul →
inferno	11–0	0.06	31%	23 Jul →
inferno	19–22	0.01	16%	23 Jul →
ancient	13–9	0.05	18%	23 Jul →
nuke	9–13	0.04	21%	22 Jul →
cache	13–8	0.01	18%	20 Jul →
ancient	13–8	0.03	26%	20 Jul →
inferno	11–13	-0.02	15%	19 Jul →
ancient	13–4	0.12	27%	19 Jul →
nuke	5–13	-0.02	21%	19 Jul →
ancient	13–11	-0.03	15%	19 Jul →
inferno	13–6	-0.03	27%	19 Jul →
anubis	7–13	0.04	14%	19 Jul →
nuke	13–16	0.03	23%	14 Jul →
inferno	13–11	0.03	14%	28 Jun →
ancient	8–13	0.02	19%	28 Jun →
mirage	13–7	0.01	31%	28 Jun →
cache	7–13	0.02	27%	27 Jun →
inferno	13–4	0.15	25%	27 Jun →
nuke	11–13	0.01	24%	27 Jun →
anubis	13–4	0.03	10%	27 Jun →
nuke	13–10	-0.01	16%	27 Jun →
overpass	13–10	-0.01	27%	27 Jun →
cache	13–5	0.02	22%	27 Jun →
inferno	11–13	-0.04	22%	26 Jun →
ancient	9–13	-0.02	17%	26 Jun →
nuke	13–11	0.02	36%	26 Jun →
nuke	13–10	0.05	13%	26 Jun →
nuke	3–13	0.01	16%	26 Jun →
inferno	13–8	0.03	19%	26 Jun →
ancient	17–19	0.05	32%	25 Jun →
cache	19–15	0.09	18%	25 Jun →
ancient	8–13	0.05	17%	25 Jun →
ancient	11–13	-0.01	14%	18 Jun →
overpass	4–13	-0.01	22%	18 Jun →
cache	10–13	-0.06	17%	18 Jun →
ancient	9–13	-0.02	14%	18 Jun →
ancient	13–6	0.02	22%	18 Jun →
nuke	13–6	0.05	21%	17 Jun →
ancient	10–13	0.05	25%	17 Jun →
nuke	12–16	-0.02	17%	17 Jun →
nuke	13–5	0.01	19%	16 Jun →
overpass	14–16	0.03	24%	10 Jun →
inferno	9–13	0.01	10%	9 Jun →
nuke	8–13	0.00	31%	9 Jun →