smegmaez — CS2 Stats

76561198010876651[U:1:50610923]

5,003Tracked matches43%Win rate2020Tracked since

CSDB Rating5.2 DevelopingHybrid Rifler

FaceitLevel 9 · 1,809 ELOTop 20.7% of ranked FACEIT players

WingmanGold Nova I

Ladder ranks via Leetify

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Performance scores

Aim72

Positioning51

Utility56

0–100 skill scores via Leetify.

Recent form

STEADY49–51Last 10049%Win rateLLWWWLLWLL

Last 10 vs previous 10: +0pp win rate · +0.02 avg rating

Player DNA

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

Aim7.2

Aggression5.9

Utility5.6

Positioning5.1

Opening Duels2.6

Clutch3.2

Strong CT-side openerEffective 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 Twistzz 90% playstyle similarity

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

Where you differ: lower utility contribution; 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

Flashes. 0.77 enemies blinded per flash — utility that consistently lands.

Areas to improve

T-side openings. Opening success drops from 50% on CT to 30% 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

Aim7.2

Positioning5.1

Utility5.6

Mechanics6.3

Opening Duels2.6

Win Impact2.8

Composite 5.2/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.01

first ⅓ avg -0.00 → last ⅓ avg -0.01

Reaction time540ms−16ms

first ⅓ avg 556ms → last ⅓ avg 540ms

Headshot accuracy21.1%+2.5%

first ⅓ avg 18.6% → last ⅓ avg 21.1%

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

0.19Best rating — ancient 13–0

13–0Biggest win — ancient

6Longest win streak

L2Current streak

8–8In matches decided by ≤2 rounds

14Overtime games

Map breakdown

nukeBest map · 87% over 15infernoWeakest map · 17% over 6

Map	Grade	Played	Record	Win rate	Avg rating
ancient	B	30	14–16	47%	-0.01
dust2	A	25	14–11	56%	0.00
nuke	S	15	13–2	87%	0.02
cache	D	12	3–9	25%	-0.02
anubis	C	11	4–7	36%	-0.02
inferno	D	6	1–5	17%	-0.02
vertigo	—	1	0–1	0%	-0.06

Across the last 100 tracked matches.

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

Faceit stats

Combat

4,795Matches

50%Win rate

0.98Avg K/D

73.1ADR

42%Headshot %

Clutches & streaks

36%1v1 clutch win

16%1v2 clutch win

11Longest win streak

Recent Faceit resultsWWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	586	47%	1.00	15.0
Dust2	483	49%	0.92	14.5
Anubis	411	47%	0.98	15.8
Nuke	357	59%	1.05	15.3
Inferno	274	49%	0.93	14.6
Vertigo	95	42%	0.95	14.6
Train	86	38%	1.00	15.4
Mirage	75	40%	0.87	13.1

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.

20.1%Headshot accuracy

34.7%Accuracy (enemy spotted)

38.8%Spray accuracy

78.4%Counter-strafing

11.9°Preaim

526msReaction time

30.5%T opening success

50.0%CT opening success

0.77Enemies flashed / flash

11.0%Flash assists

7.93HE damage / grenade

5.66Flashes / 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 30.4828% — 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.

17% win rate across 6 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
anubis	11–13	-0.04	19%	28 Aug →
nuke	10–13	-0.02	21%	28 Aug →
ancient	13–0	0.19	36%	28 Aug →
anubis	13–11	-0.05	20%	27 Aug →
ancient	13–5	0.02	26%	26 Aug →
dust2	9–13	-0.02	16%	26 Aug →
anubis	13–16	-0.04	18%	23 Aug →
inferno	16–14	-0.02	21%	22 Aug →
dust2	11–13	-0.02	26%	21 Aug →
anubis	7–13	0.01	20%	21 Aug →
inferno	13–16	-0.02	25%	20 Aug →
dust2	13–8	0.01	19%	20 Aug →
ancient	8–13	-0.02	22%	20 Aug →
inferno	13–16	-0.02	22%	18 Aug →
cache	4–13	-0.05	15%	18 Aug →
dust2	13–9	-0.01	22%	17 Aug →
ancient	3–13	-0.12	33%	17 Aug →
nuke	13–7	-0.01	29%	15 Aug →
anubis	2–13	-0.05	30%	15 Aug →
dust2	13–5	0.07	21%	14 Aug →
ancient	13–8	0.06	20%	14 Aug →
cache	10–13	-0.01	22%	11 Aug →
nuke	13–10	-0.03	11%	10 Aug →
anubis	6–13	-0.01	22%	10 Aug →
dust2	10–13	0.04	20%	9 Aug →
vertigo	4–13	-0.06	10%	8 Aug →
dust2	13–11	0.04	16%	8 Aug →
ancient	2–13	-0.10	14%	8 Aug →
ancient	25–23	-0.07	8%	7 Aug →
dust2	13–1	0.03	24%	7 Aug →
nuke	13–3	-0.03	18%	7 Aug →
cache	3–13	-0.04	21%	7 Aug →
ancient	13–10	-0.04	30%	7 Aug →
ancient	10–13	0.06	19%	6 Aug →
dust2	16–13	-0.02	21%	6 Aug →
ancient	10–13	-0.06	22%	6 Aug →
nuke	13–4	0.13	33%	5 Aug →
ancient	5–13	-0.01	17%	5 Aug →
cache	9–13	-0.03	32%	4 Aug →
dust2	4–13	-0.02	30%	4 Aug →
dust2	9–13	-0.02	18%	30 Jul →
ancient	9–13	-0.03	14%	30 Jul →
nuke	5–13	-0.03	14%	30 Jul →
ancient	18–22	-0.01	12%	29 Jul →
dust2	3–13	-0.02	24%	29 Jul →
ancient	13–11	0.02	18%	29 Jul →
cache	5–13	-0.04	14%	28 Jul →
ancient	6–13	-0.08	5%	28 Jul →
anubis	13–5	-0.00	13%	27 Jul →
cache	13–6	0.02	12%	27 Jul →
dust2	13–8	0.04	20%	27 Jul →
ancient	11–13	-0.03	15%	27 Jul →
inferno	11–13	-0.02	16%	26 Jul →
ancient	11–13	-0.04	20%	25 Jul →
nuke	13–7	-0.02	4%	24 Jul →
cache	13–3	0.04	21%	24 Jul →
nuke	13–10	0.00	16%	24 Jul →
ancient	13–9	0.03	23%	23 Jul →
dust2	16–19	-0.01	23%	23 Jul →
ancient	13–8	0.02	20%	23 Jul →
ancient	17–19	0.07	20%	21 Jul →
dust2	13–4	0.06	21%	20 Jul →
ancient	9–13	-0.07	11%	20 Jul →
cache	19–15	-0.01	18%	19 Jul →
dust2	13–6	0.03	18%	19 Jul →
nuke	13–6	0.09	30%	19 Jul →
inferno	8–13	-0.03	16%	18 Jul →
ancient	13–4	-0.02	8%	18 Jul →
dust2	6–13	-0.04	41%	18 Jul →
ancient	16–13	-0.06	14%	18 Jul →
inferno	13–16	-0.01	20%	17 Jul →
cache	14–16	-0.02	20%	17 Jul →
anubis	4–13	-0.03	21%	17 Jul →
nuke	13–3	-0.01	20%	17 Jul →
anubis	13–3	0.00	18%	14 Jul →
nuke	13–8	0.01	27%	13 Jul →
ancient	13–8	0.01	18%	12 Jul →
dust2	16–14	-0.04	13%	12 Jul →
dust2	13–10	-0.01	21%	11 Jul →
ancient	9–13	-0.01	21%	11 Jul →
ancient	13–10	-0.04	14%	11 Jul →
dust2	13–6	-0.01	15%	11 Jul →
ancient	13–6	0.00	22%	10 Jul →
dust2	9–13	-0.04	24%	10 Jul →
anubis	13–9	0.00	25%	10 Jul →
ancient	13–10	0.09	20%	10 Jul →
cache	3–13	-0.10	17%	10 Jul →
nuke	13–7	0.05	15%	9 Jul →
dust2	5–13	0.03	8%	9 Jul →
nuke	13–3	0.03	17%	9 Jul →
dust2	13–7	0.00	11%	9 Jul →
nuke	13–0	0.17	17%	9 Jul →
ancient	9–13	-0.02	25%	8 Jul →
cache	5–13	-0.01	14%	8 Jul →
dust2	11–13	0.00	17%	7 Jul →
ancient	5–13	-0.06	14%	7 Jul →
anubis	9–13	-0.04	23%	6 Jul →
dust2	13–11	0.02	17%	6 Jul →
nuke	13–11	0.02	20%	6 Jul →
cache	7–13	-0.01	16%	6 Jul →