efdeey — CS2 Stats

76561198142057079[U:1:181791351]

1,594Tracked matches61%Win rate2020Tracked since

2,694Hours in CS0Hrs last 2 wks

CSDB Rating6.7 SolidAggressive Rifler

FaceitLevel 6Top 54.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim80

Positioning60

Utility63

0–100 skill scores via Leetify.

Recent form

COLD54–39–7Last 10054%Win rateWWLWLLLLLT

Last 10 vs previous 10: -30pp win rate · -0.04 avg rating

Player DNA

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

Aim8.0

Aggression8.1

Utility6.3

Positioning6.0

Opening Duels2.6

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 b1t 93% playstyle similarity

Most alike: opening-fight frequency, 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. 582ms 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

Aim8.0

Positioning6.0

Utility6.3

Mechanics7.2

Opening Duels2.6

Win Impact8.6

Composite 6.7/10 (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 rating0.02−0.02

first ⅓ avg 0.05 → last ⅓ avg 0.02

Reaction time582ms−49ms

first ⅓ avg 631ms → last ⅓ avg 582ms

Headshot accuracy22.0%+5.1%

first ⅓ avg 16.9% → last ⅓ avg 22.0%

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

0.20Best rating — office 13–2

13–0Biggest win — office

9Longest win streak

W2Current streak

12–7In matches decided by ≤2 rounds

7Overtime games

Map breakdown

officeBest map · 71% over 7infernoWeakest map · 44% over 9

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	27	14–13	52%	0.04
nuke	B	11	5–6	45%	0.05
overpass	A	11	7–4	64%	0.05
inferno	C	9	4–5	44%	0.04
cache	A	9	5–4	56%	0.02
mirage	A	8	5–3	63%	0.05
ancient	A	7	4–3	57%	0.02
office	S	7	5–2	71%	0.09
train	—	4	2–2	50%	0.01
anubis	—	3	1–2	33%	0.01
italy	—	2	2–0	100%	0.05
vertigo	—	1	0–1	0%	-0.02
agency	—	1	0–1	0%	0.03

Across the last 100 tracked matches.

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

Lifetime stats

91,584Lifetime kills

1.25K/D · Top 25% of tracked players

4,364Matches

43.4%Match win rate

41.8%Headshot %

18.2%Shot accuracy · Top 10% of tracked players

9,109MVPs

1,560Hours (in match)

3,855Bombs planted

1,102Bombs defused

Most-used weapons

AK-4726,653

M4A4 / M4A1-S14,768

AWP8,433

Desert Eagle6,862

P2000 / USP-S5,803

Glock-183,332

SSG 083,035

MP91,902

P2501,723

MAC-101,723

Lifetime map wins

11,864dust2

4,171inferno

2,007nuke

1,060vertigo

1,003office

661train

172lake

159cbble

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

45Matches

64%Win rate

1.37Avg K/D

—ADR

38%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

5Longest win streak

Recent Faceit resultsLWLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Vertigo	7	71%	1.74	18.7
Mirage	7	71%	1.73	23.6
Inferno	6	83%	1.32	16.3
Nuke	2	100%	1.64	23.5
Overpass	2	100%	2.14	22.5
Ancient	1	0%	1.93	29.0

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.

21.5%Headshot accuracy

35.2%Accuracy (enemy spotted)

38.1%Spray accuracy

82.3%Counter-strafing

8.6°Preaim

582msReaction time

39.0%T opening success

41.9%CT opening success

0.74Enemies flashed / flash

10.9%Flash assists

7.88HE damage / grenade

13.14Flashes / 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 38.9737% — 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.

44% win rate across 9 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
dust2	13–11	0.11	25%	11 Jul →
ancient	13–6	-0.03	13%	2 Jul →
train	5–13	-0.01	42%	28 Jun →
dust2	13–6	0.06	12%	28 Jun →
dust2	3–13	-0.08	3%	26 Jun →
inferno	11–13	0.00	18%	26 Jun →
anubis	7–13	-0.02	29%	18 Jun →
vertigo	2–13	-0.02	26%	18 Jun →
dust2	11–13	0.05	24%	13 Jun →
dust2	12–12	-0.04	19%	12 Jun →
inferno	13–4	0.09	18%	12 Jun →
dust2	16–14	0.03	18%	3 Jun →
dust2	13–4	0.06	49%	3 Jun →
nuke	11–13	0.03	18%	20 May →
dust2	13–11	0.04	18%	20 May →
overpass	4–13	0.07	14%	19 May →
inferno	15–15	-0.01	19%	19 May →
ancient	8–13	0.07	17%	18 May →
dust2	13–8	-0.00	29%	18 May →
office	13–11	0.04	22%	14 May →
office	13–0	0.09	40%	14 May →
cache	9–13	0.06	14%	14 May →
dust2	2–13	-0.01	21%	12 May →
cache	13–6	-0.05	26%	11 May →
cache	13–7	0.01	22%	11 May →
cache	13–11	-0.00	21%	9 May →
italy	13–9	0.05	16%	8 May →
cache	13–2	0.10	21%	8 May →
cache	13–8	-0.03	19%	8 May →
overpass	13–10	0.04	27%	5 May →
nuke	13–8	0.03	21%	1 May →
dust2	13–6	0.01	23%	1 May →
dust2	7–13	0.03	23%	1 May →
cache	11–13	0.05	14%	30 Apr →
cache	5–13	-0.02	22%	30 Apr →
cache	11–13	0.04	23%	30 Apr →
overpass	13–10	0.17	18%	25 Apr →
overpass	13–10	0.01	16%	25 Apr →
ancient	13–9	0.01	17%	23 Apr →
anubis	6–13	0.02	18%	23 Apr →
inferno	13–6	0.08	11%	23 Apr →
overpass	13–4	0.08	20%	23 Apr →
mirage	13–11	0.14	21%	20 Apr →
dust2	13–7	0.08	23%	20 Apr →
nuke	13–5	0.04	24%	14 Apr →
dust2	6–13	0.11	21%	11 Apr →
dust2	13–6	0.12	25%	11 Apr →
nuke	7–13	0.01	25%	11 Apr →
mirage	8–13	0.07	20%	11 Apr →
office	13–1	0.15	51%	9 Apr →
ancient	13–8	0.03	14%	3 Apr →
nuke	5–13	0.05	23%	3 Apr →
dust2	2–13	-0.06	16%	3 Apr →
mirage	3–13	0.05	23%	2 Apr →
dust2	13–8	0.13	29%	26 Mar →
ancient	7–13	-0.01	18%	26 Mar →
office	13–2	0.20	20%	25 Mar →
italy	13–11	0.06	32%	25 Mar →
inferno	4–13	0.01	9%	15 Nov →
train	13–8	-0.05	9%	15 Nov →
agency	9–13	0.03	34%	8 Nov →
office	9–13	0.05	32%	27 Oct →
train	13–5	0.04	23%	21 Sept →
mirage	15–15	0.02	14%	20 Sept →
dust2	6–13	-0.07	13%	20 Sept →
overpass	7–13	0.03	20%	17 Sept →
nuke	7–13	0.06	27%	17 Sept →
overpass	13–9	-0.02	14%	16 Sept →
mirage	16–14	0.03	18%	16 Sept →
dust2	12–12	0.04	23%	15 Sept →
dust2	15–15	0.01	11%	14 Sept →
inferno	13–5	0.06	26%	14 Sept →
ancient	15–15	0.04	17%	14 Sept →
train	6–13	0.04	25%	9 Sept →
overpass	13–11	0.01	18%	8 Sept →
office	7–13	-0.01	10%	7 Sept →
office	13–9	0.09	25%	7 Sept →
inferno	10–13	0.09	24%	6 Aug →
mirage	13–10	0.02	16%	6 Aug →
inferno	13–6	0.06	13%	3 Aug →
nuke	13–11	0.09	14%	2 Aug →
overpass	13–9	0.04	11%	2 Aug →
nuke	13–9	0.05	22%	1 Aug →
overpass	10–13	0.05	18%	1 Aug →
nuke	11–13	0.05	13%	1 Aug →
overpass	15–15	0.07	12%	1 Aug →
dust2	13–5	0.07	17%	1 Aug →
dust2	11–13	0.03	12%	31 Jul →
dust2	10–13	0.01	12%	31 Jul →
nuke	13–7	0.06	18%	31 Jul →
mirage	3–0	0.04	0%	31 Jul →
ancient	13–10	0.01	11%	30 Jul →
nuke	10–13	0.10	14%	30 Jul →
dust2	13–4	0.12	25%	30 Jul →
dust2	13–11	0.05	18%	28 Jul →
dust2	9–13	0.02	13%	27 Jul →
mirage	8–0	0.05	29%	27 Jul →
dust2	13–7	0.15	25%	15 Jul →
anubis	13–11	0.04	10%	15 Jul →
inferno	2–13	-0.01	24%	12 Jul →