AdeptFknBDS — CS2 Stats

76561197960878544[U:1:612816]✓ No bans

3,321Tracked matches52%Win rate2020Tracked since

CSDB Rating6.5 SolidAggressive Rifler

FaceitLevel 10 · 2,026 ELOTop 12.4% of ranked FACEIT players

WingmanGold Nova Master

Ladder ranks via Leetify

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Performance scores

Aim77

Positioning63

Utility62

0–100 skill scores via Leetify.

Recent form

STEADY46–53–1Last 10046%Win rateLLLWLLWWTW

Last 10 vs previous 10: +10pp win rate · +0.06 avg rating

Player DNA

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

Aim7.7

Aggression9.1

Utility6.2

Positioning6.3

Opening Duels4.9

Clutch3.2

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 donk 94% 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

Strengths

CT openings. 67% 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 67% on CT to 32% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 556ms 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

Aim7.7

Positioning6.3

Utility6.2

Mechanics6.0

Opening Duels4.9

Win Impact5.6

Composite 6.5/10 (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+0.03

first ⅓ avg -0.01 → last ⅓ avg 0.02

Reaction time569ms−40ms

first ⅓ avg 609ms → last ⅓ avg 569ms

Headshot accuracy18.8%+0.1%

first ⅓ avg 18.6% → last ⅓ avg 18.8%

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

0.33Best rating — inferno 9–3

13–2Biggest win — dust2

8Longest win streak

L3Current streak

7–8In matches decided by ≤2 rounds

9Overtime games

Map breakdown

mirageBest map · 64% over 11anubisWeakest map · 23% over 13

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	35	15–20	43%	-0.01
cache	A	14	8–6	57%	0.03
anubis	D	13	3–10	23%	0.01
mirage	A	11	7–4	64%	0.02
inferno	D	10	3–7	30%	0.05
ancient	B	8	4–4	50%	-0.01
nuke	A	7	4–3	57%	0.03
vertigo	—	2	2–0	100%	0.12

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (23% over 13). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

2,633Matches

52%Win rate

1.05Avg K/D

79.6ADR

43%Headshot %

Clutches & streaks

36%1v1 clutch win

18%1v2 clutch win

13Longest win streak

Recent Faceit resultsLLWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	594	53%	1.08	17.3
Mirage	274	49%	0.97	15.9
Ancient	250	42%	0.98	16.0
Anubis	198	52%	0.99	16.2
Inferno	192	47%	0.96	16.0
Nuke	133	51%	0.93	15.7
Cache	75	59%	1.02	16.4
Overpass	46	43%	0.87	15.2

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.

17.9%Headshot accuracy

36.5%Accuracy (enemy spotted)

39.9%Spray accuracy

77.1%Counter-strafing

8.8°Preaim

556msReaction time

32.2%T opening success

67.3%CT opening success

0.60Enemies flashed / flash

7.5%Flash assists

12.29HE damage / grenade

10.44Flashes / 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 32.2338% — 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.

23% win rate across 13 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
cache	10–13	-0.02	15%	27 Aug →
anubis	10–13	-0.00	15%	27 Aug →
cache	12–16	-0.02	17%	26 Aug →
nuke	13–11	-0.01	16%	26 Aug →
ancient	10–13	-0.06	25%	26 Aug →
ancient	18–22	0.02	14%	24 Aug →
anubis	16–14	-0.06	7%	24 Aug →
dust2	9–6	0.04	38%	23 Aug →
cache	12–12	0.20	25%	22 Aug →
anubis	13–3	0.20	24%	22 Aug →
anubis	9–13	-0.04	16%	20 Aug →
inferno	11–13	-0.03	12%	19 Aug →
dust2	11–13	-0.05	15%	18 Aug →
dust2	6–13	-0.05	0%	17 Aug →
anubis	7–13	0.01	29%	17 Aug →
cache	13–11	-0.06	16%	17 Aug →
mirage	13–8	-0.01	5%	17 Aug →
inferno	5–9	-0.03	12%	16 Aug →
dust2	7–13	0.00	10%	16 Aug →
mirage	13–11	-0.01	29%	15 Aug →
dust2	5–13	-0.06	18%	15 Aug →
cache	13–9	0.00	13%	15 Aug →
cache	13–10	0.11	20%	15 Aug →
nuke	5–0	0.06	35%	15 Aug →
mirage	13–8	0.01	17%	14 Aug →
cache	13–3	0.08	25%	14 Aug →
dust2	13–5	0.10	35%	14 Aug →
cache	13–5	0.09	8%	14 Aug →
nuke	13–9	0.11	18%	14 Aug →
mirage	10–13	-0.03	28%	13 Aug →
cache	6–13	0.08	20%	11 Aug →
mirage	7–13	0.11	28%	11 Aug →
nuke	7–9	-0.03	15%	11 Aug →
dust2	8–13	-0.06	26%	10 Aug →
dust2	4–13	-0.09	11%	10 Aug →
dust2	11–13	0.00	20%	9 Aug →
cache	13–10	0.02	9%	9 Aug →
vertigo	9–5	0.21	35%	9 Aug →
inferno	3–9	0.03	19%	9 Aug →
inferno	7–9	0.14	35%	9 Aug →
vertigo	13–11	0.02	16%	9 Aug →
mirage	22–19	-0.01	25%	8 Aug →
mirage	11–13	0.02	20%	8 Aug →
dust2	9–13	-0.00	24%	7 Aug →
dust2	8–13	-0.08	25%	7 Aug →
ancient	13–9	0.02	19%	7 Aug →
dust2	0–13	-0.04	13%	6 Aug →
dust2	19–17	0.00	45%	6 Aug →
dust2	1–13	-0.09	50%	5 Aug →
dust2	13–8	-0.03	35%	5 Aug →
dust2	4–13	-0.09	21%	4 Aug →
inferno	9–3	0.33	19%	4 Aug →
nuke	6–9	0.14	23%	4 Aug →
inferno	3–9	0.14	29%	4 Aug →
mirage	13–8	-0.00	20%	3 Aug →
mirage	13–7	0.01	28%	3 Aug →
dust2	7–13	0.06	28%	3 Aug →
inferno	13–8	0.01	18%	1 Aug →
dust2	13–7	-0.03	29%	1 Aug →
mirage	13–6	0.11	20%	1 Aug →
anubis	9–13	0.03	25%	31 Jul →
inferno	9–13	0.01	17%	31 Jul →
dust2	16–13	0.01	25%	31 Jul →
anubis	17–19	-0.05	13%	30 Jul →
dust2	13–6	0.13	31%	30 Jul →
dust2	10–13	-0.03	25%	30 Jul →
anubis	5–13	0.03	20%	29 Jul →
inferno	13–9	-0.01	34%	29 Jul →
dust2	13–8	-0.00	32%	28 Jul →
dust2	13–11	-0.01	14%	28 Jul →
ancient	13–3	-0.02	10%	28 Jul →
mirage	13–16	-0.01	31%	27 Jul →
cache	13–4	0.02	15%	26 Jul →
anubis	13–10	-0.02	14%	25 Jul →
ancient	13–7	-0.02	19%	24 Jul →
nuke	17–19	-0.02	18%	23 Jul →
dust2	9–13	-0.00	28%	23 Jul →
cache	5–13	-0.07	17%	22 Jul →
dust2	4–13	-0.06	11%	22 Jul →
dust2	10–13	0.03	18%	21 Jul →
cache	10–13	-0.02	17%	21 Jul →
ancient	1–13	-0.07	13%	21 Jul →
anubis	7–13	-0.02	24%	21 Jul →
dust2	8–13	-0.08	5%	18 Jul →
anubis	10–13	-0.04	21%	18 Jul →
dust2	4–13	-0.02	13%	17 Jul →
dust2	5–13	-0.09	20%	17 Jul →
dust2	13–8	0.07	25%	16 Jul →
dust2	13–2	0.03	17%	16 Jul →
anubis	7–13	-0.04	10%	16 Jul →
inferno	2–13	-0.08	17%	16 Jul →
anubis	6–13	0.09	25%	16 Jul →
cache	13–8	-0.00	20%	16 Jul →
dust2	13–5	0.04	22%	16 Jul →
nuke	13–3	-0.02	15%	15 Jul →
ancient	13–2	-0.02	16%	14 Jul →
dust2	13–7	0.05	22%	14 Jul →
dust2	13–8	0.07	19%	14 Jul →
dust2	13–5	0.01	20%	14 Jul →
ancient	10–13	0.04	15%	14 Jul →