Flawlezz — CS2 Stats

76561198053158586[U:1:92892858]

1,679Tracked matches30%Win rate2020Tracked since

CSDB Rating3.7 Learning

Premier CS Rating13,303Blue band · top ~37.4% of ranked players (population est.)

CSDB Leaderboard#13442 of 19663 tracked

FaceitLevel 3Top 90.6% of ranked FACEIT players

WingmanGold Nova I

Ladder ranks via Leetify

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Performance scores

Aim52

Positioning41

Utility48

0–100 skill scores via Leetify.

Recent form

COLD42–53–5Last 10042%Win rateLLLLLLLWLL

Last 10 vs previous 10: -40pp win rate · -0.01 avg rating

Player DNA

Aim5.2

Aggression6.5

Utility4.8

Positioning4.1

Opening Duels1.8

Clutch1.8

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 81% playstyle similarity

Most alike: opening-duel success, utility contribution.

Where you differ: lower positioning profile; 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. 600ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 68% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim5.2

Positioning4.1

Utility4.8

Mechanics4.0

Opening Duels1.8

Win Impact0.0

Composite 3.7/10 (Learning), 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 rating0.00+0.03

first ⅓ avg -0.03 → last ⅓ avg 0.00

Reaction time602ms−44ms

first ⅓ avg 646ms → last ⅓ avg 602ms

Headshot accuracy20.5%+0.3%

first ⅓ avg 20.2% → last ⅓ avg 20.5%

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

0.23Best rating — poseidon 9–3

13–1Biggest win — anubis

5Longest win streak

L7Current streak

7–8In matches decided by ≤2 rounds

8Overtime games

Map breakdown

ancientBest map · 60% over 10mirageWeakest map · 20% over 10

Map	Grade	Played	Record	Win rate	Avg rating
cache	C	30	13–17	43%	-0.02
inferno	C	18	8–10	44%	-0.01
ancient	A	10	6–4	60%	-0.01
mirage	D	10	2–8	20%	-0.04
dust2	C	8	3–5	38%	-0.02
anubis	B	8	4–4	50%	-0.00
nuke	D	5	1–4	20%	-0.03
poseidon	—	3	2–1	67%	0.05
fachwerk	—	2	0–2	0%	-0.06
overpass	—	2	2–0	100%	0.02
train	—	2	0–2	0%	-0.06
debris	—	1	0–1	0%	-0.05
alpine	—	1	1–0	100%	-0.03

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (20% over 10). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

69Matches

46%Win rate

1.24Avg K/D

74.1ADR

42%Headshot %

Clutches & streaks

29%1v1 clutch win

67%1v2 clutch win

4Longest win streak

Recent Faceit resultsWLLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	2	0%	0.90	19.0
Inferno	2	100%	1.12	12.0
Dust2	2	50%	0.60	8.5
Cache	2	100%	0.82	12.5
Vertigo	1	0%	0.81	13.0
Anubis	1	0%	1.44	23.0
Nuke	1	0%	0.53	9.0

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.

20.5%Headshot accuracy

31.8%Accuracy (enemy spotted)

35.2%Spray accuracy

68.2%Counter-strafing

11.4°Preaim

600msReaction time

38.4%T opening success

36.2%CT opening success

0.50Enemies flashed / flash

1.6%Flash assists

10.22HE damage / grenade

6.97Flashes / 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 38.4113% — below the 40% mark we flag

Spend your practice time on Mirage

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

20% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	7–13	0.02	29%	23 Aug →
ancient	8–13	0.03	25%	21 Aug →
inferno	9–13	0.04	11%	16 Aug →
mirage	8–13	0.01	11%	15 Aug →
nuke	11–13	-0.05	17%	15 Aug →
cache	11–13	0.01	5%	15 Aug →
inferno	9–13	0.00	15%	15 Aug →
anubis	13–1	0.06	19%	15 Aug →
cache	2–13	-0.09	9%	15 Aug →
fachwerk	5–13	-0.03	19%	13 Aug →
cache	16–14	0.03	30%	11 Aug →
nuke	13–3	-0.02	16%	10 Aug →
ancient	13–5	0.03	28%	10 Aug →
inferno	7–13	-0.08	13%	9 Aug →
dust2	11–13	-0.01	19%	8 Aug →
ancient	1–13	-0.07	27%	8 Aug →
poseidon	9–3	0.23	20%	8 Aug →
inferno	13–9	-0.01	27%	7 Aug →
inferno	13–16	-0.00	26%	7 Aug →
inferno	11–13	-0.02	18%	27 Jul →
inferno	6–13	-0.01	6%	27 Jul →
nuke	12–16	-0.01	22%	25 Jul →
cache	6–13	-0.04	26%	25 Jul →
anubis	13–8	0.02	22%	25 Jul →
inferno	13–5	-0.02	31%	25 Jul →
inferno	8–13	-0.00	45%	25 Jul →
mirage	7–13	-0.09	14%	25 Jul →
cache	11–13	-0.02	16%	25 Jul →
dust2	9–13	-0.02	13%	25 Jul →
inferno	13–9	0.02	31%	25 Jul →
cache	16–14	0.01	23%	23 Jul →
cache	13–5	0.07	27%	23 Jul →
anubis	13–9	0.05	18%	23 Jul →
anubis	7–13	-0.04	18%	22 Jul →
cache	13–8	0.00	10%	22 Jul →
dust2	13–11	-0.00	20%	22 Jul →
cache	7–13	-0.05	22%	21 Jul →
mirage	4–13	-0.08	13%	20 Jul →
cache	13–9	-0.04	13%	20 Jul →
inferno	5–13	-0.04	14%	19 Jul →
mirage	11–13	-0.03	14%	19 Jul →
cache	13–3	0.11	24%	17 Jul →
mirage	13–3	-0.03	21%	17 Jul →
nuke	6–13	-0.05	24%	17 Jul →
inferno	13–1	0.04	21%	17 Jul →
poseidon	9–4	-0.03	21%	17 Jul →
inferno	9–13	0.06	22%	17 Jul →
cache	13–6	0.05	18%	17 Jul →
ancient	15–15	0.08	19%	15 Jul →
inferno	13–7	0.02	11%	15 Jul →
ancient	13–10	-0.04	15%	15 Jul →
anubis	10–13	-0.02	14%	15 Jul →
anubis	6–13	0.01	8%	14 Jul →
fachwerk	4–13	-0.09	8%	14 Jul →
debris	6–9	-0.05	26%	14 Jul →
ancient	13–6	-0.00	17%	13 Jul →
cache	15–15	0.03	19%	13 Jul →
dust2	13–4	-0.01	21%	12 Jul →
cache	10–13	-0.01	17%	9 Jul →
cache	10–13	-0.02	13%	9 Jul →
mirage	13–10	-0.01	33%	9 Jul →
cache	3–13	-0.08	33%	8 Jul →
cache	12–12	-0.07	18%	8 Jul →
cache	13–8	0.01	14%	7 Jul →
inferno	0–9	-0.18	20%	6 Jul →
cache	6–13	0.05	27%	6 Jul →
cache	12–12	-0.02	26%	6 Jul →
inferno	13–9	-0.05	13%	5 Jul →
poseidon	6–9	-0.05	18%	2 Jul →
dust2	5–13	-0.07	14%	2 Jul →
inferno	13–7	0.08	33%	2 Jul →
ancient	13–5	-0.01	30%	2 Jul →
overpass	13–11	-0.02	11%	1 Jul →
cache	5–13	-0.09	12%	1 Jul →
cache	13–3	0.04	22%	30 Jun →
mirage	11–13	0.01	26%	30 Jun →
anubis	6–13	-0.09	30%	30 Jun →
mirage	3–13	-0.08	25%	29 Jun →
cache	11–13	-0.05	26%	29 Jun →
cache	7–13	-0.12	23%	28 Jun →
train	7–13	-0.08	21%	17 Jun →
train	5–13	-0.05	33%	17 Jun →
cache	4–13	-0.11	19%	16 Jun →
cache	13–5	-0.03	19%	15 Jun →
ancient	15–15	-0.07	11%	15 Jun →
cache	1–13	-0.03	14%	15 Jun →
nuke	6–13	-0.01	31%	13 Jun →
inferno	13–11	0.01	28%	13 Jun →
mirage	3–13	-0.08	27%	13 Jun →
cache	13–8	-0.03	16%	12 Jun →
cache	13–7	0.04	22%	11 Jun →
cache	13–8	-0.03	14%	9 Jun →
alpine	13–4	-0.03	14%	8 Jun →
ancient	13–11	-0.03	26%	4 Jun →
mirage	10–13	-0.08	10%	3 Jun →
overpass	13–9	0.07	20%	2 Jun →
dust2	13–8	0.06	12%	1 Jun →
ancient	16–14	-0.03	30%	31 May →
anubis	13–9	0.01	12%	31 May →
dust2	5–13	-0.08	5%	31 May →