june eighth — CS2 Stats

US76561198182222115[U:1:221956387]Steam profile ↗✓ No bans

563Tracked matches36%Win rate2020Tracked since

CSDB Rating5.3 DevelopingPassive Rifler

Premier CS Rating16,804Purple band · top ~21.2% of ranked players (population est.)

CSDB Leaderboard#12736 of 22026 tracked

FaceitLevel 6Top 54.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim66

Positioning56

Utility52

0–100 skill scores via Leetify.

Recent form

COLD45–49–6Last 10045%Win rateLLLWLLWLLL

Last 10 vs previous 10: -30pp win rate · -0.01 avg rating

Player DNA

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

Aim6.6

Aggression4.4

Utility5.2

Positioning5.6

Opening Duels1.3

Clutch1.0

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 89% playstyle similarity

Most alike: opening-fight frequency, 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 51% on CT to 20% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 593ms 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

Aim6.6

Positioning5.6

Utility5.2

Mechanics7.7

Opening Duels2.6

Win Impact0.2

Composite 5.3/10 (Developing), 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 rating-0.01−0.01

first ⅓ avg 0.00 → last ⅓ avg -0.01

Reaction time590ms+1ms

first ⅓ avg 589ms → last ⅓ avg 590ms

Headshot accuracy17.1%−4.4%

first ⅓ avg 21.5% → last ⅓ avg 17.1%

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

0.16Best rating — ancient 13–5

13–0Biggest win — cache

7Longest win streak

L3Current streak

6–4In matches decided by ≤2 rounds

5Overtime games

Map breakdown

nukeBest map · 62% over 13dust2Weakest map · 25% over 12

Map	Grade	Played	Record	Win rate	Avg rating
cache	B	15	7–8	47%	0.01
nuke	A	13	8–5	62%	0.02
ancient	A	13	8–5	62%	0.02
inferno	C	12	5–7	42%	0.00
dust2	D	12	3–9	25%	0.01
anubis	D	12	4–8	33%	-0.02
mirage	C	7	3–4	43%	0.02
vertigo	A	5	3–2	60%	-0.00
office	—	4	2–2	50%	0.02
overpass	—	3	1–2	33%	0.01
train	—	2	1–1	50%	-0.04
shelter	—	1	0–1	0%	-0.10
boulder	—	1	0–1	0%	-0.05

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (25% over 12). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

187Matches

48%Win rate

1.14Avg K/D

78.5ADR

35%Headshot %

Clutches & streaks

25%1v1 clutch win

25%1v2 clutch win

7Longest win streak

Recent Faceit resultsLWWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Nuke	15	73%	1.19	15.1
Mirage	14	43%	1.06	16.4
Inferno	12	58%	1.27	19.3
Dust2	10	40%	1.01	15.5
Anubis	8	50%	0.80	15.4
Ancient	8	25%	1.32	19.3
Cache	6	67%	1.17	14.0
Overpass	4	75%	1.23	23.3

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.

17.6%Headshot accuracy

32.7%Accuracy (enemy spotted)

33.6%Spray accuracy

84.7%Counter-strafing

10.3°Preaim

593msReaction time

19.5%T opening success

51.1%CT opening success

0.52Enemies flashed / flash

4.1%Flash assists

6.99HE damage / grenade

19.65Flashes / 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 19.5318% — below the 40% mark we flag

Spend your practice time on Dust 2

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

25% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
inferno	6–13	-0.02	28%	8 Aug →
vertigo	9–13	-0.05	7%	30 Jul →
cache	5–13	-0.05	50%	30 Jul →
nuke	13–8	0.04	12%	28 Jul →
cache	10–13	-0.02	6%	26 Jul →
nuke	14–16	0.09	13%	26 Jul →
ancient	13–6	0.05	15%	26 Jul →
mirage	5–13	-0.06	19%	25 Jul →
shelter	6–13	-0.10	50%	22 Jul →
boulder	2–13	-0.05	14%	22 Jul →
office	12–12	0.07	57%	22 Jul →
dust2	3–13	0.01	35%	22 Jul →
ancient	13–7	-0.03	19%	18 Jul →
anubis	13–11	-0.07	12%	18 Jul →
anubis	15–15	-0.01	10%	17 Jul →
nuke	13–3	0.08	14%	17 Jul →
mirage	13–5	0.04	21%	16 Jul →
anubis	8–13	-0.08	15%	16 Jul →
cache	9–13	-0.03	14%	15 Jul →
dust2	13–10	-0.02	23%	15 Jul →
cache	13–7	-0.07	21%	13 Jul →
inferno	10–13	0.00	4%	13 Jul →
nuke	13–5	0.07	7%	13 Jul →
ancient	8–13	-0.04	8%	13 Jul →
cache	11–13	0.03	11%	11 Jul →
inferno	11–13	-0.03	10%	10 Jul →
ancient	5–13	-0.02	13%	10 Jul →
nuke	3–13	-0.05	7%	10 Jul →
anubis	13–16	0.01	15%	10 Jul →
dust2	13–3	0.05	5%	9 Jul →
anubis	13–7	-0.01	4%	9 Jul →
nuke	13–5	-0.03	11%	9 Jul →
ancient	13–8	-0.02	12%	9 Jul →
ancient	8–13	-0.02	13%	9 Jul →
nuke	10–13	0.01	5%	9 Jul →
ancient	13–7	0.05	19%	9 Jul →
dust2	9–13	-0.01	9%	9 Jul →
inferno	13–11	-0.03	6%	9 Jul →
anubis	5–13	-0.09	5%	9 Jul →
nuke	4–13	-0.07	8%	9 Jul →
dust2	9–13	0.00	21%	9 Jul →
overpass	22–20	0.06	21%	5 Jul →
inferno	8–13	-0.04	16%	3 Jul →
inferno	13–9	0.05	16%	3 Jul →
nuke	13–8	0.00	13%	3 Jul →
inferno	13–8	0.06	28%	3 Jul →
anubis	6–13	-0.03	17%	3 Jul →
ancient	11–13	0.02	14%	2 Jul →
mirage	8–13	-0.02	40%	1 Jul →
ancient	13–8	0.06	11%	1 Jul →
ancient	13–4	0.00	29%	1 Jul →
anubis	13–3	-0.02	21%	1 Jul →
nuke	13–4	-0.01	11%	1 Jul →
ancient	13–5	0.16	23%	1 Jul →
inferno	13–3	0.06	21%	1 Jul →
nuke	13–8	0.09	14%	29 Jun →
inferno	10–13	0.08	21%	25 Jun →
ancient	13–6	0.03	19%	25 Jun →
inferno	10–13	-0.05	13%	25 Jun →
nuke	13–2	0.04	15%	25 Jun →
anubis	13–9	0.02	4%	24 Jun →
cache	12–12	-0.01	14%	24 Jun →
dust2	12–12	0.07	35%	24 Jun →
mirage	2–13	-0.02	21%	20 Jun →
vertigo	13–3	0.12	9%	20 Jun →
cache	9–13	0.06	22%	20 Jun →
dust2	3–13	0.05	35%	16 Jun →
cache	13–11	0.09	32%	13 Jun →
cache	9–13	0.00	23%	13 Jun →
mirage	13–10	0.03	32%	13 Jun →
dust2	2–13	0.10	26%	13 Jun →
cache	13–4	0.04	0%	13 Jun →
dust2	6–11	-0.08	36%	12 Jun →
cache	13–11	-0.04	14%	12 Jun →
vertigo	7–13	-0.11	6%	12 Jun →
mirage	4–13	0.06	24%	1 Jun →
overpass	15–15	0.03	12%	1 Jun →
cache	13–0	0.06	10%	1 Jun →
cache	9–13	0.04	18%	31 May →
ancient	4–13	-0.00	14%	31 May →
anubis	3–13	0.01	4%	31 May →
vertigo	13–9	0.06	16%	30 May →
anubis	7–13	0.02	5%	30 May →
anubis	1–13	-0.02	13%	30 May →
train	13–7	0.02	12%	23 May →
vertigo	13–7	-0.04	31%	23 May →
cache	13–3	0.05	17%	23 May →
overpass	7–13	-0.07	14%	16 May →
dust2	13–10	-0.03	18%	16 May →
inferno	5–13	0.01	16%	16 May →
cache	13–6	-0.03	21%	16 May →
office	12–12	-0.02	23%	15 May →
office	4–2	-0.03	100%	15 May →
office	13–8	0.05	38%	15 May →
train	3–13	-0.10	45%	15 May →
inferno	13–9	-0.06	32%	15 May →
dust2	2–13	0.01	29%	15 May →
nuke	5–13	-0.03	11%	14 May →
mirage	13–2	0.07	10%	13 May →
dust2	7–13	0.04	7%	13 May →