k6 — CS2 Stats

76561198829706492[U:1:869440764]Steam profile ↗

1,343Tracked matches46%Win rate2020Tracked since

CSDB Rating7.1 StrongAggressive Rifler

Premier CS Rating24,848Top 25% of 17,162 CSDB-tracked playersPink band · top ~3.2% of ranked players (population est.)

CSDB Leaderboard#4000 of 26496 tracked

FaceitLevel 3Top 90.6% of ranked FACEIT players

WingmanGold Nova III

Ladder ranks via Leetify

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Performance scores

Aim92

Positioning64

Utility59

0–100 skill scores via Leetify.

Recent form

STEADY43–53–4Last 10043%Win rateWWLLWTWLTL

Last 10 vs previous 10: +0pp win rate · -0.01 avg rating

Player DNA

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

Aim9.2

Aggression10.0

Utility5.9

Positioning6.4

Opening Duels5.0

Sharp aimerStrong 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 sh1ro 95% playstyle similarity

Most alike: utility contribution, positioning 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

Aim. Aim score of 92 — the mechanical foundation is a clear strength.

CT openings. 61% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

T-side openings. Opening success drops from 61% on CT to 39% 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

Aim9.2

Positioning6.4

Utility5.9

Mechanics7.9

Opening Duels5.0

Win Impact3.8

Composite 7.1/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.07−0.00

first ⅓ avg 0.07 → last ⅓ avg 0.07

Reaction time490ms−20ms

first ⅓ avg 510ms → last ⅓ avg 490ms

Headshot accuracy19.1%−2.0%

first ⅓ avg 21.1% → last ⅓ avg 19.1%

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

0.27Best rating — overpass 13–8

13–0Biggest win — inferno

5Longest win streak

W2Current streak

7–3In matches decided by ≤2 rounds

5Overtime games

Map breakdown

overpassBest map · 80% over 5ancientWeakest map · 22% over 9

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	17	9–8	53%	0.09
mirage	C	17	6–11	35%	0.02
dust2	B	15	7–8	47%	0.06
nuke	C	14	6–8	43%	0.08
ancient	D	9	2–7	22%	0.09
anubis	C	9	4–5	44%	0.05
overpass	S	5	4–1	80%	0.16
cache	—	4	3–1	75%	0.07
train	—	4	1–3	25%	0.06
vertigo	—	3	1–2	33%	0.13
office	—	2	0–2	0%	0.04
shelter	—	1	0–1	0%	0.16

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (22% over 9). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

19.1%Headshot accuracy

39.5%Accuracy (enemy spotted)

35.0%Spray accuracy

85.6%Counter-strafing

5.9°Preaim

486msReaction time

39.4%T opening success

60.6%CT opening success

0.61Enemies flashed / flash

3.9%Flash assists

7.60HE damage / grenade

13.65Flashes / 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 39.4072% — below the 40% mark we flag

Spend your practice time on Ancient

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

22% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
cache	13–9	0.10	9%	2 Aug →
inferno	8–5	0.02	9%	2 Aug →
mirage	8–13	0.15	17%	2 Aug →
office	3–13	0.01	21%	2 Aug →
inferno	16–12	0.18	23%	1 Aug →
ancient	12–12	0.02	17%	1 Aug →
nuke	13–7	0.10	19%	1 Aug →
dust2	5–13	0.04	16%	1 Aug →
vertigo	12–12	0.07	18%	30 Jul →
inferno	2–13	-0.01	9%	27 Jul →
inferno	12–16	0.09	18%	27 Jul →
nuke	6–13	0.13	18%	26 Jul →
dust2	13–2	0.10	23%	26 Jul →
nuke	8–13	0.06	21%	26 Jul →
mirage	5–13	-0.02	33%	26 Jul →
cache	13–8	0.13	17%	26 Jul →
anubis	13–9	0.11	18%	26 Jul →
ancient	5–13	0.09	18%	26 Jul →
mirage	13–11	0.06	13%	26 Jul →
nuke	8–13	0.06	33%	23 Jul →
cache	5–13	-0.01	26%	23 Jul →
mirage	13–9	0.09	8%	19 Jul →
train	4–13	0.00	17%	18 Jul →
shelter	10–13	0.16	15%	18 Jul →
nuke	3–13	-0.04	32%	18 Jul →
mirage	10–13	-0.04	24%	14 Jul →
dust2	13–8	0.08	26%	12 Jul →
inferno	13–3	0.14	8%	12 Jul →
cache	16–14	0.06	19%	12 Jul →
inferno	13–10	0.05	21%	11 Jul →
mirage	11–13	0.10	23%	9 Jul →
inferno	13–10	0.05	22%	9 Jul →
anubis	16–14	0.03	13%	9 Jul →
anubis	0–13	-0.04	12%	9 Jul →
dust2	13–10	0.10	27%	26 Jun →
inferno	13–0	0.19	16%	26 Jun →
nuke	4–13	0.01	29%	24 Jun →
anubis	6–13	0.09	11%	24 Jun →
anubis	13–11	0.13	16%	16 May →
dust2	10–12	0.11	19%	23 Apr →
train	3–13	-0.00	11%	23 Apr →
ancient	10–13	0.13	13%	20 Apr →
overpass	13–8	0.27	20%	20 Apr →
inferno	13–4	0.26	22%	20 Apr →
overpass	13–3	0.17	16%	20 Apr →
nuke	13–8	0.05	24%	20 Apr →
dust2	13–9	0.05	22%	20 Apr →
train	9–13	0.05	25%	19 Apr →
inferno	4–13	0.14	15%	19 Apr →
vertigo	3–13	0.05	11%	19 Apr →
overpass	13–9	0.10	19%	18 Apr →
ancient	6–13	0.02	9%	18 Apr →
office	10–13	0.07	37%	10 Apr →
inferno	13–7	0.09	9%	9 Apr →
mirage	5–13	0.03	19%	8 Apr →
dust2	9–13	-0.00	20%	8 Apr →
mirage	1–5	-0.08	33%	8 Apr →
inferno	10–13	0.10	27%	8 Apr →
dust2	13–7	0.15	26%	7 Apr →
mirage	13–3	-0.05	31%	7 Apr →
anubis	6–13	0.03	27%	7 Apr →
nuke	13–6	0.08	11%	7 Apr →
ancient	13–9	-0.03	17%	7 Apr →
mirage	13–3	0.09	15%	3 Apr →
anubis	8–13	0.02	30%	2 Apr →
inferno	13–8	0.04	20%	2 Apr →
ancient	8–13	0.16	22%	1 Apr →
mirage	7–13	-0.04	18%	1 Apr →
ancient	12–12	0.05	9%	30 Mar →
inferno	12–12	0.06	27%	30 Mar →
mirage	13–10	0.00	27%	30 Mar →
dust2	8–13	-0.02	36%	30 Mar →
dust2	11–13	0.00	15%	28 Mar →
inferno	9–13	-0.06	11%	28 Mar →
dust2	9–13	-0.01	9%	26 Mar →
mirage	2–13	-0.06	14%	26 Mar →
mirage	4–13	0.01	18%	26 Mar →
nuke	9–13	0.16	29%	25 Mar →
dust2	13–6	0.22	19%	25 Mar →
mirage	2–13	-0.05	18%	25 Mar →
mirage	9–13	0.08	22%	25 Mar →
nuke	10–13	0.09	16%	25 Mar →
nuke	13–11	0.14	25%	23 Mar →
nuke	13–8	0.10	45%	23 Mar →
anubis	13–9	0.07	23%	23 Mar →
overpass	13–8	0.20	23%	23 Mar →
dust2	16–14	0.06	15%	23 Mar →
dust2	4–13	-0.02	10%	23 Mar →
anubis	9–13	0.03	16%	22 Mar →
nuke	5–13	-0.05	31%	22 Mar →
ancient	13–4	0.26	26%	22 Mar →
overpass	3–13	0.07	10%	22 Mar →
vertigo	13–2	0.26	15%	20 Mar →
ancient	10–13	0.07	21%	20 Mar →
inferno	5–13	0.10	20%	20 Mar →
mirage	13–7	0.04	33%	20 Mar →
train	13–6	0.19	15%	20 Mar →
dust2	1–13	-0.01	33%	20 Mar →
nuke	13–11	0.22	28%	18 Mar →
inferno	10–13	0.10	19%	18 Mar →