Blu. — CS2 Stats

US76561198168243155[U:1:207977427]Steam profile ↗✓ No bans

600Tracked matches41%Win rate2024Tracked since

CSDB Rating4.1 Developing

Premier CS Rating10,140Blue band · top ~54.2% of ranked players (population est.)

CSDB Leaderboard#32515 of 45437 tracked

FaceitLevel 4 · 1,005 ELOTop 81.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim52

Positioning48

Utility33

0–100 skill scores via Leetify.

Recent form

COLD49–47–4Last 10049%Win rateLLLLLWLLWL

Last 10 vs previous 10: -30pp win rate · +0.02 avg rating

Player DNA

Aim5.2

Aggression4.9

Utility3.3

Positioning4.8

Opening Duels2.5

Clutch4.2

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, opening-fight frequency.

Where you differ: lower utility contribution; 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 54% on CT to 26% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 619ms 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

Aim5.2

Positioning4.8

Utility3.3

Mechanics5.5

Opening Duels3.0

Win Impact2.1

Composite 4.1/10 (Developing), 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 rating-0.02−0.00

first ⅓ avg -0.02 → last ⅓ avg -0.02

Reaction time629ms−51ms

first ⅓ avg 680ms → last ⅓ avg 629ms

Headshot accuracy16.1%+0.7%

first ⅓ avg 15.4% → last ⅓ avg 16.1%

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

0.11Best rating — dust2 13–1

13–1Biggest win — dust2

4Longest win streak

L5Current streak

7–9In matches decided by ≤2 rounds

8Overtime games

Map breakdown

ancientBest map · 69% over 16anubisWeakest map · 30% over 10

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	22	10–12	45%	-0.03
ancient	S	16	11–5	69%	-0.01
mirage	B	15	7–8	47%	-0.02
dust2	C	14	6–8	43%	-0.01
anubis	D	10	3–7	30%	-0.00
nuke	A	8	5–3	63%	-0.02
cache	B	8	4–4	50%	-0.03
train	—	4	3–1	75%	-0.02
overpass	—	2	0–2	0%	-0.01
vertigo	—	1	0–1	0%	-0.06

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

52Matches

56%Win rate

0.91Avg K/D

69.6ADR

37%Headshot %

Clutches & streaks

41%1v1 clutch win

12%1v2 clutch win

6Longest win streak

Recent Faceit resultsLLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	21	62%	0.95	11.9
Dust2	9	44%	0.95	14.6
Inferno	6	83%	1.04	13.7
Anubis	5	80%	0.76	12.0
Ancient	4	25%	0.68	9.8
Nuke	3	67%	0.96	14.0
Overpass	2	0%	0.84	17.0
Cache	1	0%	0.78	14.0

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.

16.0%Headshot accuracy

32.3%Accuracy (enemy spotted)

34.4%Spray accuracy

74.9%Counter-strafing

10.7°Preaim

619msReaction time

26.1%T opening success

53.8%CT opening success

0.44Enemies flashed / flash

9.0%Flash assists

5.05HE damage / grenade

4.00Flashes / 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.

Grenades & Utility
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.4431 — below the 0.5 mark we flag
Grenade Lineups →
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 26.0657% — 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.

30% win rate across 10 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
nuke	7–13	-0.03	11%	29 Aug →
nuke	11–13	0.01	20%	28 Aug →
dust2	9–13	0.00	27%	27 Aug →
inferno	2–13	-0.08	0%	27 Aug →
inferno	3–13	-0.09	24%	26 Aug →
ancient	13–11	-0.04	16%	26 Aug →
anubis	12–13	-0.02	12%	24 Aug →
ancient	5–13	-0.01	27%	24 Aug →
inferno	13–5	0.04	27%	24 Aug →
dust2	10–13	0.05	18%	15 Aug →
ancient	13–10	-0.06	13%	12 Aug →
mirage	13–6	-0.03	15%	10 Aug →
anubis	3–13	-0.03	10%	9 Aug →
dust2	7–13	-0.09	14%	2 Aug →
inferno	13–4	-0.03	18%	30 Jul →
inferno	10–13	-0.06	16%	26 Jul →
ancient	13–8	-0.07	20%	26 Jul →
dust2	13–5	-0.02	26%	26 Jul →
dust2	4–13	-0.06	3%	23 Jul →
mirage	6–13	0.03	16%	23 Jul →
cache	13–11	-0.01	20%	20 Jul →
mirage	15–15	-0.05	13%	20 Jul →
ancient	11–13	-0.03	19%	19 Jul →
ancient	13–7	0.09	24%	19 Jul →
anubis	3–13	-0.02	10%	19 Jul →
inferno	11–13	-0.02	20%	17 Jul →
cache	13–9	-0.01	25%	16 Jul →
ancient	7–13	-0.05	6%	14 Jul →
mirage	16–13	-0.03	5%	13 Jul →
anubis	13–4	-0.06	5%	12 Jul →
mirage	4–13	-0.04	23%	12 Jul →
mirage	13–11	0.05	19%	12 Jul →
ancient	13–9	0.09	11%	11 Jul →
mirage	13–2	0.05	16%	11 Jul →
mirage	13–10	-0.02	24%	11 Jul →
dust2	9–13	-0.05	13%	11 Jul →
nuke	13–8	-0.06	6%	11 Jul →
dust2	15–15	-0.04	7%	10 Jul →
dust2	3–13	-0.09	20%	10 Jul →
anubis	8–13	0.01	23%	10 Jul →
anubis	14–16	-0.01	14%	10 Jul →
nuke	8–13	-0.03	9%	10 Jul →
ancient	13–11	-0.04	8%	10 Jul →
mirage	10–13	-0.04	9%	10 Jul →
inferno	13–4	-0.00	13%	9 Jul →
ancient	13–5	-0.03	15%	9 Jul →
dust2	13–1	-0.02	29%	9 Jul →
cache	5–13	-0.00	26%	9 Jul →
inferno	13–4	-0.05	20%	9 Jul →
inferno	13–3	-0.07	0%	9 Jul →
mirage	9–13	-0.06	10%	9 Jul →
nuke	13–10	-0.03	13%	9 Jul →
anubis	8–13	0.03	22%	9 Jul →
dust2	13–1	0.11	31%	9 Jul →
cache	1–13	-0.05	5%	9 Jul →
anubis	15–15	0.04	13%	9 Jul →
ancient	13–2	0.07	6%	9 Jul →
inferno	8–13	-0.02	10%	9 Jul →
mirage	10–13	-0.05	23%	9 Jul →
inferno	6–13	-0.07	14%	8 Jul →
vertigo	5–13	-0.06	16%	8 Jul →
ancient	13–4	0.01	23%	8 Jul →
inferno	13–1	-0.02	16%	8 Jul →
cache	12–12	-0.04	21%	7 Jul →
cache	13–7	-0.06	30%	7 Jul →
mirage	13–6	0.02	48%	7 Jul →
anubis	13–6	0.08	14%	7 Jul →
anubis	13–9	-0.01	11%	6 Jul →
train	10–13	-0.08	12%	29 Jun →
dust2	16–13	0.00	15%	25 Jun →
mirage	8–13	0.01	15%	25 Jun →
inferno	8–13	-0.02	17%	24 Jun →
ancient	13–2	-0.02	18%	24 Jun →
dust2	13–5	-0.01	21%	23 Jun →
inferno	9–13	-0.03	24%	23 Jun →
overpass	11–13	-0.02	11%	23 Jun →
ancient	13–5	-0.03	13%	23 Jun →
inferno	4–9	-0.08	12%	20 Jun →
ancient	11–13	-0.03	11%	20 Jun →
train	13–5	-0.05	24%	20 Jun →
inferno	10–13	-0.02	15%	18 Jun →
dust2	1–9	0.08	21%	14 Jun →
nuke	13–3	-0.02	4%	14 Jun →
train	13–8	0.04	9%	13 Jun →
overpass	12–16	-0.01	11%	7 Jun →
inferno	13–3	0.01	26%	7 Jun →
inferno	13–9	0.05	13%	7 Jun →
train	13–11	-0.00	14%	28 May →
mirage	2–13	-0.08	10%	22 May →
inferno	14–16	-0.06	13%	22 May →
inferno	13–11	-0.08	12%	16 May →
cache	10–13	-0.05	19%	16 May →
inferno	8–13	-0.04	15%	13 May →
nuke	13–1	0.01	26%	13 May →
mirage	13–7	-0.05	11%	13 May →
nuke	13–11	0.03	12%	13 May →
ancient	11–13	-0.04	17%	6 May →
cache	13–4	-0.01	10%	6 May →
inferno	13–8	0.00	18%	6 May →
dust2	13–6	0.01	30%	6 May →