𝐬𝐚𝐧𝐜𝐡𝐞𝐳 — CS2 Stats

KR76561199563524553[U:1:1603258825]Steam profile ↗✓ No bans

1,544Tracked matches43%Win rate2023Tracked since

CSDB Rating5.6 SolidAll-Rounder

FaceitLevel 10Top 12.4% of ranked FACEIT players

WingmanLegendary Eagle Master

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 17 Sep 2026 (59 days ago). Ranks are recorded once per day this page is viewed.

+10Tracked matches · now 1,544

+2.1ppWin rate · 40.7% → 42.9%

Rating over time

Premier CS Rating: 26,418 +1,622 15 Jan – 30 Jun · 18 days played

26,418Peak Premier in tracked matches

43Days played since 2026-01-15

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

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Performance scores

Aim82

Positioning50

Utility50

0–100 skill scores via Leetify.

Recent form

STEADY48–46–6Last 10048%Win rateLLWLWWLWTT

Last 10 vs previous 10: +10pp win rate · −0.02 avg rating · −1.8pp headshot accuracy · −84ms reaction

Win rate +10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

2–3 · 40% win rate
Avg rating 0.00
Avg headshot accuracy 33%
Avg reaction 517ms

Last 10

4–4–2 · 40% win rate
Avg rating -0.00
Avg headshot accuracy 31%
Avg reaction 533ms

Last 20

7–11–2 · 35% win rate
Avg rating 0.00
Avg headshot accuracy 31%
Avg reaction 575ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: All-Rounder — No style dimension stands clear of the others in this profile.

Aim8.2

Utility5.0

Positioning5.0

Opening Duels3.7

Clutch3.2

Limited utility dependence

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

Plays most like ZywOo 90% playstyle similarity

Most alike: aim profile, positioning profile.

Where you differ: lower opening-duel success; lower utility contribution.

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

Positioning. Positioning trails aim by 32 points — deaths here waste a strong aim profile.

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

Reaction time. 557ms 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

Aim8.2

Positioning5.0

Utility5.0

Mechanics6.2

Opening Duels2.5

Win Impact2.6

Composite 5.6/10 (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 rating0.01+0.01

first ⅓ avg -0.00 → last ⅓ avg 0.01

Reaction time552ms−54ms

first ⅓ avg 606ms → last ⅓ avg 552ms

Headshot accuracy30.3%+2.7%

first ⅓ avg 27.6% → last ⅓ avg 30.3%

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.

Personal bests

0.16Best match rating · 9–7 · inferno, 8 Jun →

57%Best headshot accuracy · 12–12 · cache, 8 Jun →

406msFastest reaction time · 13–9 · inferno, 20 Aug →

13–0Biggest win · inferno, 13 Mar →

Across the last 100 tracked matches.

Highlights

4Longest win streak

L2Current streak

14–8In matches decided by ≤2 rounds

8Overtime games

Map breakdown

ancientBest map · 70% over 10anubisWeakest map · 27% over 11

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	24	14–10	58%	-0.00
inferno	A	21	13–8	62%	0.02
mirage	C	20	7–13	35%	0.02
anubis	D	11	3–8	27%	-0.01
ancient	S	10	7–3	70%	0.01
nuke	D	7	2–5	29%	0.01
cache	—	3	0–3	0%	-0.04
overpass	—	3	1–2	33%	0.03
train	—	1	1–0	100%	0.04

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (27% over 11). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

768Matches

52%Win rate

1.14Avg K/D

79.8ADR

58%Headshot %

Clutches & streaks

36%1v1 clutch win

23%1v2 clutch win

9Longest win streak

Recent Faceit resultsWLWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	233	49%	1.12	16.2
Dust2	126	56%	1.26	16.0
Anubis	125	50%	1.10	17.0
Ancient	93	49%	1.07	16.0
Inferno	91	62%	1.17	15.7
Vertigo	46	52%	1.10	16.8
Nuke	35	51%	1.12	15.7
Overpass	15	40%	1.24	18.3

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.

31.0%Headshot accuracy

32.2%Accuracy (enemy spotted)

28.8%Spray accuracy

77.9%Counter-strafing

7.6°Preaim

557msReaction time

38.0%T opening success

41.8%CT opening success

0.65Enemies flashed / flash

4.9%Flash assists

11.95HE damage / grenade

4.83Flashes / 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 38.0092% — 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.

27% win rate across 11 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
dust2	5–13	-0.09	47%	29 Oct →
inferno	7–13	0.01	34%	13 Oct →
ancient	13–6	-0.00	20%	13 Oct →
dust2	10–13	0.05	29%	24 Sept →
anubis	13–10	0.03	37%	24 Sept →
mirage	13–11	-0.03	23%	24 Sept →
cache	11–13	-0.06	26%	22 Sept →
inferno	13–9	0.06	31%	20 Aug →
mirage	12–12	0.01	40%	14 Aug →
cache	15–15	-0.03	19%	29 Jul →
nuke	11–13	0.12	24%	27 Jul →
anubis	13–11	0.05	30%	27 Jul →
mirage	11–13	0.04	41%	27 Jul →
mirage	9–13	0.00	44%	21 Jul →
dust2	4–13	-0.10	50%	21 Jul →
mirage	13–4	0.02	33%	20 Jul →
dust2	13–1	0.05	24%	16 Jul →
dust2	7–13	-0.02	26%	2 Jul →
dust2	1–13	-0.06	20%	2 Jul →
overpass	9–13	0.01	31%	2 Jul →
dust2	13–10	0.07	43%	30 Jun →
inferno	13–8	0.03	24%	23 Jun →
inferno	13–2	0.08	24%	23 Jun →
inferno	4–13	-0.06	26%	23 Jun →
inferno	6–13	-0.01	23%	23 Jun →
mirage	4–13	0.07	37%	19 Jun →
dust2	0–7	-0.07	0%	19 Jun →
anubis	10–13	-0.05	15%	17 Jun →
inferno	13–11	0.01	40%	17 Jun →
train	13–11	0.04	44%	17 Jun →
dust2	9–13	0.02	27%	12 Jun →
dust2	13–11	-0.04	33%	9 Jun →
mirage	7–13	0.03	33%	8 Jun →
cache	12–12	-0.03	57%	8 Jun →
inferno	9–7	0.16	42%	8 Jun →
ancient	13–11	0.06	34%	26 May →
mirage	7–13	-0.02	40%	26 May →
inferno	11–13	-0.08	10%	23 May →
dust2	3–13	-0.00	13%	20 May →
dust2	16–14	0.01	21%	20 May →
dust2	13–6	0.01	29%	19 May →
mirage	9–13	-0.04	25%	19 May →
dust2	13–9	-0.02	23%	17 May →
dust2	16–19	-0.04	25%	30 Apr →
inferno	13–8	-0.00	20%	23 Apr →
dust2	13–11	-0.01	20%	23 Apr →
anubis	11–13	0.03	33%	23 Apr →
mirage	13–11	0.02	41%	23 Apr →
ancient	13–10	0.09	38%	22 Apr →
dust2	13–11	0.06	42%	18 Apr →
mirage	7–13	0.10	52%	18 Apr →
anubis	9–13	-0.01	38%	27 Mar →
mirage	13–8	0.00	29%	27 Mar →
mirage	8–13	-0.04	32%	16 Mar →
inferno	13–0	0.14	35%	13 Mar →
mirage	6–3	0.00	50%	13 Mar →
dust2	13–3	0.03	44%	13 Mar →
ancient	13–9	0.03	21%	7 Mar →
nuke	9–13	-0.08	39%	7 Mar →
inferno	13–4	0.04	34%	7 Mar →
inferno	15–15	-0.02	23%	16 Feb →
inferno	13–8	0.01	41%	16 Feb →
dust2	13–9	0.02	37%	12 Feb →
anubis	10–13	-0.04	18%	8 Feb →
mirage	13–11	0.09	42%	8 Feb →
dust2	13–7	0.04	43%	8 Feb →
dust2	8–13	0.06	26%	4 Feb →
mirage	11–13	-0.06	31%	4 Feb →
anubis	11–13	-0.01	26%	31 Jan →
inferno	10–13	-0.03	30%	31 Jan →
inferno	4–13	0.04	32%	31 Jan →
ancient	6–13	-0.04	38%	27 Jan →
dust2	13–9	-0.06	26%	27 Jan →
nuke	13–10	0.01	38%	27 Jan →
overpass	10–13	-0.01	10%	27 Jan →
mirage	10–13	0.06	22%	27 Jan →
nuke	6–13	0.01	20%	27 Jan →
ancient	9–13	-0.04	20%	27 Jan →
inferno	13–3	0.02	29%	26 Jan →
nuke	8–13	-0.04	14%	26 Jan →
mirage	13–7	0.02	31%	26 Jan →
inferno	13–6	0.01	18%	26 Jan →
mirage	15–15	-0.01	30%	26 Jan →
inferno	7–13	-0.04	29%	26 Jan →
inferno	13–6	-0.04	33%	25 Jan →
anubis	8–13	-0.03	16%	25 Jan →
ancient	6–1	0.03	50%	25 Jan →
overpass	13–11	0.09	27%	25 Jan →
anubis	13–11	0.01	26%	25 Jan →
mirage	13–16	0.04	31%	25 Jan →
inferno	11–4	-0.00	32%	25 Jan →
anubis	2–13	-0.08	23%	24 Jan →
anubis	15–15	-0.03	31%	24 Jan →
ancient	6–1	-0.06	18%	24 Jan →
ancient	13–10	0.10	20%	24 Jan →
dust2	13–10	-0.01	30%	24 Jan →
nuke	10–13	-0.03	39%	16 Jan →
nuke	13–2	0.06	40%	16 Jan →
ancient	11–13	-0.01	23%	16 Jan →
dust2	16–13	0.03	27%	15 Jan →