⚡ Č𝗔𝗕𝗔𝗦 — CS2 Stats

76561199197186555[U:1:1236920827]Steam profile ↗✓ No bans

767Tracked matches41%Win rate2021Tracked since

1,804Hours in CS17Hrs last 2 wks

CSDB Rating3.9 LearningPositional Player

FaceitLevel 3Top 90.6% of ranked FACEIT players

WingmanMaster Guardian I

Ladder ranks via Leetify

Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. Today is the first observation — history builds from here and cannot be backfilled. Come back after the next session and the change shows above.

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How this compares with the same rank

Median values for Level 3 among CSDB-tracked players (n=8,548), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

Metric	This player	Level 3 median	Level 4 median	vs Level 4
Headshot rate	45.0%	41.9%	42.7%	above
Shot accuracy	15.2%	12.2%	11.2%	above
Kill/death ratio	0.98	0.98	0.99	meets
Match win rate	40.2%	43.3%	43.9%	3.7% short

This profile matches the typical Level 4 player on 3 of 4 comparable metrics.

Widest gap: Match win rate. That is the metric furthest from the Level 4 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim50

Positioning44

Utility29

0–100 skill scores via Leetify.

Recent form

STEADY46–45–9Last 10046%Win rateWLTWWWWLLW

Last 10 vs previous 10: +20pp win rate · +0.01 avg rating · −0.9pp headshot accuracy · +38ms reaction

Win rate up 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

3–1–1 · 60% win rate
Avg rating 0.01
Avg headshot accuracy 18%
Avg reaction 587ms

Last 10

6–3–1 · 60% win rate
Avg rating -0.00
Avg headshot accuracy 16%
Avg reaction 630ms

Last 20

10–9–1 · 50% win rate
Avg rating -0.01
Avg headshot accuracy 17%
Avg reaction 611ms

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: Positional Player — Positioning stands above the rest of this profile (+1.6 against its own average).

Aim5.0

Utility2.9

Positioning4.4

Opening Duels1.1

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 NiKo 86% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower opening-duel success; 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. 640ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 70% 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

Aim5.0

Positioning4.4

Utility2.9

Mechanics4.4

Opening Duels1.9

Win Impact2.1

Composite 3.9/10 (Learning), 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 -0.02 → last ⅓ avg -0.01

Reaction time576ms−81ms

first ⅓ avg 657ms → last ⅓ avg 576ms

Headshot accuracy17.5%−0.4%

first ⅓ avg 17.8% → last ⅓ avg 17.5%

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.

Personal bests

0.38Best match rating · 9–1 · overpass, 10 Sept →

45%Best headshot accuracy · 4–9 · overpass, 25 Aug →

367msFastest reaction time · 4–9 · overpass, 25 Aug →

13–3Biggest win · mirage, 16 Sept →

Across the last 100 tracked matches.

Highlights

5Longest win streak

5–7In matches decided by ≤2 rounds

1Overtime games

Map breakdown

mirageBest map · 59% over 17anubisWeakest map · 20% over 5

Map	Grade	Played	Record	Win rate	Avg rating
overpass	B	33	16–17	48%	0.03
mirage	A	17	10–7	59%	-0.03
vertigo	C	10	4–6	40%	-0.02
inferno	C	8	3–5	38%	-0.04
dust2	C	7	3–4	43%	-0.01
train	D	7	2–5	29%	-0.04
anubis	D	5	1–4	20%	-0.05
cache	—	4	2–2	50%	-0.01
sanctum	—	3	2–1	67%	0.11
office	—	3	2–1	67%	0.02
shelter	—	1	0–1	0%	-0.06
stronghold	—	1	1–0	100%	-0.06
poseidon	—	1	0–1	0%	-0.07

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

37,992Lifetime kills

0.98K/D

2,527Matches

40.2%Match win rate

45.0%Headshot % · Top 50% of Level 3 players

15.2%Shot accuracy · Top 50% of Level 3 players

5,906MVPs

661Hours (in match)

1,190Bombs planted

205Bombs defused

Most-used weapons

AK-479,201

AWP5,949

M4A4 / M4A1-S5,861

Desert Eagle3,839

P2000 / USP-S2,522

Glock-181,923

MP91,189

Galil AR1,103

SSG 081,056

FAMAS878

Lifetime map wins

3,257office

3,022inferno

1,618dust2

477vertigo

316nuke

210train

101cbble

80lake

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

24Matches

33%Win rate

0.93Avg K/D

—ADR

37%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

3Longest win streak

Recent Faceit resultsLLLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	3	33%	1.30	17.3
Anubis	3	0%	0.77	12.3
Inferno	1	0%	1.57	22.0
Ancient	1	0%	0.64	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.

14.7%Headshot accuracy

31.4%Accuracy (enemy spotted)

35.0%Spray accuracy

69.9%Counter-strafing

8.8°Preaim

640msReaction time

42.6%T opening success

32.4%CT opening success

0.46Enemies flashed / flash

4.0%Flash assists

6.10HE damage / grenade

4.49Flashes / 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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 14.744% — below the 15% mark we flag
Aim Training →
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 0.4573 — below the 0.5 mark we flag
Grenade Lineups →
Advanced Mechanics
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 32.3653% — 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.

20% win rate across 5 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
mirage	13–3	0.01	14%	16 Sept →
dust2	5–13	0.02	26%	14 Sept →
mirage	15–15	0.03	23%	14 Sept →
dust2	13–4	0.01	16%	14 Sept →
mirage	9–0	-0.02	14%	14 Sept →
mirage	13–11	-0.06	11%	13 Sept →
mirage	13–3	-0.01	17%	13 Sept →
shelter	10–13	-0.06	22%	13 Sept →
cache	6–13	0.00	9%	13 Sept →
mirage	13–8	0.04	10%	11 Sept →
mirage	13–10	-0.00	15%	11 Sept →
overpass	2–9	-0.14	8%	10 Sept →
overpass	7–9	-0.15	17%	10 Sept →
overpass	9–1	0.38	19%	10 Sept →
overpass	1–9	-0.10	21%	8 Sept →
overpass	9–7	0.06	15%	8 Sept →
anubis	11–13	-0.06	17%	3 Sept →
cache	13–6	0.02	20%	3 Sept →
inferno	6–13	-0.07	24%	3 Sept →
inferno	6–13	-0.08	14%	3 Sept →
cache	4–13	-0.06	14%	28 Aug →
overpass	7–9	-0.01	10%	28 Aug →
overpass	9–2	0.09	19%	28 Aug →
overpass	5–9	-0.05	18%	27 Aug →
overpass	9–7	0.12	9%	27 Aug →
overpass	8–8	-0.13	12%	27 Aug →
overpass	8–8	-0.06	9%	26 Aug →
overpass	9–6	0.09	11%	26 Aug →
overpass	5–9	-0.11	35%	26 Aug →
overpass	9–1	0.08	15%	26 Aug →
overpass	8–8	0.04	38%	26 Aug →
overpass	4–9	-0.12	45%	25 Aug →
overpass	9–5	0.17	10%	25 Aug →
overpass	8–8	-0.05	29%	25 Aug →
overpass	8–8	-0.02	18%	25 Aug →
overpass	9–0	0.28	36%	23 Aug →
overpass	9–4	0.12	24%	23 Aug →
overpass	9–4	0.11	11%	23 Aug →
overpass	9–0	0.26	16%	23 Aug →
overpass	1–9	-0.17	5%	23 Aug →
overpass	8–8	-0.10	15%	23 Aug →
overpass	9–6	0.13	15%	19 Aug →
overpass	9–1	0.23	19%	19 Aug →
overpass	7–9	-0.01	23%	19 Aug →
overpass	9–3	0.21	17%	19 Aug →
overpass	9–5	0.05	12%	19 Aug →
anubis	5–13	-0.08	21%	18 Aug →
cache	13–6	0.02	13%	18 Aug →
mirage	5–13	-0.07	5%	17 Aug →
dust2	3–13	-0.12	7%	17 Aug →
train	4–13	0.02	11%	16 Aug →
train	9–13	-0.05	9%	16 Aug →
train	10–13	-0.05	6%	13 Aug →
mirage	3–13	-0.08	17%	14 Feb →
vertigo	6–13	-0.10	11%	13 Feb →
stronghold	13–10	-0.06	14%	13 Feb →
vertigo	13–8	-0.06	22%	12 Feb →
vertigo	1–13	-0.07	20%	12 Feb →
dust2	9–13	0.02	11%	12 Feb →
vertigo	13–8	0.09	10%	12 Feb →
mirage	13–8	-0.00	15%	12 Feb →
vertigo	13–11	0.04	16%	12 Feb →
vertigo	9–13	-0.05	6%	12 Feb →
vertigo	6–13	-0.01	7%	12 Feb →
mirage	7–13	-0.04	9%	9 Feb →
inferno	13–9	0.03	18%	9 Feb →
anubis	11–13	-0.05	11%	8 Feb →
anubis	13–9	-0.04	10%	8 Feb →
sanctum	9–1	0.11	13%	2 Feb →
sanctum	9–4	0.17	37%	2 Feb →
sanctum	7–9	0.06	13%	1 Feb →
poseidon	3–9	-0.07	11%	1 Feb →
office	3–13	-0.11	22%	31 Jan →
office	13–9	0.08	16%	21 Jan →
dust2	13–9	-0.03	8%	20 Jan →
mirage	10–13	0.01	13%	14 Jan →
overpass	5–13	-0.15	7%	14 Jan →
dust2	13–9	-0.06	23%	4 Jan →
mirage	13–7	-0.07	11%	4 Jan →
dust2	12–12	0.09	30%	3 Jan →
overpass	10–13	-0.03	13%	3 Jan →
inferno	13–9	0.06	15%	2 Jan →
train	13–5	-0.07	12%	2 Jan →
train	2–13	0.02	36%	2 Jan →
train	13–5	-0.01	22%	2 Jan →
train	2–13	-0.12	16%	1 Jan →
mirage	7–13	-0.06	14%	31 Dec →
inferno	12–12	-0.04	16%	31 Dec →
inferno	8–13	-0.08	15%	30 Dec →
mirage	13–11	-0.03	20%	30 Dec →
inferno	6–13	-0.09	13%	25 Dec →
overpass	13–9	-0.04	11%	25 Dec →
inferno	13–4	-0.03	19%	23 Dec →
mirage	13–8	-0.03	29%	22 Dec →
office	13–4	0.09	15%	21 Dec →
vertigo	13–10	-0.04	23%	21 Dec →
vertigo	3–13	-0.00	17%	21 Dec →
vertigo	7–13	-0.00	23%	21 Dec →
anubis	11–13	-0.02	15%	10 Dec →
mirage	7–13	-0.07	33%	20 Nov →