F𝖗𝖆𝖌𝖌𝖊𝖑 — CS2 Stats

DK76561197960548188[U:1:282460]Steam profile ↗✓ No bans

594Tracked matches50%Win rate2021Tracked since

2,310Hours in CS4Hrs last 2 wks

CSDB Rating5.7 SolidAll-Rounder

Premier CS Rating16,098Purple band · top ~24% of ranked players (population est.)

CSDB Leaderboard#135959 of 260047 tracked

FaceitLevel 5Top 67.6% of ranked FACEIT players

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 3 Nov 2026 (3 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 16,098 +1,099 26 Aug – 3 Nov · 25 days played

18,178Peak Premier in tracked matches

64Days played since 2025-08-12

Premier CS Rating

2,080 below peak (18,178)
+598 over 30 days · improving
Next: Pink band at 20,000 — 3,902 to go
Reached: Purple band · Blue band · Light Blue band

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

How this compares with the same rank

Median values for Level 5 among CSDB-tracked players (n=14,283), 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 5 median	Level 6 median	vs Level 6
Headshot rate	34.2%	43.8%	44.8%	10.6% short
Shot accuracy	14.6%	12.0%	12.4%	above
Kill/death ratio	1.17	1.02	1.03	above
Match win rate	48.3%	44.7%	45.2%	above

This profile matches the typical Level 6 player on 3 of 4 comparable metrics.

Widest gap: Headshot rate. That is the metric furthest from the Level 6 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim61

Positioning55

Utility59

0–100 skill scores via Leetify.

Recent form

HOT46–49–5Last 10046%Win rateWWWLLWLWWW

Last 10 vs previous 10: +30pp win rate · +0.01 avg rating · −4.6pp headshot accuracy · −38ms reaction

Win rate up 30pp 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

3–2 · 60% win rate
Avg rating 0.02
Avg headshot accuracy 11%
Avg reaction 544ms

Last 10

7–3 · 70% win rate
Avg rating 0.02
Avg headshot accuracy 10%
Avg reaction 580ms

Last 20

11–9 · 55% win rate
Avg rating 0.02
Avg headshot accuracy 12%
Avg reaction 599ms

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.

Aim6.1

Utility5.9

Positioning5.5

Opening Duels3.8

Clutch6.0

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 m0NESY 80% playstyle similarity

Most alike: utility contribution, positioning profile.

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

T-side openings. Opening success drops from 51% on CT to 32% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 616ms 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

Aim6.1

Positioning5.5

Utility5.9

Mechanics7.4

Opening Duels2.9

Win Impact5.0

Composite 5.7/10 (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 0.02 → last ⅓ avg 0.01

Reaction time615ms−9ms

first ⅓ avg 624ms → last ⅓ avg 615ms

Headshot accuracy12.1%+1.0%

first ⅓ avg 11.0% → last ⅓ avg 12.1%

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.

Personal bests

0.15Best match rating · 13–11 · nuke, 10 Oct →

26%Best headshot accuracy · 3–9 · inferno, 9 Aug →

438msFastest reaction time · 13–10 · nuke, 3 Nov →

13–0Biggest win · anubis, 1 Sept →

Across the last 100 tracked matches.

Highlights

5Longest win streak

W3Current streak

6–7In matches decided by ≤2 rounds

10Overtime games

Map breakdown

overpassBest map · 73% over 11infernoWeakest map · 33% over 21

Map	Grade	Played	Record	Win rate	Avg rating
nuke	C	21	9–12	43%	0.03
inferno	D	21	7–14	33%	0.01
dust2	B	20	9–11	45%	0.03
overpass	S	11	8–3	73%	0.02
mirage	C	10	4–6	40%	-0.02
ancient	C	7	3–4	43%	0.02
anubis	—	4	4–0	100%	0.05
vertigo	—	2	1–1	50%	0.00
train	—	2	0–2	0%	0.03
cache	—	1	1–0	100%	0.04
cache_b	—	1	0–1	0%	-0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 21). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

59,021Lifetime kills

1.17K/D · Top 25% of Level 5 players

2,988Matches

48.3%Match win rate · Top 25% of Level 5 players

34.2%Headshot %

14.6%Shot accuracy · Top 50% of Level 5 players

7,738MVPs

1,240Hours (in match)

4,302Bombs planted

863Bombs defused

Most-used weapons

AK-4723,399

M4A4 / M4A1-S12,426

P2000 / USP-S3,752

Glock-183,153

MP91,838

FAMAS1,526

MAC-101,352

UMP-451,247

PP-Bizon1,225

AWP1,124

Lifetime map wins

5,911inferno

5,175dust2

4,633nuke

1,279vertigo

1,168train

1,050cbble

242aztec

206dust

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

Faceit stats

Combat

26Matches

65%Win rate

1.14Avg K/D

85.2ADR

32%Headshot %

Clutches & streaks

50%1v1 clutch win

17%1v2 clutch win

8Longest win streak

Recent Faceit resultsWWLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	5	40%	0.87	13.4
Nuke	5	80%	1.04	14.8
Dust2	3	100%	1.25	19.0
Ancient	1	100%	0.80	16.0
Anubis	1	0%	0.19	3.0
Vertigo	1	100%	0.70	7.0

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.

11.6%Headshot accuracy

35.8%Accuracy (enemy spotted)

39.1%Spray accuracy

83.2%Counter-strafing

11.0°Preaim

616msReaction time

32.4%T opening success

50.6%CT opening success

0.66Enemies flashed / flash

4.0%Flash assists

10.55HE damage / grenade

6.29Flashes / 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 11.5728% — below the 15% mark we flag
Aim Training →
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 32.4021% — below the 40% mark we flag

Spend your practice time on Inferno

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

33% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
nuke	13–10	0.02	9%	3 Nov →
nuke	13–8	0.00	7%	1 Nov →
cache	13–6	0.04	10%	27 Oct →
ancient	10–13	0.08	10%	25 Oct →
mirage	6–13	-0.06	16%	16 Oct →
dust2	13–2	0.11	13%	9 Oct →
mirage	6–13	-0.01	10%	1 Oct →
anubis	13–0	0.05	11%	1 Sept →
mirage	13–7	-0.04	14%	27 Aug →
nuke	13–8	0.05	1%	25 Aug →
dust2	13–8	0.02	12%	25 Aug →
anubis	13–5	0.02	12%	9 Aug →
inferno	8–13	0.12	13%	9 Aug →
inferno	3–9	-0.02	26%	9 Aug →
dust2	11–13	0.02	22%	5 Aug →
nuke	6–13	0.00	19%	4 Aug →
dust2	13–10	0.02	12%	2 Aug →
nuke	1–13	-0.01	13%	26 Jul →
nuke	16–14	0.02	10%	25 Jul →
ancient	9–13	-0.05	11%	18 Jul →
dust2	2–13	0.02	14%	7 Jul →
nuke	11–13	0.02	14%	7 Jul →
ancient	8–13	0.00	8%	1 May →
nuke	13–11	0.02	14%	12 Mar →
ancient	13–7	0.06	9%	12 Mar →
dust2	5–13	0.02	13%	12 Mar →
mirage	7–9	-0.06	10%	1 Mar →
inferno	13–5	-0.01	15%	21 Feb →
inferno	6–13	-0.04	2%	13 Feb →
inferno	1–13	-0.11	21%	11 Feb →
dust2	1–12	-0.12	7%	11 Feb →
overpass	13–6	0.05	11%	8 Feb →
overpass	10–13	0.05	12%	8 Feb →
dust2	5–13	0.01	10%	8 Feb →
vertigo	13–8	0.00	5%	7 Feb →
nuke	1–13	-0.04	5%	7 Feb →
inferno	3–13	-0.04	16%	7 Feb →
dust2	15–15	0.01	11%	31 Jan →
dust2	12–16	0.06	19%	30 Jan →
inferno	13–10	0.09	7%	30 Jan →
anubis	10–7	0.10	8%	24 Jan →
inferno	14–16	-0.03	10%	22 Jan →
nuke	9–13	0.08	11%	22 Jan →
overpass	13–5	0.03	9%	16 Jan →
inferno	6–13	0.03	11%	15 Jan →
cache_b	10–13	-0.05	8%	15 Jan →
inferno	5–13	-0.01	12%	15 Jan →
anubis	13–8	0.03	6%	14 Jan →
mirage	13–6	0.04	23%	14 Jan →
nuke	3–13	-0.04	10%	31 Dec →
dust2	13–4	0.01	11%	28 Dec →
dust2	7–0	0.11	0%	13 Dec →
overpass	13–6	-0.02	10%	10 Dec →
inferno	12–12	0.02	9%	10 Dec →
nuke	7–13	-0.07	14%	10 Dec →
train	11–13	0.06	15%	5 Dec →
overpass	13–8	0.04	11%	5 Dec →
vertigo	11–13	0.00	7%	3 Dec →
overpass	13–2	-0.01	14%	3 Dec →
nuke	13–7	0.11	7%	30 Nov →
nuke	10–13	-0.04	11%	26 Nov →
overpass	13–8	0.09	7%	26 Nov →
dust2	13–6	0.01	10%	19 Nov →
inferno	10–13	-0.02	10%	19 Nov →
inferno	13–5	0.02	8%	19 Nov →
mirage	3–13	0.03	9%	13 Nov →
nuke	13–6	0.04	9%	11 Nov →
dust2	6–13	0.01	20%	11 Nov →
ancient	13–5	0.05	10%	9 Nov →
dust2	15–15	0.06	14%	9 Nov →
inferno	16–13	0.07	13%	8 Nov →
dust2	6–13	0.08	12%	8 Nov →
inferno	12–16	0.04	10%	8 Nov →
nuke	7–13	0.00	11%	8 Nov →
nuke	14–16	0.10	7%	8 Nov →
train	4–13	0.01	10%	8 Nov →
overpass	10–13	-0.05	18%	5 Nov →
nuke	12–12	-0.00	8%	29 Oct →
inferno	13–4	0.06	15%	22 Oct →
inferno	6–13	-0.06	8%	22 Oct →
mirage	13–4	0.04	11%	19 Oct →
overpass	6–13	-0.00	8%	17 Oct →
mirage	8–13	-0.06	6%	15 Oct →
overpass	13–6	0.06	9%	15 Oct →
mirage	12–12	0.03	8%	15 Oct →
dust2	13–5	0.09	24%	10 Oct →
ancient	16–14	-0.03	5%	10 Oct →
nuke	13–11	0.15	7%	10 Oct →
inferno	13–10	0.03	10%	7 Oct →
nuke	8–13	0.13	11%	1 Oct →
dust2	13–11	-0.03	17%	28 Sept →
mirage	8–13	-0.09	3%	28 Sept →
nuke	13–7	0.01	13%	27 Sept →
ancient	5–13	0.04	8%	24 Sept →
inferno	6–13	-0.03	9%	23 Sept →
dust2	13–9	-0.03	14%	14 Sept →
dust2	10–13	0.04	14%	1 Sept →
overpass	13–3	0.02	11%	26 Aug →
inferno	13–9	-0.01	11%	13 Aug →
inferno	14–16	0.03	10%	12 Aug →