𝕊𝕚𝕝𝕖𝕟𝕔3𝕣 — CS2 Stats

JP76561199656607477[U:1:1696341749]Steam profile ↗✓ No bans

368Tracked matches59%Win rate2025Tracked since

1,452Hours in CS20Hrs last 2 wks

CSDB Rating7.4 StrongPositional Player

Premier CS Rating26,882Top 5% of 215,558 CSDB-tracked playersRed band · top ~2.1% of ranked players (population est.)

CSDB Leaderboard#7454 of 261709 tracked

FaceitLevel 8Top 31.2% of ranked FACEIT players

WingmanGold Nova I

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 29 Oct 2026 (17 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: 26,882 +10,629 5 Jul – 29 Oct · 18 days played

27,455Peak Premier in tracked matches

38Days played since 2026-07-05

Premier CS Rating

573 below peak (27,455)
+1,882 over 30 days · improving
Next: Gold band at 30,000 — 3,118 to go
Reached: Red band · Pink band · Purple band · Blue band
Red band first seen 2026-09-22
Pink band first seen 2026-09-22

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 8 among CSDB-tracked players (n=15,878), 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 8 median	Level 9 median	vs Level 9
Headshot rate	52.5%	46.8%	48.2%	above
Shot accuracy	0.0%	13.0%	13.2%	13.2% short
Kill/death ratio	1.06	1.06	1.07	meets
Match win rate	52.0%	46.3%	46.9%	above

This profile matches the typical Level 9 player on 3 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 9 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim81

Positioning63

Utility48

0–100 skill scores via Leetify.

Recent form

STEADY66–31–3Last 10066%Win rateWWLWLLTWWL

Last 10 vs previous 10: +10pp win rate · +0.01 avg rating · +7.3pp headshot accuracy · +36ms 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

3–2 · 60% win rate
Avg rating 0.02
Avg headshot accuracy 32%
Avg reaction 608ms

Last 10

5–4–1 · 50% win rate
Avg rating -0.00
Avg headshot accuracy 32%
Avg reaction 616ms

Last 20

9–10–1 · 45% win rate
Avg rating -0.01
Avg headshot accuracy 29%
Avg reaction 598ms

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 (+1.4 against its own average).

Aim8.1

Utility4.8

Positioning6.3

Opening Duels5.0

Clutch3.4

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 donk 92% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: 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

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

Reaction time. 600ms 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

Aim8.1

Positioning6.3

Utility4.8

Mechanics7.7

Opening Duels6.9

Win Impact7.9

Composite 7.4/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 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 time600ms+18ms

first ⅓ avg 582ms → last ⅓ avg 600ms

Headshot accuracy30.1%+2.6%

first ⅓ avg 27.5% → last ⅓ avg 30.1%

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

0.21Best match rating · 13–1 · cache, 21 Oct →

67%Best headshot accuracy · 5–13 · dust2, 20 Sept →

414msFastest reaction time · 13–0 · inferno, 14 Sept →

13–0Biggest win · nuke, 30 Sept →

Across the last 100 tracked matches.

Highlights

14Longest win streak

W2Current streak

4–6In matches decided by ≤2 rounds

5Overtime games

Map breakdown

cacheBest map · 88% over 8dust2Weakest map · 53% over 19

Map	Grade	Played	Record	Win rate	Avg rating
mirage	S	22	16–6	73%	-0.00
dust2	B	19	10–9	53%	-0.03
inferno	A	14	8–6	57%	-0.01
anubis	A	11	7–4	64%	0.02
cache	S	8	7–1	88%	0.04
nuke	S	8	6–2	75%	-0.01
ancient	S	6	4–2	67%	-0.02
office	—	4	3–1	75%	0.04
train	—	4	2–2	50%	0.02
vertigo	—	3	2–1	67%	0.01
overpass	—	1	1–0	100%	-0.01

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (53% over 19). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

32,605Lifetime kills

1.06K/D · Top 50% of Level 8 players

1,770Matches

52.0%Match win rate · Top 25% of Level 8 players

52.5%Headshot % · Top 25% of Level 8 players

0.0%Shot accuracy

5,772MVPs

651Hours (in match)

963Bombs planted

450Bombs defused

Most-used weapons

AK-478,928

AWP5,504

M4A4 / M4A1-S4,741

Desert Eagle3,741

P2000 / USP-S1,942

SSG 081,856

Glock-18959

Knife536

MP9449

Galil AR432

Lifetime map wins

6,599dust2

2,156inferno

1,325nuke

308train

224vertigo

198office

11italy

1ar_shoots

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

Faceit stats

Combat

120Matches

58%Win rate

1.13Avg K/D

80.3ADR

51%Headshot %

Clutches & streaks

37%1v1 clutch win

20%1v2 clutch win

9Longest win streak

Recent Faceit resultsWLWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	44	66%	1.11	15.2
Ancient	22	45%	1.22	18.4
Dust2	22	50%	1.10	16.1
Inferno	11	64%	1.07	14.9
Nuke	10	50%	1.22	16.3
Anubis	9	67%	1.03	14.7
Cache	1	100%	1.00	15.0
Vertigo	1	0%	1.41	24.0

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.

30.1%Headshot accuracy

30.6%Accuracy (enemy spotted)

38.2%Spray accuracy

84.6%Counter-strafing

9.7°Preaim

600msReaction time

58.9%T opening success

56.0%CT opening success

0.57Enemies flashed / flash

11.6%Flash assists

6.86HE damage / grenade

6.39Flashes / match

Recent matches

Map	Score	Rating	HS%	Date
anubis	13–7	0.05	35%	14 Nov →
anubis	13–7	0.03	39%	14 Nov →
ancient	6–13	-0.02	24%	29 Oct →
anubis	13–7	0.02	39%	29 Oct →
cache	11–13	0.01	25%	29 Oct →
dust2	5–13	0.00	43%	28 Oct →
office	12–12	0.02	40%	28 Oct →
office	13–2	-0.06	18%	28 Oct →
ancient	13–7	-0.01	29%	26 Oct →
inferno	4–13	-0.07	29%	26 Oct →
inferno	13–4	0.02	27%	25 Oct →
anubis	4–13	0.01	31%	24 Oct →
inferno	14–16	0.01	15%	24 Oct →
dust2	7–13	-0.01	33%	24 Oct →
mirage	11–13	-0.02	37%	24 Oct →
dust2	13–7	0.04	29%	23 Oct →
nuke	13–5	0.02	14%	23 Oct →
mirage	13–9	-0.04	18%	23 Oct →
inferno	2–13	-0.01	27%	23 Oct →
ancient	2–13	-0.12	18%	23 Oct →
dust2	13–4	0.04	37%	21 Oct →
cache	13–7	0.01	36%	21 Oct →
cache	13–9	-0.03	27%	21 Oct →
cache	13–6	-0.00	38%	21 Oct →
cache	13–1	0.21	36%	21 Oct →
inferno	5–13	-0.04	26%	20 Oct →
inferno	13–10	-0.03	37%	20 Oct →
train	13–1	0.12	33%	9 Oct →
train	6–13	-0.08	30%	7 Oct →
train	13–3	0.07	34%	7 Oct →
cache	13–4	0.08	40%	1 Oct →
inferno	13–8	0.03	33%	1 Oct →
mirage	13–4	-0.01	13%	1 Oct →
nuke	13–0	0.01	19%	30 Sept →
vertigo	6–13	0.00	13%	26 Sept →
vertigo	13–7	-0.03	32%	23 Sept →
mirage	12–1	0.15	24%	22 Sept →
dust2	5–13	-0.10	67%	20 Sept →
anubis	13–8	0.03	22%	17 Sept →
anubis	13–5	0.05	42%	17 Sept →
nuke	13–0	-0.01	0%	14 Sept →
inferno	13–2	-0.02	47%	14 Sept →
dust2	4–0	-0.04	0%	14 Sept →
dust2	13–0	-0.00	11%	14 Sept →
dust2	13–1	-0.01	37%	14 Sept →
mirage	13–0	-0.04	40%	14 Sept →
mirage	4–0	0.03	67%	14 Sept →
dust2	13–3	-0.05	37%	14 Sept →
mirage	13–2	0.01	10%	14 Sept →
inferno	13–0	-0.02	11%	14 Sept →
dust2	16–13	-0.12	30%	14 Sept →
mirage	13–5	-0.01	32%	14 Sept →
dust2	10–13	-0.13	19%	14 Sept →
mirage	13–11	-0.07	16%	13 Sept →
nuke	5–13	-0.04	30%	13 Sept →
ancient	13–1	0.04	36%	11 Sept →
dust2	13–8	-0.05	37%	11 Sept →
anubis	0–9	-0.04	0%	30 Aug →
cache	13–2	0.12	49%	26 Aug →
nuke	13–7	-0.02	28%	23 Aug →
anubis	2–13	0.02	32%	23 Aug →
ancient	13–2	-0.01	16%	18 Aug →
mirage	13–4	-0.03	48%	18 Aug →
mirage	13–2	0.11	32%	18 Aug →
train	11–13	-0.01	50%	12 Aug →
inferno	11–13	0.00	31%	11 Aug →
mirage	4–13	-0.01	29%	11 Aug →
dust2	9–13	-0.01	26%	10 Aug →
dust2	13–11	0.05	36%	8 Aug →
dust2	3–13	-0.10	32%	8 Aug →
vertigo	13–4	0.05	34%	29 Jul →
cache	13–7	-0.05	40%	24 Jul →
nuke	13–8	-0.02	36%	24 Jul →
anubis	13–11	0.02	31%	22 Jul →
dust2	15–15	0.03	23%	22 Jul →
mirage	3–13	-0.02	40%	20 Jul →
nuke	13–1	0.07	35%	20 Jul →
inferno	9–6	0.07	26%	20 Jul →
mirage	13–8	-0.03	27%	20 Jul →
mirage	13–7	0.08	29%	20 Jul →
anubis	0–5	0.00	0%	20 Jul →
inferno	11–13	0.02	24%	15 Jul →
anubis	13–11	0.01	35%	14 Jul →
mirage	15–15	-0.03	20%	14 Jul →
nuke	1–13	-0.07	0%	14 Jul →
office	13–4	0.11	23%	9 Jul →
office	13–7	0.08	31%	9 Jul →
mirage	7–13	-0.11	36%	7 Jul →
mirage	13–4	0.04	23%	7 Jul →
inferno	13–8	0.02	13%	7 Jul →
mirage	2–9	-0.03	57%	5 Jul →
inferno	13–2	-0.05	43%	5 Jul →
mirage	13–6	0.05	18%	5 Jul →
dust2	5–13	-0.01	20%	5 Jul →
mirage	13–8	-0.05	14%	5 Jul →
mirage	16–12	-0.03	15%	5 Jul →
ancient	13–8	-0.03	32%	5 Jul →
dust2	3–13	-0.04	13%	5 Jul →
dust2	13–1	-0.04	64%	5 Jul →
overpass	13–7	-0.01	11%	5 Jul →