𝖜𝖔𝖒𝖆𝖓 — CS2 Stats

FI76561198182825569[U:1:222559841]Steam profile ↗✓ No bans

1,015Tracked matches33%Win rate2022Tracked since

1,769Hours in CS4Hrs last 2 wks

CSDB Rating5.9 SolidPositional Player

Premier CS Rating16,753Purple band · top ~21.4% of ranked players (population est.)

CSDB Leaderboard#127988 of 259896 tracked

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 3 Nov 2026 (yesterday). 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: 16,753 +2,014 1 Sept – 3 Nov · 31 days played

19,866Peak Premier in tracked matches

30Days played since 2026-09-01

Premier CS Rating

2,547 below peak (19,300)
-221 over 30 days · steady
Next: Pink band at 20,000 — 3,247 to go
Reached: Purple band · Blue band · Light Blue band
Blue band first seen 2026-09-01
Light Blue band first seen 2026-09-01

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 Purple band among CSDB-tracked players (n=37,767), 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	Purple band median	Pink band median	vs Pink band
Headshot rate	42.8%	44.4%	46.9%	4.1% short
Shot accuracy	3.5%	11.9%	13.0%	9.5% short
Kill/death ratio	1.13	1.03	1.08	above
Match win rate	45.4%	45.2%	46.7%	1.3% short

This profile matches the typical Pink band player on 1 of 4 comparable metrics.

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

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Performance scores

Aim82

Positioning57

Utility52

0–100 skill scores via Leetify.

Recent form

COLD49–50–1Last 10049%Win rateLLLLLLLLLL

Last 10 vs previous 10: −70pp win rate · −0.03 avg rating · +13.2pp headshot accuracy · +32ms reaction

Win rate down 70pp 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

0–5 · 0% win rate
Avg rating 0.04
Avg headshot accuracy 37%
Avg reaction 652ms

Last 10

0–10 · 0% win rate
Avg rating 0.02
Avg headshot accuracy 28%
Avg reaction 629ms

Last 20

7–13 · 35% win rate
Avg rating 0.03
Avg headshot accuracy 21%
Avg reaction 613ms

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 (+1.2 against its own average).

Aim8.2

Utility5.2

Positioning5.7

Opening Duels3.1

Clutch4.2

Strong T-side opener

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 Twistzz 96% playstyle similarity

Most alike: positioning profile, aim 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

Strengths

T openings. 63% T opening-duel success — entries that actually open the round.

Areas to improve

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

CT openings. Opening success drops from 63% on T to 34% on CT — first contacts on the defending side are being lost.

Reaction time. 592ms 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

Positioning5.7

Utility5.2

Mechanics7.2

Opening Duels4.7

Win Impact0.0

Composite 5.9/10 (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 rating0.03+0.00

first ⅓ avg 0.02 → last ⅓ avg 0.03

Reaction time607ms+5ms

first ⅓ avg 602ms → last ⅓ avg 607ms

Headshot accuracy20.8%+4.1%

first ⅓ avg 16.7% → last ⅓ avg 20.8%

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

0.20Best match rating · 3–9 · inferno, 28 Oct →

67%Best headshot accuracy · 3–9 · inferno, 28 Oct →

469msFastest reaction time · 13–5 · ancient, 13 Oct →

13–0Biggest win · ancient, 30 Sept →

Across the last 100 tracked matches.

Highlights

10Longest win streak

L11Current streak

12–6In matches decided by ≤2 rounds

14Overtime games

Map breakdown

nukeBest map · 63% over 19infernoWeakest map · 31% over 16

Map	Grade	Played	Record	Win rate	Avg rating
anubis	B	21	11–10	52%	0.02
dust2	C	21	8–13	38%	0.02
nuke	A	19	12–7	63%	0.01
inferno	D	16	5–11	31%	0.02
ancient	A	10	6–4	60%	0.06
mirage	C	7	3–4	43%	0.02
cache	A	5	3–2	60%	-0.01
overpass	—	1	1–0	100%	0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (31% over 16). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

38,672Lifetime kills

1.13K/D · Top 50% of Purple band

2,261Matches

45.4%Match win rate · Top 50% of Purple band

42.8%Headshot %

3.5%Shot accuracy

4,444MVPs

906Hours (in match)

2,274Bombs planted

638Bombs defused

Most-used weapons

AK-4710,157

M4A4 / M4A1-S8,224

AWP4,004

Desert Eagle2,600

P2000 / USP-S2,304

Glock-181,665

MAC-101,404

P901,155

SSG 081,034

MP91,027

Lifetime map wins

4,349nuke

3,544dust2

3,487inferno

774vertigo

530train

149office

17cbble

16ar_shoots

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

Faceit stats

Combat

114Matches

50%Win rate

1.07Avg K/D

69.1ADR

47%Headshot %

Clutches & streaks

41%1v1 clutch win

25%1v2 clutch win

5Longest win streak

Recent Faceit resultsWLWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Nuke	25	68%	1.12	13.7
Dust2	24	46%	1.05	14.1
Mirage	20	50%	1.00	13.2
Inferno	16	56%	1.18	15.1
Anubis	16	50%	1.19	13.9
Train	4	25%	0.80	14.5
Ancient	3	0%	0.59	9.0
Cache	2	50%	1.73	12.0

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.

19.2%Headshot accuracy

39.8%Accuracy (enemy spotted)

37.7%Spray accuracy

82.5%Counter-strafing

8.5°Preaim

592msReaction time

63.2%T opening success

34.4%CT opening success

0.50Enemies flashed / flash

2.6%Flash assists

5.99HE damage / grenade

7.79Flashes / 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
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 34.3752% — 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.

31% win rate across 16 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
ancient	11–13	0.09	22%	3 Nov →
anubis	7–13	-0.05	31%	2 Nov →
inferno	3–9	0.20	67%	28 Oct →
anubis	8–13	-0.04	23%	22 Oct →
cache	4–13	-0.02	41%	21 Oct →
dust2	5–13	-0.04	20%	20 Oct →
dust2	10–13	0.05	21%	20 Oct →
dust2	7–13	-0.04	24%	19 Oct →
dust2	13–16	0.03	21%	19 Oct →
mirage	10–13	0.03	9%	18 Oct →
mirage	9–13	0.01	8%	18 Oct →
anubis	13–6	0.09	14%	18 Oct →
anubis	13–3	0.09	26%	18 Oct →
mirage	10–13	-0.02	15%	18 Oct →
anubis	14–16	0.09	6%	17 Oct →
cache	13–7	0.01	12%	17 Oct →
anubis	13–10	0.02	15%	17 Oct →
nuke	13–8	-0.00	10%	17 Oct →
dust2	13–6	0.10	18%	17 Oct →
anubis	13–11	0.08	24%	17 Oct →
mirage	9–13	0.02	23%	16 Oct →
ancient	4–13	0.02	16%	16 Oct →
dust2	13–8	-0.01	21%	16 Oct →
inferno	13–7	0.00	23%	16 Oct →
nuke	4–13	-0.02	17%	16 Oct →
inferno	12–16	-0.04	18%	15 Oct →
mirage	13–6	0.04	22%	15 Oct →
ancient	10–13	0.10	28%	15 Oct →
cache	9–13	-0.06	21%	15 Oct →
nuke	9–13	0.01	22%	15 Oct →
dust2	5–13	0.05	19%	15 Oct →
dust2	13–16	0.04	13%	14 Oct →
nuke	13–6	0.05	18%	14 Oct →
anubis	4–13	-0.02	13%	14 Oct →
dust2	14–16	0.05	20%	14 Oct →
anubis	13–7	0.04	15%	14 Oct →
anubis	13–11	0.01	11%	14 Oct →
overpass	13–11	0.01	7%	13 Oct →
dust2	5–13	-0.02	27%	13 Oct →
nuke	16–14	-0.00	18%	13 Oct →
nuke	13–3	0.03	11%	13 Oct →
ancient	13–10	0.08	19%	13 Oct →
ancient	13–5	0.06	16%	13 Oct →
nuke	13–10	0.06	14%	13 Oct →
dust2	16–14	0.00	6%	12 Oct →
nuke	3–13	0.01	22%	12 Oct →
inferno	13–6	-0.04	5%	12 Oct →
nuke	3–13	-0.01	16%	12 Oct →
nuke	13–11	0.05	19%	12 Oct →
nuke	13–16	-0.03	12%	11 Oct →
inferno	11–13	0.00	22%	11 Oct →
inferno	8–13	0.03	29%	11 Oct →
inferno	9–13	-0.01	19%	10 Oct →
anubis	13–9	0.05	20%	10 Oct →
inferno	6–13	0.01	27%	9 Oct →
anubis	16–14	0.02	17%	9 Oct →
dust2	13–11	0.01	23%	9 Oct →
cache	13–11	-0.00	13%	8 Oct →
anubis	8–13	0.05	15%	7 Oct →
dust2	11–13	-0.02	24%	6 Oct →
anubis	13–7	-0.06	24%	6 Oct →
anubis	10–13	0.03	7%	5 Oct →
nuke	13–8	-0.01	19%	5 Oct →
anubis	4–13	-0.07	18%	5 Oct →
dust2	9–13	-0.01	23%	5 Oct →
anubis	11–13	0.05	16%	4 Oct →
dust2	13–3	0.03	26%	4 Oct →
inferno	9–13	0.01	14%	4 Oct →
dust2	7–13	-0.04	30%	3 Oct →
inferno	13–16	0.02	17%	3 Oct →
nuke	13–16	0.00	17%	2 Oct →
ancient	2–13	-0.02	23%	2 Oct →
nuke	13–7	-0.00	17%	1 Oct →
anubis	4–13	-0.05	23%	1 Oct →
inferno	13–10	0.01	12%	1 Oct →
anubis	6–13	-0.03	8%	1 Oct →
inferno	13–6	0.04	22%	1 Oct →
cache	13–9	0.02	12%	30 Sept →
dust2	16–14	0.01	15%	30 Sept →
inferno	13–6	0.06	16%	30 Sept →
ancient	13–5	0.03	11%	30 Sept →
nuke	13–11	0.05	14%	30 Sept →
ancient	13–0	0.17	16%	30 Sept →
anubis	13–8	0.03	25%	30 Sept →
ancient	13–7	0.05	13%	29 Sept →
mirage	13–4	0.07	12%	29 Sept →
dust2	6–13	-0.01	20%	29 Sept →
ancient	16–14	0.04	17%	29 Sept →
inferno	2–13	0.01	11%	29 Sept →
inferno	9–13	-0.02	15%	29 Sept →
dust2	13–10	0.03	22%	28 Sept →
nuke	13–10	0.00	27%	28 Sept →
inferno	8–13	0.01	18%	28 Sept →
dust2	15–15	0.08	17%	27 Sept →
nuke	13–1	0.05	18%	27 Sept →
nuke	13–4	0.03	11%	27 Sept →
anubis	13–7	0.07	16%	27 Sept →
nuke	6–13	-0.03	15%	26 Sept →
dust2	13–4	0.10	20%	26 Sept →
mirage	13–3	0.01	9%	26 Sept →