𝕿𝖊𝖗𝖒𝖆𝖓 — CS2 Stats

US76561198980481387[U:1:1020215659]Steam profile ↗✓ No bans

834Tracked matches50%Win rate2021Tracked since

1,316Hours in CS

CSDB Rating4.0 DevelopingClutch Specialist

CSDB Leaderboard#126590 of 261308 tracked

FaceitLevel 4Top 81.0% of ranked FACEIT players

WingmanMaster Guardian II

Ladder ranks via Leetify

Rating over time

Premier CS Rating: 16,969 +3,936 16 Feb – 7 Apr · 14 days played

16,969Peak Premier in tracked matches

43Days played since 2025-02-16

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 4 among CSDB-tracked players (n=14,630), 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 4 median	Level 5 median	vs Level 5
Headshot rate	40.9%	42.7%	43.8%	2.9% short
Shot accuracy	13.8%	11.2%	12.0%	above
Kill/death ratio	1.00	0.99	1.02	meets
Match win rate	69.0%	43.9%	44.7%	above

This profile matches the typical Level 5 player on 3 of 4 comparable metrics.

Widest gap: Headshot rate. That is the metric furthest from the Level 5 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim47

Positioning35

Utility27

0–100 skill scores via Leetify.

Recent form

COLD47–38–15Last 10047%Win rateWTLLWLWLTT

Last 10 vs previous 10: −40pp win rate · −0.02 avg rating · +3.3pp headshot accuracy · −29ms reaction

Win rate down 40pp 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

2–2–1 · 40% win rate
Avg rating -0.04
Avg headshot accuracy 26%
Avg reaction 628ms

Last 10

3–4–3 · 30% win rate
Avg rating -0.03
Avg headshot accuracy 23%
Avg reaction 627ms

Last 20

10–7–3 · 50% win rate
Avg rating -0.02
Avg headshot accuracy 21%
Avg reaction 642ms

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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+6 against its own average).

Aim4.7

Utility2.7

Positioning3.5

Opening Duels0.0

Clutch10.0

Reliable in 1v1s

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 89% 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

T-side openings. Opening success drops from 36% on CT to 17% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 664ms 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

Aim4.7

Positioning3.5

Utility2.7

Mechanics6.3

Opening Duels0.7

Win Impact5.0

Composite 4.0/10 (Developing), 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-0.03−0.01

first ⅓ avg -0.02 → last ⅓ avg -0.03

Reaction time643ms−38ms

first ⅓ avg 681ms → last ⅓ avg 643ms

Headshot accuracy20.5%−1.9%

first ⅓ avg 22.4% → last ⅓ avg 20.5%

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

0.17Best match rating · 9–2 · inferno, 31 May →

100%Best headshot accuracy · 7–0 · inferno, 15 May →

406msFastest reaction time · 2–13 · ancient, 15 May →

13–2Biggest win · dust2, 20 Aug →

Across the last 100 tracked matches.

Highlights

5Longest win streak

4–8In matches decided by ≤2 rounds

4Overtime games

Map breakdown

nukeBest map · 71% over 7mirageWeakest map · 29% over 7

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	38	18–20	47%	-0.02
dust2	B	20	10–10	50%	-0.02
ancient	B	11	5–6	45%	-0.04
anubis	D	9	3–6	33%	-0.02
mirage	D	7	2–5	29%	-0.03
nuke	S	7	5–2	71%	-0.02
vertigo	—	3	1–2	33%	0.03
train	—	3	2–1	67%	-0.03
overpass	—	2	1–1	50%	-0.12

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (29% over 7). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Lifetime stats

63,164Lifetime kills

1.00K/D · Top 50% of Level 4 players

9,467Matches

69.0%Match win rate · Top 5% of Level 4 players

40.9%Headshot %

13.8%Shot accuracy · Top 50% of Level 4 players

9,012MVPs

1,316Hours (in match)

2,357Bombs planted

1,275Bombs defused

Most-used weapons

AK-4722,475

M4A4 / M4A1-S14,462

AWP4,648

P2000 / USP-S2,703

MP92,056

Desert Eagle2,028

Glock-181,981

Galil AR1,815

MAC-101,460

P90978

Lifetime map wins

8,896inferno

6,001dust2

3,120nuke

2,697vertigo

919train

120office

109italy

101aztec

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

Faceit stats

Combat

39Matches

51%Win rate

0.80Avg K/D

65.5ADR

45%Headshot %

Clutches & streaks

71%1v1 clutch win

17%1v2 clutch win

4Longest win streak

Recent Faceit resultsWWLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	7	57%	0.64	9.4
Mirage	3	33%	0.86	13.7
Ancient	3	100%	1.02	14.0
Anubis	2	100%	0.71	9.0
Dust2	1	100%	1.19	19.0
Train	1	0%	0.71	12.0
Nuke	1	0%	0.47	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.

18.5%Headshot accuracy

27.5%Accuracy (enemy spotted)

30.5%Spray accuracy

78.4%Counter-strafing

9.3°Preaim

664msReaction time

17.3%T opening success

35.7%CT opening success

0.64Enemies flashed / flash

9.5%Flash assists

9.06HE damage / grenade

10.92Flashes / 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 17.2502% — below the 40% mark we flag

Spend your practice time on Mirage

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

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	13–8	-0.07	19%	2 Feb →
inferno	12–12	-0.02	15%	1 Feb →
inferno	11–13	0.04	20%	18 Oct →
anubis	6–13	-0.08	32%	18 Oct →
ancient	13–4	-0.07	46%	17 Oct →
anubis	7–13	0.04	35%	17 Oct →
inferno	13–3	-0.03	19%	28 Sept →
dust2	4–13	-0.08	19%	18 Sept →
inferno	12–12	-0.08	8%	17 Sept →
dust2	12–12	0.02	18%	14 Sept →
inferno	8–13	-0.05	16%	14 Sept →
inferno	9–1	0.07	19%	14 Sept →
overpass	3–9	-0.26	31%	12 Sept →
inferno	9–4	0.16	29%	12 Sept →
vertigo	5–9	-0.03	10%	12 Sept →
inferno	13–7	0.03	22%	1 Sept →
dust2	13–6	0.01	26%	1 Sept →
ancient	13–9	-0.02	15%	1 Sept →
dust2	13–2	0.01	12%	20 Aug →
anubis	13–10	-0.01	18%	20 Aug →
inferno	7–13	-0.07	10%	10 Aug →
mirage	13–11	-0.06	18%	10 Aug →
nuke	8–8	-0.04	10%	2 Aug →
vertigo	7–9	0.08	31%	2 Aug →
inferno	0–9	-0.30	33%	2 Aug →
overpass	9–6	0.03	32%	2 Aug →
nuke	9–7	-0.04	19%	2 Aug →
dust2	12–12	-0.00	16%	5 Jul →
dust2	11–13	-0.00	16%	5 Jul →
nuke	2–9	-0.09	10%	5 Jul →
inferno	8–8	0.05	23%	5 Jul →
inferno	7–9	0.04	24%	4 Jul →
mirage	0–6	-0.10	6%	30 Jun →
inferno	4–13	-0.05	21%	30 Jun →
dust2	13–9	-0.01	23%	30 Jun →
dust2	4–13	-0.01	18%	30 Jun →
mirage	2–13	-0.05	23%	29 Jun →
vertigo	13–9	0.04	8%	29 Jun →
anubis	12–12	-0.02	16%	29 Jun →
mirage	12–12	0.01	11%	29 Jun →
ancient	1–13	-0.01	6%	29 Jun →
inferno	13–8	0.05	22%	28 Jun →
dust2	13–7	-0.04	14%	28 Jun →
dust2	9–13	-0.08	26%	28 Jun →
dust2	6–13	0.00	17%	28 Jun →
inferno	13–11	-0.03	19%	28 Jun →
inferno	9–3	0.02	8%	28 Jun →
nuke	9–5	-0.02	21%	28 Jun →
nuke	9–4	0.13	16%	28 Jun →
anubis	7–13	-0.01	17%	28 Jun →
train	13–6	0.03	31%	10 Jun →
inferno	5–9	-0.16	31%	2 Jun →
inferno	9–4	-0.04	15%	2 Jun →
nuke	9–6	-0.05	16%	2 Jun →
inferno	9–6	0.01	38%	2 Jun →
inferno	7–9	-0.02	32%	31 May →
inferno	9–2	0.17	19%	31 May →
inferno	7–9	-0.12	9%	30 May →
inferno	8–8	0.01	25%	30 May →
inferno	3–13	-0.04	23%	23 May →
inferno	7–0	-0.09	100%	15 May →
dust2	2–8	-0.12	0%	15 May →
ancient	2–13	-0.08	16%	15 May →
inferno	12–12	-0.01	20%	12 May →
dust2	6–13	-0.01	36%	12 May →
ancient	11–13	-0.09	17%	24 Apr →
nuke	13–5	-0.02	16%	7 Apr →
dust2	13–4	-0.00	26%	7 Apr →
anubis	15–15	-0.05	26%	7 Apr →
inferno	13–11	-0.04	25%	4 Apr →
dust2	13–8	-0.02	17%	28 Mar →
inferno	9–13	-0.03	24%	27 Mar →
ancient	9–13	-0.08	21%	27 Mar →
dust2	6–13	-0.02	29%	25 Mar →
inferno	13–6	-0.03	31%	24 Mar →
mirage	9–13	-0.05	15%	24 Mar →
dust2	13–7	0.03	21%	24 Mar →
inferno	10–13	-0.04	8%	23 Mar →
dust2	13–4	-0.02	17%	23 Mar →
inferno	13–10	-0.01	34%	20 Mar →
ancient	15–15	0.03	21%	20 Mar →
train	12–12	-0.08	13%	19 Mar →
inferno	13–7	0.03	20%	18 Mar →
ancient	13–10	0.01	28%	17 Mar →
ancient	13–3	-0.02	24%	17 Mar →
anubis	13–7	0.02	24%	16 Mar →
dust2	13–9	-0.04	20%	16 Mar →
inferno	3–13	-0.07	27%	16 Mar →
ancient	11–13	-0.09	15%	16 Mar →
anubis	13–10	-0.08	19%	2 Mar →
mirage	4–13	0.00	19%	2 Mar →
mirage	13–8	0.01	29%	2 Mar →
inferno	13–9	0.08	35%	2 Mar →
train	13–10	-0.03	29%	24 Feb →
inferno	9–4	-0.03	15%	18 Feb →
inferno	8–13	-0.04	28%	17 Feb →
ancient	13–7	0.01	12%	17 Feb →
inferno	15–15	0.03	29%	17 Feb →
anubis	15–15	-0.02	19%	17 Feb →
inferno	13–9	-0.02	19%	16 Feb →