𝔏𝔄𝔇ℜℑ𝔏ℌ𝔄 — CS2 Stats

GY76561199007302141[U:1:1047036413]Steam profile ↗✓ No bans

551Tracked matches57%Win rate2023Tracked since

2,838Hours in CS43Hrs last 2 wks

CSDB Rating5.3 DevelopingClutch Specialist

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 11 Sep 2026 (51 days ago). Ranks are recorded once per day this page is viewed.

+71Tracked matches · now 551

+11.8ppWin rate · 44.8% → 56.7%

Rating over time

39Days played since 2026-08-10

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled.

Performance scores

Aim56

Positioning42

Utility56

0–100 skill scores via Leetify.

Recent form

STEADY47–46–7Last 10047%Win rateWLWLWWLWWL

Last 10 vs previous 10: 0pp win rate · +0.01 avg rating · −1.3pp headshot accuracy · +42ms reaction

Win rate 0pp 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 -0.03
Avg headshot accuracy 18%
Avg reaction 631ms

Last 10

6–4 · 60% win rate
Avg rating -0.02
Avg headshot accuracy 23%
Avg reaction 634ms

Last 20

12–8 · 60% win rate
Avg rating -0.02
Avg headshot accuracy 24%
Avg reaction 612ms

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 (+3.1 against its own average).

Aim5.6

Utility5.6

Positioning4.2

Opening Duels0.0

Clutch7.4

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 b1t 74% 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

CT openings. Opening success drops from 48% on T to 29% on CT — first contacts on the defending side are being lost.

Reaction time. 613ms 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

Aim5.6

Positioning4.2

Utility5.6

Mechanics6.9

Opening Duels2.3

Win Impact7.2

Composite 5.3/10 (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-0.02+0.00

first ⅓ avg -0.03 → last ⅓ avg -0.02

Reaction time619ms−2ms

first ⅓ avg 620ms → last ⅓ avg 619ms

Headshot accuracy22.5%+2.8%

first ⅓ avg 19.8% → last ⅓ avg 22.5%

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

0.08Best match rating · 5–13 · dust2, 30 Oct →

40%Best headshot accuracy · 13–7 · dust2, 30 Oct →

398msFastest reaction time · 13–11 · vertigo, 30 Sept →

13–2Biggest win · dust2, 26 Oct →

Across the last 100 tracked matches.

Highlights

4Longest win streak

13–10In matches decided by ≤2 rounds

8Overtime games

Map breakdown

infernoBest map · 52% over 23trainWeakest map · 29% over 7

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	30	15–15	50%	-0.02
inferno	B	23	12–11	52%	-0.02
mirage	B	20	9–11	45%	-0.03
ancient	C	9	4–5	44%	-0.01
train	D	7	2–5	29%	-0.02
anubis	C	5	2–3	40%	-0.04
overpass	—	2	1–1	50%	-0.02
cache	—	2	1–1	50%	0.01
nuke	—	1	0–1	0%	-0.04
vertigo	—	1	1–0	100%	0.01

Across the last 100 tracked matches.

Lifetime stats

68,818Lifetime kills

0.91K/D

4,896Matches

44.6%Match win rate

42.7%Headshot %

4.9%Shot accuracy

5,278MVPs

1,619Hours (in match)

2,988Bombs planted

917Bombs defused

Most-used weapons

AK-4715,526

M4A4 / M4A1-S9,784

AWP5,120

Desert Eagle3,289

P2000 / USP-S3,100

MP92,884

Galil AR2,496

Glock-182,494

MAC-102,398

AUG2,118

Lifetime map wins

9,724dust2

5,846inferno

1,565vertigo

1,304nuke

835train

89ar_shoots

73ar_baggage

55italy

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

Faceit stats

Combat

16Matches

56%Win rate

0.71Avg K/D

55.2ADR

51%Headshot %

Clutches & streaks

57%1v1 clutch win

14%1v2 clutch win

3Longest win streak

Recent Faceit resultsWWLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	5	20%	0.70	9.8
Dust2	5	80%	0.59	8.8
Anubis	3	67%	0.85	11.3
Train	1	100%	0.57	12.0
Ancient	1	0%	0.79	15.0
Inferno	1	100%	1.00	10.0

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.

22.3%Headshot accuracy

31.0%Accuracy (enemy spotted)

26.1%Spray accuracy

81.1%Counter-strafing

11.2°Preaim

613msReaction time

48.0%T opening success

28.6%CT opening success

0.48Enemies flashed / flash

0.8%Flash assists

11.34HE damage / grenade

10.73Flashes / 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.

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 0.4774 — 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 28.6214% — below the 40% mark we flag

Spend your practice time on Train

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.

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
inferno	16–14	0.02	23%	1 Nov →
nuke	5–13	-0.04	12%	1 Nov →
inferno	13–11	-0.02	7%	1 Nov →
dust2	3–13	-0.05	27%	31 Oct →
ancient	13–11	-0.03	20%	31 Oct →
overpass	13–5	-0.00	15%	31 Oct →
dust2	5–13	0.08	38%	30 Oct →
mirage	13–11	-0.02	32%	30 Oct →
dust2	13–7	-0.05	40%	30 Oct →
mirage	6–13	-0.04	17%	30 Oct →
dust2	13–5	-0.04	10%	30 Oct →
anubis	13–16	-0.07	24%	29 Oct →
cache	13–8	0.07	30%	29 Oct →
inferno	5–13	-0.04	33%	29 Oct →
ancient	13–11	0.03	25%	29 Oct →
inferno	13–10	0.00	25%	28 Oct →
ancient	13–9	-0.00	16%	28 Oct →
mirage	13–6	-0.11	30%	28 Oct →
anubis	11–13	-0.05	30%	27 Oct →
inferno	8–13	-0.08	18%	27 Oct →
ancient	13–11	-0.04	20%	26 Oct →
mirage	13–6	-0.06	16%	26 Oct →
ancient	11–13	-0.02	23%	26 Oct →
anubis	13–11	-0.03	16%	26 Oct →
dust2	13–2	0.01	27%	26 Oct →
dust2	17–19	-0.05	19%	23 Oct →
dust2	7–13	-0.02	16%	23 Oct →
ancient	16–19	0.03	19%	19 Oct →
dust2	10–13	-0.06	23%	18 Oct →
inferno	13–2	-0.02	25%	18 Oct →
mirage	8–13	-0.08	16%	18 Oct →
mirage	5–13	-0.03	31%	16 Oct →
inferno	13–11	0.06	22%	16 Oct →
mirage	13–11	-0.02	16%	15 Oct →
dust2	10–13	-0.04	14%	14 Oct →
train	13–7	0.01	27%	14 Oct →
dust2	13–9	0.00	18%	14 Oct →
cache	12–12	-0.06	19%	14 Oct →
train	12–12	-0.05	17%	13 Oct →
dust2	11–13	-0.03	17%	13 Oct →
inferno	13–10	-0.00	22%	11 Oct →
anubis	19–17	-0.03	21%	11 Oct →
mirage	4–13	-0.01	13%	10 Oct →
dust2	13–4	0.03	11%	9 Oct →
mirage	8–13	-0.02	23%	9 Oct →
train	5–13	-0.06	38%	9 Oct →
inferno	13–8	0.02	24%	8 Oct →
ancient	12–12	0.03	28%	8 Oct →
dust2	7–13	-0.06	17%	8 Oct →
inferno	11–13	-0.03	25%	7 Oct →
inferno	16–14	0.03	18%	7 Oct →
dust2	16–14	-0.05	17%	6 Oct →
mirage	13–9	-0.04	12%	6 Oct →
train	10–13	0.01	20%	30 Sept →
mirage	12–12	0.03	20%	30 Sept →
dust2	13–6	0.03	29%	30 Sept →
vertigo	13–11	0.01	32%	30 Sept →
train	12–12	-0.03	21%	23 Sept →
dust2	12–12	-0.01	24%	23 Sept →
inferno	7–13	0.05	22%	22 Sept →
dust2	11–13	-0.07	10%	22 Sept →
mirage	13–9	-0.07	4%	10 Sept →
inferno	13–3	0.02	19%	10 Sept →
dust2	13–10	-0.05	13%	10 Sept →
inferno	9–13	-0.08	18%	4 Sept →
dust2	6–13	-0.06	13%	4 Sept →
inferno	13–4	-0.04	9%	4 Sept →
dust2	9–13	-0.06	29%	2 Sept →
dust2	13–5	-0.07	13%	2 Sept →
inferno	13–8	-0.06	14%	2 Sept →
mirage	14–16	-0.06	12%	2 Sept →
dust2	13–7	-0.05	24%	30 Aug →
overpass	5–13	-0.04	21%	30 Aug →
dust2	13–7	0.01	29%	29 Aug →
mirage	13–7	-0.02	20%	29 Aug →
inferno	7–13	-0.07	21%	29 Aug →
mirage	7–13	-0.02	12%	29 Aug →
inferno	11–13	-0.04	17%	29 Aug →
anubis	11–13	-0.02	11%	29 Aug →
ancient	9–13	-0.04	17%	28 Aug →
mirage	9–13	-0.04	11%	28 Aug →
dust2	11–13	-0.05	22%	28 Aug →
dust2	13–5	0.02	18%	27 Aug →
ancient	12–12	-0.02	14%	26 Aug →
mirage	13–2	0.08	28%	20 Aug →
inferno	5–13	-0.08	19%	20 Aug →
dust2	13–9	-0.00	15%	18 Aug →
inferno	10–13	-0.02	25%	18 Aug →
train	10–13	-0.08	13%	17 Aug →
dust2	10–13	0.01	33%	17 Aug →
mirage	13–3	0.01	13%	16 Aug →
inferno	7–13	-0.03	20%	14 Aug →
dust2	13–6	-0.02	3%	14 Aug →
train	13–3	0.06	40%	12 Aug →
inferno	13–9	-0.01	15%	11 Aug →
inferno	6–13	-0.04	31%	11 Aug →
dust2	2–6	0.04	23%	11 Aug →
mirage	1–13	-0.04	29%	11 Aug →
dust2	13–5	-0.02	21%	10 Aug →
mirage	1–13	-0.09	22%	10 Aug →