Beah⭒˚.⋆𓃠 — CS2 Stats

76561198290328047[U:1:330062319]Steam profile ↗✓ No bans

1,029Tracked matches53%Win rate2020Tracked since

CSDB Rating6.5 SolidPositional Player

Premier CS Rating22,293Top 50% of 213,211 CSDB-tracked playersPink band · top ~6% of ranked players (population est.)

CSDB Leaderboard#52718 of 259892 tracked

FaceitLevel 9Top 20.7% of ranked FACEIT players

WingmanGold Nova Master

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 30 Oct 2026 (5 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: 22,293 -2,605 3 Sept – 30 Oct · 12 days played

25,789Peak Premier in tracked matches

42Days played since 2026-07-22

Premier CS Rating

3,496 below peak (25,789)
-2,811 over 30 days · declining
Next: Red band at 25,000 — 2,707 to go
Reached: Red band · Pink band · Purple band · Blue band
Red band first seen 2026-09-21
Pink band first seen 2026-09-09

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

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Performance scores

Aim80

Positioning57

Utility35

0–100 skill scores via Leetify.

Recent form

COLD55–43–2Last 10055%Win rateLLLLLLLLLL

Last 10 vs previous 10: −80pp win rate · −0.03 avg rating · −0.8pp headshot accuracy · −49ms reaction

Win rate down 80pp 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 -0.05
Avg headshot accuracy 18%
Avg reaction 550ms

Last 10

0–10 · 0% win rate
Avg rating -0.04
Avg headshot accuracy 21%
Avg reaction 551ms

Last 20

8–12 · 40% win rate
Avg rating -0.03
Avg headshot accuracy 21%
Avg reaction 576ms

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 (+1.9 against its own average).

Aim8.0

Utility3.5

Positioning5.7

Opening Duels3.4

Clutch2.8

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 91% playstyle similarity

Most alike: aim profile, positioning profile.

Where you differ: lower utility contribution; lower opening-duel success.

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. 589ms 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

Aim8.0

Positioning5.7

Utility3.5

Mechanics8.0

Opening Duels5.0

Win Impact6.1

Composite 6.5/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02+0.00

first ⅓ avg -0.02 → last ⅓ avg -0.02

Reaction time568ms−10ms

first ⅓ avg 578ms → last ⅓ avg 568ms

Headshot accuracy23.1%+0.8%

first ⅓ avg 22.3% → last ⅓ avg 23.1%

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

0.10Best match rating · 12–2 · dust2, 27 Sept →

50%Best headshot accuracy · 0–13 · ancient, 20 Sept →

391msFastest reaction time · 13–11 · ancient, 6 Sept →

13–1Biggest win · dust2, 27 Sept →

Across the last 100 tracked matches.

Highlights

7Longest win streak

L10Current streak

14–6In matches decided by ≤2 rounds

11Overtime games

Map breakdown

ancientBest map · 83% over 6infernoWeakest map · 33% over 6

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	42	20–22	48%	-0.01
mirage	S	23	15–8	65%	-0.03
anubis	S	12	8–4	67%	-0.02
inferno	D	6	2–4	33%	-0.04
ancient	S	6	5–1	83%	-0.04
nuke	—	4	1–3	25%	-0.03
cache	—	3	2–1	67%	-0.02
vertigo	—	2	1–1	50%	-0.04
office	—	1	0–1	0%	-0.01
overpass	—	1	1–0	100%	-0.01

Across the last 100 tracked matches.

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

Faceit stats

Combat

764Matches

55%Win rate

0.93Avg K/D

68.9ADR

50%Headshot %

Clutches & streaks

34%1v1 clutch win

14%1v2 clutch win

14Longest win streak

Recent Faceit resultsLLWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	140	49%	0.86	12.6
Dust2	126	54%	0.84	13.2
Anubis	50	50%	0.90	13.9
Ancient	23	39%	0.88	13.9
Inferno	15	40%	0.77	13.0
Nuke	12	50%	0.79	13.5
Train	10	50%	0.96	16.3
Overpass	6	33%	0.75	16.0

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.

22.9%Headshot accuracy

35.0%Accuracy (enemy spotted)

35.8%Spray accuracy

86.1%Counter-strafing

9.3°Preaim

589msReaction time

49.8%T opening success

50.2%CT opening success

0.47Enemies flashed / flash

2.6%Flash assists

9.04HE damage / grenade

5.84Flashes / 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 0.4708 — below the 0.5 mark we flag
Grenade Lineups →

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 6 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
dust2	11–13	-0.03	16%	30 Oct →
mirage	4–13	-0.11	18%	30 Oct →
vertigo	6–9	-0.08	18%	25 Oct →
dust2	7–13	-0.01	14%	18 Oct →
dust2	10–13	-0.00	22%	18 Oct →
anubis	9–13	0.01	23%	18 Oct →
nuke	5–13	-0.00	23%	18 Oct →
inferno	8–13	-0.07	3%	18 Oct →
dust2	5–13	-0.07	38%	18 Oct →
inferno	9–13	-0.06	31%	12 Oct →
dust2	13–5	0.00	22%	12 Oct →
mirage	13–7	0.02	25%	12 Oct →
dust2	13–11	-0.01	23%	12 Oct →
nuke	6–13	-0.07	27%	11 Oct →
mirage	19–17	-0.04	20%	8 Oct →
anubis	13–8	-0.03	26%	8 Oct →
ancient	16–14	-0.05	14%	7 Oct →
anubis	5–13	-0.06	16%	7 Oct →
mirage	13–4	0.03	16%	28 Sept →
anubis	13–5	0.05	24%	28 Sept →
dust2	13–2	0.02	30%	27 Sept →
dust2	12–2	0.10	44%	27 Sept →
cache	13–11	-0.01	25%	27 Sept →
anubis	13–10	-0.02	18%	27 Sept →
dust2	13–1	0.02	41%	27 Sept →
dust2	0–4	-0.00	0%	22 Sept →
anubis	5–13	-0.05	20%	22 Sept →
dust2	13–11	-0.02	29%	20 Sept →
cache	13–4	0.02	19%	20 Sept →
ancient	0–13	-0.07	50%	20 Sept →
dust2	13–6	-0.01	18%	20 Sept →
mirage	10–13	-0.02	21%	18 Sept →
mirage	26–28	-0.04	30%	15 Sept →
inferno	6–13	-0.04	13%	15 Sept →
ancient	13–11	-0.03	24%	15 Sept →
inferno	13–9	-0.02	13%	14 Sept →
dust2	8–13	0.02	30%	13 Sept →
cache	4–13	-0.06	16%	13 Sept →
dust2	8–13	-0.07	27%	12 Sept →
nuke	13–11	-0.03	8%	11 Sept →
mirage	10–13	-0.06	20%	10 Sept →
dust2	13–8	0.01	20%	10 Sept →
dust2	5–13	-0.05	22%	7 Sept →
mirage	9–13	0.09	33%	7 Sept →
ancient	13–11	-0.04	21%	6 Sept →
inferno	13–10	-0.06	21%	6 Sept →
office	3–13	-0.01	18%	6 Sept →
inferno	7–13	-0.01	24%	6 Sept →
dust2	12–12	0.01	24%	6 Sept →
dust2	5–13	-0.13	19%	6 Sept →
dust2	10–13	-0.00	26%	6 Sept →
dust2	13–10	0.01	27%	4 Sept →
anubis	13–9	-0.02	20%	4 Sept →
anubis	19–16	0.02	15%	4 Sept →
mirage	13–5	-0.01	19%	4 Sept →
dust2	12–16	-0.01	27%	3 Sept →
dust2	13–4	0.06	24%	3 Sept →
dust2	13–8	0.07	41%	2 Sept →
mirage	11–13	0.01	38%	1 Sept →
dust2	9–13	-0.05	13%	31 Aug →
dust2	1–13	-0.07	16%	30 Aug →
dust2	11–13	-0.08	18%	30 Aug →
anubis	13–9	-0.04	31%	30 Aug →
overpass	19–17	-0.01	25%	30 Aug →
mirage	13–6	-0.03	22%	30 Aug →
ancient	13–9	-0.03	13%	30 Aug →
dust2	13–10	-0.08	25%	28 Aug →
nuke	8–13	-0.01	45%	27 Aug →
mirage	13–8	-0.01	30%	27 Aug →
mirage	13–6	-0.00	20%	27 Aug →
anubis	11–13	-0.07	12%	27 Aug →
dust2	13–5	0.00	26%	25 Aug →
dust2	13–4	-0.03	22%	25 Aug →
mirage	10–13	-0.03	14%	24 Aug →
vertigo	16–12	0.00	14%	24 Aug →
mirage	13–5	-0.06	27%	24 Aug →
dust2	12–12	0.00	17%	23 Aug →
mirage	13–6	-0.09	18%	23 Aug →
dust2	13–5	0.01	30%	23 Aug →
dust2	13–7	0.01	18%	23 Aug →
dust2	8–13	-0.02	17%	20 Aug →
dust2	7–13	-0.04	28%	14 Aug →
mirage	16–13	-0.06	26%	10 Aug →
ancient	13–8	-0.04	20%	5 Aug →
mirage	5–13	-0.03	31%	5 Aug →
mirage	16–14	-0.07	20%	5 Aug →
dust2	3–9	-0.04	19%	2 Aug →
dust2	13–3	0.06	26%	2 Aug →
dust2	8–13	-0.00	14%	2 Aug →
mirage	13–11	-0.07	18%	31 Jul →
anubis	16–14	-0.03	17%	31 Jul →
anubis	13–6	-0.03	34%	30 Jul →
dust2	13–10	-0.08	29%	30 Jul →
mirage	13–11	0.00	29%	30 Jul →
dust2	8–13	-0.07	25%	28 Jul →
dust2	13–4	-0.00	19%	25 Jul →
mirage	13–10	0.01	20%	25 Jul →
dust2	11–13	0.00	14%	24 Jul →
dust2	16–13	-0.02	17%	22 Jul →
mirage	13–11	-0.00	22%	22 Jul →