beebz ッ — CS2 Stats

76561198061019304[U:1:100753576]✓ No bans

2,056Tracked matches39%Win rate2023Tracked since

2,161Hours in CS15Hrs last 2 wks

CSDB Rating4.8 DevelopingPassive Rifler

Premier CS Rating15,395Purple band · top ~26.8% of ranked players (population est.)

CSDB Leaderboard#6841 of 10688 tracked

FaceitLevel 6Top 54.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim60

Positioning43

Utility54

0–100 skill scores via Leetify.

Recent form

COLD45–50–5Last 10045%Win rateLLWLWLLTWL

Last 10 vs previous 10: +0pp win rate · +0.02 avg rating

Player DNA

Primary style: Passive Rifler — Aim-led profile without a single dominant tendency.

Aim6.0

Aggression3.8

Utility5.4

Positioning4.3

Opening Duels0.1

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

Plays most like NiKo 82% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

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

Reaction time. 660ms 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

Aim6.0

Positioning4.3

Utility5.4

Mechanics7.5

Opening Duels0.2

Win Impact1.4

Composite 4.8/10 (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-0.03−0.00

first ⅓ avg -0.03 → last ⅓ avg -0.03

Reaction time661ms−61ms

first ⅓ avg 722ms → last ⅓ avg 661ms

Headshot accuracy15.0%−0.8%

first ⅓ avg 15.8% → last ⅓ avg 15.0%

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.

Highlights

0.10Best rating — cache 13–6

13–0Biggest win — mirage

5Longest win streak

L2Current streak

5–3In matches decided by ≤2 rounds

6Overtime games

Map breakdown

anubisBest map · 55% over 11infernoWeakest map · 29% over 7

Map	Grade	Played	Record	Win rate	Avg rating
mirage	B	30	16–14	53%	-0.04
dust2	B	22	10–12	45%	-0.02
cache	D	13	4–9	31%	-0.01
anubis	A	11	6–5	55%	-0.02
inferno	D	7	2–5	29%	-0.05
nuke	B	6	3–3	50%	-0.03
ancient	D	6	2–4	33%	-0.03
train	—	3	1–2	33%	-0.02
overpass	—	1	1–0	100%	0.01
vertigo	—	1	0–1	0%	-0.07

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

44,588Lifetime kills

0.86K/D

3,071Matches

43.9%Match win rate

40.2%Headshot %

10.2%Shot accuracy

4,502MVPs

1,310Hours (in match)

5,285Bombs planted

651Bombs defused

Most-used weapons

AK-4717,900

M4A4 / M4A1-S8,119

AWP4,385

P2000 / USP-S2,688

FAMAS1,615

Glock-181,605

Galil AR1,505

Desert Eagle1,412

SSG 08899

Five-SeveN665

Lifetime map wins

4,586inferno

3,964dust2

1,993nuke

1,268vertigo

1,240train

442cbble

53office

19dust

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

Faceit stats

Combat

35Matches

54%Win rate

0.82Avg K/D

—ADR

35%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

4Longest win streak

Recent Faceit resultsLWLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Vertigo	4	75%	0.67	11.0
Overpass	3	0%	0.70	17.3
Mirage	3	67%	0.75	11.0
Nuke	2	0%	0.86	15.5
Anubis	2	100%	0.71	11.0
Inferno	1	0%	0.53	9.0
Ancient	1	0%	0.38	5.0

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.

14.8%Headshot accuracy

35.0%Accuracy (enemy spotted)

35.7%Spray accuracy

83.6%Counter-strafing

10.3°Preaim

660msReaction time

31.3%T opening success

29.8%CT opening success

0.64Enemies flashed / flash

10.2%Flash assists

6.58HE damage / grenade

6.77Flashes / 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.

Best CS2 Crosshair
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 14.8258% — below the 15% mark we flag
Aim Training →
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 31.2697% — 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.

29% win rate across 7 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	6–13	-0.04	29%	27 Aug →
mirage	4–13	-0.08	14%	27 Aug →
mirage	13–9	-0.04	12%	25 Aug →
dust2	9–13	-0.05	11%	25 Aug →
mirage	13–8	0.01	20%	22 Aug →
nuke	3–13	-0.06	13%	22 Aug →
anubis	5–13	0.01	17%	22 Aug →
ancient	12–12	0.01	11%	22 Aug →
cache	13–6	0.10	19%	22 Aug →
mirage	10–13	-0.00	14%	22 Aug →
dust2	7–13	-0.07	29%	22 Aug →
dust2	13–7	-0.02	14%	19 Aug →
anubis	8–13	0.02	6%	19 Aug →
cache	5–13	-0.02	16%	19 Aug →
mirage	6–13	0.00	13%	19 Aug →
anubis	13–5	-0.03	14%	19 Aug →
dust2	8–13	-0.09	18%	19 Aug →
mirage	13–9	-0.04	10%	15 Aug →
mirage	4–13	-0.13	17%	15 Aug →
dust2	15–15	0.01	18%	15 Aug →
mirage	13–6	0.03	13%	15 Aug →
ancient	7–13	-0.07	13%	15 Aug →
mirage	9–13	-0.03	11%	15 Aug →
dust2	9–4	-0.02	10%	15 Aug →
cache	13–8	-0.00	10%	11 Aug →
nuke	10–13	0.02	15%	11 Aug →
mirage	13–11	-0.04	15%	11 Aug →
inferno	2–13	-0.09	13%	11 Aug →
dust2	13–8	-0.05	13%	11 Aug →
mirage	11–13	-0.02	18%	11 Aug →
dust2	13–9	-0.02	20%	3 Aug →
anubis	4–13	-0.00	18%	3 Aug →
inferno	6–13	-0.06	12%	3 Aug →
overpass	13–8	0.01	18%	3 Aug →
dust2	6–13	0.04	15%	3 Aug →
vertigo	5–13	-0.07	14%	3 Aug →
anubis	13–4	0.04	4%	30 Jul →
mirage	10–13	-0.04	13%	30 Jul →
dust2	13–3	-0.01	28%	30 Jul →
inferno	13–9	-0.03	13%	30 Jul →
dust2	13–11	-0.04	17%	30 Jul →
cache	7–13	-0.05	9%	30 Jul →
cache	4–13	0.02	16%	28 Jul →
cache	16–13	0.02	9%	28 Jul →
dust2	16–13	-0.03	24%	28 Jul →
inferno	6–13	-0.06	8%	28 Jul →
dust2	8–13	-0.07	18%	28 Jul →
mirage	13–3	-0.00	3%	23 Jul →
dust2	16–14	-0.04	13%	23 Jul →
cache	12–16	-0.07	13%	23 Jul →
dust2	0–13	-0.02	50%	23 Jul →
nuke	13–10	-0.11	7%	23 Jul →
mirage	9–13	-0.06	7%	23 Jul →
mirage	13–4	-0.06	17%	21 Jul →
mirage	13–8	-0.01	15%	21 Jul →
nuke	13–5	-0.04	15%	21 Jul →
inferno	13–10	-0.03	16%	21 Jul →
mirage	13–0	-0.06	14%	21 Jul →
ancient	12–12	0.02	17%	21 Jul →
anubis	8–13	-0.04	10%	16 Jul →
mirage	13–10	-0.01	17%	16 Jul →
dust2	4–13	-0.01	15%	16 Jul →
mirage	3–13	-0.04	8%	16 Jul →
dust2	13–11	-0.02	24%	16 Jul →
inferno	2–13	-0.06	9%	13 Jul →
nuke	6–13	-0.01	30%	13 Jul →
train	6–13	-0.04	20%	13 Jul →
cache	8–13	-0.01	21%	13 Jul →
ancient	8–13	-0.05	12%	13 Jul →
mirage	13–2	-0.07	7%	13 Jul →
cache	10–13	-0.01	20%	13 Jul →
mirage	13–7	-0.07	7%	9 Jul →
ancient	13–6	-0.05	7%	9 Jul →
mirage	11–13	0.04	19%	9 Jul →
anubis	13–7	-0.01	13%	9 Jul →
cache	8–13	-0.05	6%	9 Jul →
dust2	6–13	-0.01	12%	9 Jul →
mirage	9–4	-0.08	11%	9 Jul →
nuke	6–1	0.05	11%	25 Jun →
cache	12–12	-0.04	13%	25 Jun →
mirage	7–13	-0.06	6%	25 Jun →
dust2	6–13	-0.05	12%	25 Jun →
anubis	3–13	-0.09	33%	25 Jun →
mirage	8–13	-0.02	34%	25 Jun →
mirage	14–16	-0.05	15%	23 Jun →
dust2	13–6	0.08	18%	22 Jun →
mirage	13–0	0.01	8%	22 Jun →
anubis	13–10	-0.05	15%	22 Jun →
cache	4–13	-0.06	21%	22 Jun →
mirage	13–9	-0.01	14%	22 Jun →
dust2	3–13	-0.00	22%	18 Jun →
cache	13–11	0.04	15%	18 Jun →
ancient	13–6	-0.04	12%	18 Jun →
anubis	13–7	-0.03	23%	18 Jun →
inferno	12–12	-0.03	36%	18 Jun →
train	6–13	-0.06	16%	18 Jun →
mirage	13–8	-0.02	27%	18 Jun →
mirage	3–13	-0.11	4%	11 Jun →
anubis	9–6	0.01	17%	11 Jun →
train	9–0	0.05	13%	11 Jun →