🚮WASTEMAN🚮 — CS2 Stats

GB76561198767662294[U:1:807396566]Steam profile ↗✓ No bans

947Tracked matches57%Win rate2025Tracked since

1,016Hours in CS28Hrs last 2 wks

CSDB Rating5.3 DevelopingPositional Player

Premier CS Rating3,585Grey band · top ~84.8% of ranked players (population est.)

CSDB Leaderboard#205372 of 258630 tracked

FaceitLevel 5 · 764 ELOTop 67.6% of ranked FACEIT players

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 22 Oct 2026 (7 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: 3,585 -6 8 Sept – 22 Oct · 12 days played

3,779Peak Premier in tracked matches

764Highest Faceit ELO seen on CSDB

41Days played since 2026-07-31

Faceit ELO

At peak — 764
Next: Level 4 at 901 — 137 to go
Reached: Level 3 · Level 2

Premier CS Rating

194 below peak (3,779)
+261 over 30 days · steady
Next: Light Blue band at 5,000 — 1,415 to go

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 5 among CSDB-tracked players (n=14,283), 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 5 median	Level 6 median	vs Level 6
Headshot rate	49.7%	43.8%	44.8%	above
Shot accuracy	0.0%	12.0%	12.4%	12.4% short
Kill/death ratio	0.90	1.02	1.03	0.13 short
Match win rate	46.2%	44.7%	45.2%	above

This profile matches the typical Level 6 player on 2 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 6 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim60

Positioning57

Utility56

0–100 skill scores via Leetify.

Recent form

STEADY50–47–3Last 10050%Win rateTWWLWLWWWL

Last 10 vs previous 10: −10pp win rate · +0.02 avg rating · +6.9pp headshot accuracy · −22ms reaction

Win rate −10pp 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

3–1–1 · 60% win rate
Avg rating 0.02
Avg headshot accuracy 32%
Avg reaction 653ms

Last 10

6–3–1 · 60% win rate
Avg rating 0.01
Avg headshot accuracy 24%
Avg reaction 616ms

Last 20

13–6–1 · 65% win rate
Avg rating 0.00
Avg headshot accuracy 20%
Avg reaction 627ms

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 against its own average).

Aim6.0

Utility5.6

Positioning5.7

Opening Duels4.1

Clutch3.4

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 84% 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

Reaction time. 619ms 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

Positioning5.7

Utility5.6

Mechanics5.8

Opening Duels5.4

Win Impact7.4

Composite 5.3/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01+0.02

first ⅓ avg -0.01 → last ⅓ avg 0.01

Reaction time616ms−68ms

first ⅓ avg 684ms → last ⅓ avg 616ms

Headshot accuracy18.0%−7.9%

first ⅓ avg 25.9% → last ⅓ avg 18.0%

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.

Personal bests

0.14Best match rating · 10–13 · dust2, 18 Sept →

75%Best headshot accuracy · 12–12 · shelter, 31 Jul →

438msFastest reaction time · 6–13 · inferno, 1 Oct →

13–0Biggest win · mirage, 31 Jul →

Across the last 100 tracked matches.

Highlights

5Longest win streak

5–3In matches decided by ≤2 rounds

7Overtime games

Map breakdown

dust2Best map · 70% over 23infernoWeakest map · 0% over 5

Map	Grade	Played	Record	Win rate	Avg rating
dust2	S	23	16–7	70%	0.01
nuke	B	17	9–8	53%	-0.01
mirage	C	16	7–9	44%	-0.00
cache	A	12	7–5	58%	0.02
ancient	D	12	4–8	33%	-0.01
anubis	A	11	6–5	55%	0.01
inferno	D	5	0–5	0%	-0.02
overpass	—	3	1–2	33%	-0.01
shelter	—	1	0–1	0%	0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (0% over 5). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

20,689Lifetime kills

0.90K/D

1,376Matches

46.2%Match win rate · Top 50% of Level 5 players

49.7%Headshot % · Top 25% of Level 5 players

0.0%Shot accuracy

2,742MVPs

729Hours (in match)

1,754Bombs planted

424Bombs defused

Most-used weapons

AK-476,578

M4A4 / M4A1-S5,682

Galil AR1,809

P2000 / USP-S1,166

FAMAS1,063

Desert Eagle1,022

Knife798

Glock-18709

AWP452

HE Grenade397

Lifetime map wins

3,712dust2

2,464nuke

318inferno

151train

58vertigo

35office

19lake

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

Faceit stats

Combat

789Matches

50%Win rate

0.96Avg K/D

77.0ADR

50%Headshot %

Clutches & streaks

37%1v1 clutch win

21%1v2 clutch win

9Longest win streak

Recent Faceit resultsLLWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	206	51%	0.99	15.4
Anubis	162	51%	0.93	14.7
Nuke	124	49%	0.96	14.9
Ancient	117	50%	0.93	14.2
Mirage	89	42%	0.89	14.4
Cache	54	56%	1.04	15.0
Overpass	17	71%	1.19	16.9
Inferno	16	31%	0.91	12.4

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.

17.9%Headshot accuracy

34.7%Accuracy (enemy spotted)

34.5%Spray accuracy

75.9%Counter-strafing

10.4°Preaim

619msReaction time

58.2%T opening success

44.9%CT opening success

0.61Enemies flashed / flash

6.4%Flash assists

12.65HE damage / grenade

9.28Flashes / match

Recommended for you

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.

0% win rate across 5 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
overpass	12–12	-0.01	49%	24 Oct →
nuke	13–11	-0.02	31%	22 Oct →
cache	13–3	0.01	21%	17 Oct →
cache	7–13	0.03	18%	16 Oct →
ancient	13–8	0.07	42%	14 Oct →
anubis	4–13	-0.04	15%	14 Oct →
cache	13–6	0.07	13%	13 Oct →
anubis	19–15	0.06	17%	12 Oct →
dust2	13–10	-0.01	11%	12 Oct →
inferno	10–13	-0.01	18%	12 Oct →
ancient	13–8	-0.03	16%	12 Oct →
dust2	13–3	-0.05	18%	11 Oct →
anubis	11–13	0.02	21%	11 Oct →
overpass	13–9	0.02	25%	11 Oct →
dust2	13–6	0.09	19%	11 Oct →
mirage	24–28	-0.04	15%	11 Oct →
dust2	13–10	-0.03	14%	11 Oct →
nuke	13–4	0.01	5%	11 Oct →
dust2	19–16	-0.01	15%	10 Oct →
ancient	8–13	-0.06	20%	9 Oct →
ancient	13–9	0.08	16%	9 Oct →
nuke	10–13	0.01	13%	9 Oct →
overpass	11–13	-0.02	24%	8 Oct →
dust2	12–12	0.04	18%	8 Oct →
mirage	8–13	-0.02	14%	8 Oct →
dust2	13–9	0.05	11%	8 Oct →
dust2	13–6	0.00	11%	8 Oct →
mirage	8–13	-0.04	3%	8 Oct →
cache	2–13	-0.06	9%	8 Oct →
cache	7–13	0.02	11%	7 Oct →
nuke	13–4	-0.00	15%	7 Oct →
anubis	13–5	0.10	27%	7 Oct →
mirage	10–13	0.11	22%	7 Oct →
dust2	8–13	-0.03	17%	7 Oct →
mirage	6–13	-0.04	11%	6 Oct →
nuke	8–13	-0.01	26%	6 Oct →
inferno	14–16	-0.01	22%	6 Oct →
mirage	13–8	0.05	16%	6 Oct →
mirage	5–13	-0.03	20%	5 Oct →
nuke	8–13	-0.06	22%	5 Oct →
dust2	6–13	-0.04	16%	5 Oct →
anubis	13–11	-0.04	23%	5 Oct →
cache	13–4	-0.01	11%	5 Oct →
dust2	16–14	0.02	22%	5 Oct →
inferno	6–13	-0.01	21%	1 Oct →
dust2	13–10	-0.04	21%	30 Sept →
nuke	16–12	0.01	16%	29 Sept →
cache	13–3	0.08	21%	29 Sept →
dust2	13–8	-0.04	16%	28 Sept →
mirage	6–13	-0.04	13%	28 Sept →
dust2	13–10	0.01	17%	26 Sept →
nuke	13–7	0.06	25%	26 Sept →
cache	13–4	0.09	19%	26 Sept →
ancient	13–9	0.08	19%	26 Sept →
nuke	9–13	-0.02	19%	26 Sept →
inferno	10–13	-0.03	28%	26 Sept →
ancient	6–13	-0.02	21%	25 Sept →
dust2	13–11	0.02	21%	24 Sept →
anubis	13–7	0.02	21%	24 Sept →
mirage	16–14	0.00	15%	23 Sept →
ancient	10–13	0.01	18%	22 Sept →
dust2	13–5	0.05	22%	22 Sept →
nuke	9–13	0.04	22%	22 Sept →
dust2	13–6	0.04	32%	21 Sept →
ancient	6–13	-0.14	13%	21 Sept →
ancient	7–13	0.08	24%	20 Sept →
dust2	2–13	0.03	20%	20 Sept →
mirage	13–5	0.02	29%	19 Sept →
anubis	9–13	-0.04	19%	19 Sept →
nuke	13–8	-0.06	20%	19 Sept →
nuke	13–5	0.02	19%	19 Sept →
cache	13–4	-0.05	42%	18 Sept →
mirage	9–13	-0.04	33%	18 Sept →
mirage	5–0	0.10	26%	18 Sept →
nuke	5–13	-0.05	16%	18 Sept →
ancient	4–13	-0.04	26%	18 Sept →
dust2	10–13	0.14	19%	18 Sept →
cache	9–13	-0.03	22%	17 Sept →
dust2	7–13	0.02	20%	17 Sept →
dust2	9–13	-0.01	23%	16 Sept →
nuke	8–13	-0.03	18%	16 Sept →
mirage	9–13	-0.03	23%	15 Sept →
ancient	4–13	-0.10	12%	14 Sept →
nuke	6–13	-0.09	15%	8 Sept →
anubis	4–13	0.02	24%	8 Sept →
dust2	13–4	0.08	19%	8 Sept →
anubis	4–13	-0.03	16%	7 Sept →
cache	4–13	-0.00	18%	4 Sept →
mirage	13–9	-0.02	17%	25 Aug →
cache	13–2	0.05	35%	24 Aug →
ancient	10–13	-0.01	22%	23 Aug →
anubis	13–8	0.04	14%	17 Aug →
mirage	13–6	-0.08	12%	8 Aug →
nuke	13–9	0.01	24%	1 Aug →
anubis	13–1	0.04	24%	1 Aug →
nuke	13–10	-0.06	21%	1 Aug →
inferno	3–13	-0.05	63%	31 Jul →
mirage	13–0	0.02	42%	31 Jul →
dust2	13–6	-0.03	48%	31 Jul →
shelter	12–12	0.03	75%	31 Jul →