Shame — CS2 Stats

US76561197967439921[U:1:7174193]Steam profile ↗✓ No bans

136Tracked matches29%Win rate2025Tracked since

154Hours in CS1Hrs last 2 wks

CSDB Rating4.1 DevelopingPassive Rifler

Ladder ranks via Leetify

Performance scores

Aim64

Positioning38

Utility18

0–100 skill scores via Leetify.

Recent form

STEADY28–67–5Last 10028%Win rateLTLLWLWLWW

Last 10 vs previous 10: +10pp win rate · -0.00 avg rating

Player DNA

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

Aim6.4

Aggression4.0

Utility1.8

Positioning3.8

Opening Duels1.4

Limited utility dependence

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 78% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

Where you differ: lower aim profile; lower utility contribution.

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. 672ms 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

Aim6.4

Positioning3.8

Utility1.8

Mechanics6.9

Opening Duels1.4

Win Impact0.0

Composite 4.1/10 (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 rating0.00+0.02

first ⅓ avg -0.02 → last ⅓ avg 0.00

Reaction time688ms+4ms

first ⅓ avg 684ms → last ⅓ avg 688ms

Headshot accuracy12.3%−1.0%

first ⅓ avg 13.3% → last ⅓ avg 12.3%

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

0.22Best rating — ancient 13–3

13–3Biggest win — nuke

3Longest win streak

2–7In matches decided by ≤2 rounds

8Overtime games

Map breakdown

nukeBest map · 38% over 16infernoWeakest map · 14% over 7

Map	Grade	Played	Record	Win rate	Avg rating
dust2	D	30	10–20	33%	-0.02
mirage	D	20	5–15	25%	-0.00
nuke	C	16	6–10	38%	-0.02
ancient	D	13	3–10	23%	-0.01
overpass	D	11	3–8	27%	-0.01
inferno	D	7	1–6	14%	-0.02
cache	—	1	0–1	0%	0.03
train	—	1	0–1	0%	-0.04
anubis	—	1	0–1	0%	0.00

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (14% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

5,943Lifetime kills

0.95K/D

240Matches

26.3%Match win rate

33.7%Headshot %

13.9%Shot accuracy · Top 50% of tracked players

509MVPs

81Hours (in match)

156Bombs planted

30Bombs defused

Most-used weapons

M4A4 / M4A1-S1,022

AK-47871

Glock-18424

P2000 / USP-S238

SG 553235

AWP230

AUG206

Knife181

P90159

MP7158

Lifetime map wins

426dust2

212nuke

105inferno

44ar_monastery

19ar_shoots

16train

14ar_baggage

10office

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

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

12.7%Headshot accuracy

39.1%Accuracy (enemy spotted)

37.1%Spray accuracy

81.1%Counter-strafing

9.3°Preaim

672msReaction time

36.9%T opening success

34.0%CT opening success

0.30Enemies flashed / flash

5.2%Flash assists

9.49HE damage / grenade

0.86Flashes / 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 12.7413% — below the 15% mark we flag
Aim Training →
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 0.2985 — below the 0.5 mark we flag
Grenade Lineups →
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 36.8893% — 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.

14% 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	8–13	-0.05	9%	18 Aug →
mirage	12–12	0.01	13%	18 Aug →
dust2	5–13	-0.04	16%	15 Aug →
dust2	8–13	0.02	13%	9 Aug →
inferno	13–6	0.01	21%	1 Aug →
ancient	7–13	-0.01	2%	15 Jul →
mirage	13–4	-0.00	11%	30 Jun →
mirage	7–13	-0.02	13%	22 Jun →
mirage	13–4	0.08	9%	14 Jun →
dust2	13–11	0.05	13%	14 Jun →
mirage	5–13	-0.07	5%	10 Jun →
dust2	15–15	-0.02	9%	9 Jun →
nuke	13–3	0.04	5%	9 Jun →
dust2	13–4	0.04	9%	9 Jun →
ancient	13–3	0.22	16%	9 Jun →
nuke	6–13	-0.07	14%	9 Jun →
mirage	14–16	0.03	13%	8 Jun →
dust2	8–13	-0.01	20%	8 Jun →
overpass	0–8	-0.06	4%	7 Jun →
nuke	7–13	-0.01	2%	7 Jun →
mirage	14–16	0.06	13%	7 Jun →
nuke	8–13	-0.01	18%	6 Jun →
dust2	8–13	-0.01	31%	5 Jun →
ancient	4–13	-0.09	9%	5 Jun →
cache	3–13	0.03	14%	26 May →
train	4–13	-0.04	9%	26 May →
nuke	13–6	0.05	22%	26 May →
overpass	8–13	-0.04	14%	19 May →
inferno	3–13	0.01	11%	23 Apr →
nuke	7–13	0.02	8%	10 Apr →
dust2	14–16	0.03	13%	2 Apr →
mirage	4–13	-0.06	9%	27 Mar →
dust2	3–13	-0.06	16%	27 Mar →
overpass	5–13	0.06	10%	23 Mar →
dust2	13–7	-0.08	3%	20 Mar →
ancient	8–13	-0.04	9%	19 Mar →
dust2	9–13	-0.01	19%	19 Mar →
anubis	0–2	0.00	0%	19 Mar →
dust2	12–12	-0.02	12%	16 Mar →
mirage	12–12	-0.01	5%	16 Mar →
inferno	2–13	-0.14	11%	9 Mar →
dust2	13–7	-0.06	16%	9 Mar →
mirage	6–13	0.03	20%	2 Mar →
mirage	6–13	-0.08	15%	2 Mar →
mirage	13–8	0.01	13%	23 Feb →
mirage	6–13	-0.02	11%	21 Feb →
nuke	13–7	-0.01	11%	21 Feb →
nuke	10–13	-0.04	11%	15 Feb →
nuke	13–6	0.02	6%	15 Feb →
dust2	7–13	-0.03	13%	12 Feb →
ancient	10–13	-0.06	18%	11 Feb →
mirage	13–6	0.02	10%	8 Feb →
dust2	7–13	0.01	11%	6 Feb →
dust2	13–4	-0.08	4%	6 Feb →
nuke	7–13	-0.00	3%	6 Feb →
dust2	13–10	-0.04	8%	3 Feb →
nuke	13–10	-0.03	10%	2 Feb →
ancient	13–5	0.03	4%	2 Feb →
dust2	1–13	0.01	17%	1 Feb →
mirage	6–13	-0.06	3%	1 Feb →
overpass	13–4	0.01	11%	31 Jan →
ancient	15–15	-0.02	10%	30 Jan →
ancient	3–13	-0.06	11%	30 Jan →
overpass	13–4	-0.02	18%	30 Jan →
mirage	10–13	0.05	11%	20 Jan →
dust2	13–9	-0.02	15%	14 Jan →
dust2	3–13	-0.09	20%	14 Jan →
ancient	3–13	-0.04	14%	11 Jan →
ancient	4–13	-0.05	9%	9 Jan →
dust2	8–13	-0.02	13%	9 Jan →
dust2	10–13	-0.05	20%	8 Jan →
overpass	7–13	-0.08	9%	7 Jan →
mirage	13–8	-0.02	19%	6 Jan →
ancient	9–13	-0.03	22%	6 Jan →
dust2	16–13	-0.01	9%	4 Jan →
dust2	13–8	0.05	15%	4 Jan →
nuke	13–11	0.04	12%	3 Jan →
dust2	6–13	-0.02	18%	2 Jan →
dust2	13–16	-0.03	4%	2 Jan →
nuke	11–13	-0.09	23%	31 Dec →
dust2	3–13	-0.05	11%	31 Dec →
inferno	6–13	-0.02	17%	31 Dec →
mirage	6–13	0.05	16%	30 Dec →
overpass	7–13	0.09	19%	29 Dec →
dust2	13–4	0.01	11%	29 Dec →
inferno	5–13	0.02	12%	29 Dec →
nuke	9–13	-0.10	17%	21 Dec →
nuke	5–13	-0.02	19%	21 Dec →
nuke	12–16	-0.07	12%	21 Dec →
overpass	11–13	-0.08	18%	19 Dec →
mirage	7–13	-0.01	16%	19 Dec →
overpass	5–13	-0.00	13%	18 Dec →
ancient	11–13	-0.04	7%	18 Dec →
dust2	7–13	-0.06	6%	17 Dec →
overpass	4–13	-0.11	6%	17 Dec →
ancient	13–6	0.00	12%	15 Dec →
mirage	8–13	-0.00	13%	15 Dec →
inferno	6–13	-0.01	6%	8 Dec →
overpass	13–6	0.07	14%	8 Dec →
inferno	4–13	-0.00	10%	7 Dec →