Gottloser Bot — CS2 Stats

IE76561198040896527[U:1:80630799]Steam profile ↗

532Tracked matches37%Win rate2023Tracked since

2,308Hours in CS5Hrs last 2 wks

CSDB Rating4.7 DevelopingPassive Rifler

Premier CS Rating16,318Purple band · top ~23.2% of ranked players (population est.)

CSDB Leaderboard#30393 of 54833 tracked

Ladder ranks via Leetify

How this compares with the same rank

Median values for Purple band among CSDB-tracked players (n=5,002), 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	Purple band median	Pink band median	vs Pink band
Headshot rate	37.2%	44.2%	47.1%	9.9% short
Shot accuracy	20.6%	11.6%	12.8%	above
Kill/death ratio	1.34	1.03	1.08	above
Match win rate	49.5%	45.2%	46.6%	above

This profile matches the typical Pink band player on 3 of 4 comparable metrics.

Widest gap: Headshot rate. That is the metric furthest from the Pink band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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Performance scores

Aim72

Positioning37

Utility42

0–100 skill scores via Leetify.

Recent form

STEADY45–48–7Last 10045%Win rateLLLWWWWLLL

Last 10 vs previous 10: +0pp win rate · -0.00 avg rating

Player DNA

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

Aim7.2

Aggression4.0

Utility4.2

Positioning3.7

Opening Duels0.0

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-fight frequency, aim profile.

Where you differ: lower positioning profile; 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

Positioning. Positioning trails aim by 35 points — deaths here waste a strong aim profile.

Reaction time. 587ms 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

Aim7.2

Positioning3.7

Utility4.2

Mechanics7.1

Opening Duels0.1

Win Impact0.7

Composite 4.7/10 (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 rating0.01−0.04

first ⅓ avg 0.05 → last ⅓ avg 0.01

Reaction time532ms−43ms

first ⅓ avg 576ms → last ⅓ avg 532ms

Headshot accuracy14.6%+0.3%

first ⅓ avg 14.3% → last ⅓ avg 14.6%

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

0.20Best rating — nuke 3–0

13–1Biggest win — mirage

6Longest win streak

L3Current streak

3–10In matches decided by ≤2 rounds

5Overtime games

Map breakdown

nukeBest map · 65% over 17infernoWeakest map · 36% over 14

Map	Grade	Played	Record	Win rate	Avg rating
mirage	C	27	12–15	44%	0.02
dust2	C	21	9–12	43%	0.01
nuke	S	17	11–6	65%	0.05
inferno	C	14	5–9	36%	0.04
cache	B	13	7–6	54%	0.05
ancient	—	3	0–3	0%	-0.01
vertigo	—	2	1–1	50%	0.06
anubis	—	2	0–2	0%	0.00
office	—	1	0–1	0%	0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (36% over 14). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

62,643Lifetime kills

1.34K/D · Top 10% of Purple band

2,703Matches

49.5%Match win rate · Top 25% of Purple band

37.2%Headshot %

20.6%Shot accuracy · Top 5% of Purple band

8,227MVPs

1,061Hours (in match)

1,750Bombs planted

667Bombs defused

Most-used weapons

AK-4713,277

M4A4 / M4A1-S13,021

AWP6,442

SG 5533,284

P2000 / USP-S3,111

Desert Eagle2,112

MP72,038

AUG1,857

Five-SeveN1,598

P901,393

Lifetime map wins

5,871inferno

5,298dust2

2,930nuke

1,252cbble

730train

413vertigo

335office

111italy

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

Faceit stats

Combat

45Matches

44%Win rate

0.97Avg K/D

—ADR

40%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

2Longest win streak

Recent Faceit resultsWLLLW

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.

16.1%Headshot accuracy

35.9%Accuracy (enemy spotted)

36.9%Spray accuracy

82.1%Counter-strafing

9.5°Preaim

587msReaction time

29.3%T opening success

30.7%CT opening success

0.45Enemies flashed / flash

1.4%Flash assists

7.71HE damage / grenade

6.08Flashes / 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 0.4477 — 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 29.299% — 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.

36% win rate across 14 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
cache	9–13	0.02	20%	27 Aug →
cache	5–13	-0.06	8%	27 Aug →
cache	2–3	0.00	0%	23 Aug →
dust2	13–7	0.00	24%	23 Aug →
nuke	13–8	0.02	17%	23 Aug →
mirage	13–1	0.05	13%	23 Aug →
cache	13–8	-0.01	22%	23 Aug →
mirage	10–13	-0.04	11%	14 Aug →
cache	12–16	0.03	15%	14 Aug →
mirage	0–3	0.00	0%	12 Aug →
dust2	7–13	-0.02	23%	12 Aug →
inferno	11–13	-0.01	18%	12 Aug →
mirage	8–13	-0.07	18%	10 Aug →
inferno	11–13	-0.02	9%	10 Aug →
dust2	10–13	-0.01	22%	10 Aug →
mirage	2–9	0.04	24%	3 Aug →
dust2	16–13	0.03	25%	3 Aug →
nuke	10–3	0.06	7%	3 Aug →
dust2	13–10	0.06	14%	1 Aug →
inferno	16–13	0.00	10%	1 Aug →
dust2	8–13	0.04	20%	1 Aug →
mirage	12–12	-0.01	19%	1 Aug →
ancient	11–13	-0.07	11%	1 Aug →
vertigo	6–13	-0.02	10%	1 Aug →
inferno	13–4	0.08	12%	1 Aug →
nuke	12–12	-0.00	17%	31 Jul →
mirage	10–13	-0.01	19%	31 Jul →
nuke	13–9	-0.02	18%	31 Jul →
office	12–12	0.01	9%	31 Jul →
mirage	2–5	0.00	0%	30 Jul →
cache	13–4	0.12	18%	30 Jul →
dust2	13–7	-0.02	9%	30 Jul →
nuke	13–6	0.01	19%	30 Jul →
mirage	9–1	0.00	14%	30 Jul →
mirage	13–6	0.08	22%	30 Jul →
mirage	13–5	-0.01	12%	28 Jul →
nuke	14–16	0.06	20%	28 Jul →
dust2	7–13	0.00	0%	27 Jul →
dust2	2–13	0.00	0%	27 Jul →
dust2	5–13	-0.04	18%	26 Jul →
dust2	13–9	0.03	17%	26 Jul →
mirage	13–4	0.05	15%	26 Jul →
nuke	10–0	0.00	15%	26 Jul →
nuke	6–13	0.06	19%	26 Jul →
inferno	6–13	0.11	10%	26 Jul →
mirage	13–9	0.04	21%	26 Jul →
dust2	10–13	0.02	22%	25 Jul →
ancient	8–13	0.01	25%	25 Jul →
dust2	5–13	-0.05	13%	25 Jul →
cache	5–13	0.00	13%	25 Jul →
cache	13–11	0.05	14%	24 Jul →
nuke	13–7	0.08	17%	24 Jul →
mirage	12–12	0.04	16%	24 Jul →
cache	13–4	0.05	10%	24 Jul →
dust2	13–9	0.01	29%	24 Jul →
cache	13–6	0.16	18%	24 Jul →
inferno	0–13	-0.03	0%	24 Jul →
nuke	13–3	0.04	20%	24 Jul →
inferno	7–13	-0.02	16%	24 Jul →
inferno	13–5	0.20	21%	24 Jul →
mirage	15–15	0.04	9%	23 Jul →
dust2	12–12	0.13	23%	22 Jul →
cache	13–2	0.13	25%	22 Jul →
anubis	9–13	0.02	19%	22 Jul →
dust2	7–13	-0.01	13%	21 Jul →
mirage	4–13	0.12	12%	21 Jul →
inferno	10–13	0.02	14%	21 Jul →
nuke	9–13	0.07	21%	20 Jul →
mirage	11–13	0.02	7%	20 Jul →
dust2	13–6	0.06	14%	19 Jul →
mirage	4–13	0.09	14%	19 Jul →
dust2	8–13	-0.03	6%	19 Jul →
nuke	13–8	0.02	5%	19 Jul →
mirage	13–9	-0.01	11%	19 Jul →
ancient	11–13	0.02	10%	18 Jul →
cache	11–13	0.11	18%	18 Jul →
mirage	13–8	0.02	15%	18 Jul →
cache	13–6	0.02	16%	18 Jul →
inferno	13–6	0.11	15%	18 Jul →
dust2	13–8	0.07	7%	18 Jul →
nuke	3–0	0.20	60%	18 Jul →
inferno	11–13	-0.05	18%	18 Jul →
inferno	11–13	0.03	9%	17 Jul →
mirage	10–13	0.04	15%	17 Jul →
mirage	13–7	0.01	10%	17 Jul →
vertigo	13–7	0.13	13%	17 Jul →
nuke	13–11	0.10	14%	17 Jul →
mirage	12–12	0.01	9%	17 Jul →
mirage	13–2	0.03	8%	17 Jul →
mirage	13–11	-0.01	14%	16 Jul →
inferno	8–13	0.08	12%	16 Jul →
dust2	13–9	-0.03	20%	16 Jul →
nuke	10–13	0.04	11%	16 Jul →
anubis	9–13	-0.01	13%	16 Jul →
nuke	13–10	0.11	13%	16 Jul →
inferno	13–10	0.08	16%	16 Jul →
nuke	0–6	-0.00	13%	11 Jul →
dust2	4–9	0.05	18%	11 Jul →
mirage	4–13	-0.05	13%	10 Jul →
mirage	13–2	0.17	13%	10 Jul →