twitch.tv/gruenics2randale — CS2 Stats

DE76561197969394031[U:1:9128303]Steam profile ↗✓ No bans

3,582Tracked matches68%Win rate2020Tracked since

CSDB Rating5.7 Solid

Premier CS Rating17,087Purple band · top ~20.1% of ranked players (population est.)

CSDB Leaderboard#14231 of 25426 tracked

FaceitLevel 4 · 997 ELOTop 81.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim38

Positioning58

Utility73

0–100 skill scores via Leetify.

Recent form

STEADY64–30–6Last 10064%Win rateWLLLWWLLWW

Last 10 vs previous 10: -10pp win rate · -0.03 avg rating

Player DNA

Aim3.8

Aggression8.8

Utility7.3

Positioning5.8

Opening Duels5.4

Clutch3.0

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 ZywOo 82% playstyle similarity

Most alike: utility contribution, opening-fight frequency.

Where you differ: 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. 607ms 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

Aim3.8

Positioning5.8

Utility7.3

Mechanics5.0

Opening Duels5.4

Win Impact10.0

Composite 5.7/10 (Solid), 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-0.01−0.02

first ⅓ avg 0.01 → last ⅓ avg -0.01

Reaction time608ms−46ms

first ⅓ avg 654ms → last ⅓ avg 608ms

Headshot accuracy12.0%−4.3%

first ⅓ avg 16.3% → last ⅓ avg 12.0%

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

0.23Best rating — warden 13–10

13–0Biggest win — inferno

9Longest win streak

7–7In matches decided by ≤2 rounds

4Overtime games

Map breakdown

dust2Best map · 82% over 11trainWeakest map · 40% over 5

Map	Grade	Played	Record	Win rate	Avg rating
nuke	A	19	11–8	58%	0.02
inferno	A	16	10–6	63%	0.00
cache	S	11	8–3	73%	0.02
dust2	S	11	9–2	82%	0.00
ancient	S	9	6–3	67%	0.03
anubis	B	8	4–4	50%	0.03
train	C	5	2–3	40%	0.01
overpass	S	5	4–1	80%	0.05
office	—	4	2–2	50%	-0.04
mirage	—	3	2–1	67%	-0.02
vertigo	—	2	1–1	50%	-0.07
stronghold	—	2	2–0	100%	0.02
warden	—	2	1–1	50%	0.12
alpine	—	2	2–0	100%	-0.04
italy	—	1	0–1	0%	-0.07

Across the last 100 tracked matches.

Faceit stats

Combat

154Matches

47%Win rate

1.00Avg K/D

83.6ADR

41%Headshot %

Clutches & streaks

35%1v1 clutch win

23%1v2 clutch win

7Longest win streak

Recent Faceit resultsWLLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	35	57%	0.95	13.8
Nuke	30	43%	1.09	16.1
Dust2	28	46%	1.01	14.1
Ancient	19	21%	0.99	15.2
Anubis	13	62%	1.05	14.5
Mirage	7	57%	1.06	12.9
Overpass	7	57%	0.80	14.6
Train	6	67%	1.06	16.3

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.

12.1%Headshot accuracy

30.6%Accuracy (enemy spotted)

34.8%Spray accuracy

72.5%Counter-strafing

12.3°Preaim

607msReaction time

47.9%T opening success

55.5%CT opening success

0.65Enemies flashed / flash

6.9%Flash assists

7.72HE damage / grenade

18.73Flashes / 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.

Advanced Mechanics
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 12.2699° — above the 12° mark we flag
Aim Training →
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 12.0599% — below the 15% mark we flag
Aim Training →

Spend your practice time on Train

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

40% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
train	13–9	-0.02	3%	17 Jun →
train	10–13	-0.07	9%	17 Jun →
vertigo	1–9	-0.21	8%	16 Jun →
office	8–13	-0.08	15%	16 Jun →
cache	13–6	0.07	9%	16 Jun →
vertigo	13–4	0.06	11%	16 Jun →
nuke	7–13	-0.05	8%	16 Jun →
nuke	5–13	-0.04	24%	15 Jun →
dust2	13–6	-0.02	14%	15 Jun →
mirage	13–2	-0.04	11%	15 Jun →
anubis	15–15	-0.00	16%	15 Jun →
dust2	13–8	0.02	13%	15 Jun →
dust2	13–4	-0.02	13%	15 Jun →
nuke	13–1	0.03	15%	15 Jun →
ancient	11–13	-0.04	13%	14 Jun →
inferno	13–9	-0.03	13%	14 Jun →
inferno	13–11	-0.00	13%	14 Jun →
stronghold	13–6	-0.00	17%	14 Jun →
ancient	12–12	-0.06	9%	14 Jun →
train	7–13	0.05	16%	14 Jun →
ancient	13–8	0.09	6%	14 Jun →
anubis	13–6	0.14	10%	14 Jun →
ancient	13–8	0.00	12%	14 Jun →
overpass	13–6	0.08	12%	14 Jun →
stronghold	13–9	0.04	13%	14 Jun →
inferno	13–11	-0.05	9%	14 Jun →
warden	11–13	0.02	11%	14 Jun →
office	4–13	-0.03	9%	13 Jun →
inferno	13–7	0.02	14%	13 Jun →
nuke	13–4	0.03	15%	13 Jun →
anubis	8–13	-0.01	12%	13 Jun →
nuke	9–13	-0.05	10%	13 Jun →
ancient	13–7	0.03	14%	13 Jun →
warden	13–10	0.23	16%	13 Jun →
ancient	9–1	0.12	12%	13 Jun →
nuke	13–1	0.09	35%	13 Jun →
anubis	13–4	0.10	19%	13 Jun →
inferno	2–13	-0.02	16%	13 Jun →
overpass	13–9	0.13	22%	13 Jun →
nuke	13–11	0.10	21%	12 Jun →
cache	8–13	0.02	19%	12 Jun →
inferno	13–10	0.02	21%	12 Jun →
train	13–5	0.10	14%	12 Jun →
dust2	13–9	0.01	8%	12 Jun →
anubis	11–13	0.08	14%	12 Jun →
inferno	13–6	0.01	10%	12 Jun →
cache	13–9	-0.04	10%	12 Jun →
cache	13–3	0.10	16%	12 Jun →
inferno	13–10	0.04	24%	12 Jun →
nuke	13–11	0.04	21%	12 Jun →
nuke	8–1	0.07	14%	12 Jun →
nuke	13–11	0.00	19%	5 Jun →
office	13–7	-0.02	13%	5 Jun →
dust2	13–11	0.02	18%	4 Jun →
train	11–13	0.01	17%	3 Jun →
nuke	11–13	0.01	17%	3 Jun →
nuke	13–16	-0.05	17%	3 Jun →
nuke	0–4	-0.05	13%	3 Jun →
ancient	12–12	0.06	10%	3 Jun →
inferno	13–3	-0.10	15%	3 Jun →
cache	4–13	-0.06	19%	3 Jun →
cache	13–1	0.01	8%	1 Jun →
inferno	10–13	0.03	19%	1 Jun →
anubis	12–16	-0.02	12%	31 May →
ancient	13–6	-0.02	14%	31 May →
dust2	13–3	0.03	22%	31 May →
inferno	13–0	0.08	28%	31 May →
nuke	13–8	0.02	14%	31 May →
dust2	13–7	0.04	16%	31 May →
anubis	13–11	-0.05	15%	31 May →
dust2	3–13	-0.02	17%	31 May →
overpass	13–9	0.01	20%	31 May →
overpass	13–4	0.03	13%	29 May →
cache	13–2	0.13	13%	29 May →
mirage	12–12	-0.01	12%	29 May →
dust2	13–4	-0.03	6%	29 May →
inferno	13–7	0.07	10%	29 May →
cache	5–13	0.01	40%	28 May →
nuke	13–2	0.15	21%	24 May →
alpine	13–7	-0.06	23%	24 May →
cache	13–5	0.00	7%	16 May →
dust2	13–9	-0.00	14%	16 May →
dust2	14–16	-0.02	12%	16 May →
office	13–9	-0.04	13%	16 May →
nuke	13–3	0.06	17%	16 May →
cache	13–5	-0.04	17%	16 May →
nuke	13–8	0.08	21%	16 May →
anubis	13–9	0.03	14%	16 May →
mirage	13–5	-0.00	11%	14 May →
inferno	11–13	-0.01	11%	14 May →
inferno	2–13	-0.08	12%	9 May →
alpine	13–4	-0.02	22%	9 May →
inferno	12–12	0.03	15%	9 May →
cache	13–0	0.07	27%	9 May →
nuke	10–13	-0.02	5%	9 May →
ancient	13–4	0.07	11%	9 May →
inferno	8–13	0.04	20%	9 May →
italy	2–13	-0.07	37%	9 May →
overpass	12–12	-0.02	16%	9 May →
nuke	8–13	0.02	16%	9 May →