gren — CS2 Stats

76561198799720934[U:1:839455206]Steam profile ↗✓ No bans

403Tracked matches20%Win rate2024Tracked since

CSDB Rating3.5 Learning

FaceitLevel 4Top 81.0% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim47

Positioning34

Utility25

0–100 skill scores via Leetify.

Recent form

COLD37–62–1Last 10037%Win rateLLLLLWWLLL

Last 10 vs previous 10: +0pp win rate · +0.03 avg rating

Player DNA

Aim4.7

Aggression0.0

Utility2.5

Positioning3.4

Opening Duels0.0

Clutch0.0

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 64% playstyle similarity

Most alike: opening-duel success, positioning profile.

Where you differ: lower aim profile; lower opening-fight frequency.

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

T-side openings. Opening success drops from 33% on CT to 8% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 678ms 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

Aim4.7

Positioning3.4

Utility2.5

Mechanics6.7

Opening Duels0.4

Win Impact0.0

Composite 3.5/10 (Learning), 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 time669ms−40ms

first ⅓ avg 708ms → last ⅓ avg 669ms

Headshot accuracy12.5%+1.0%

first ⅓ avg 11.5% → last ⅓ avg 12.5%

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

0.11Best rating — dust2 13–9

13–2Biggest win — ancient

5Longest win streak

L5Current streak

4–7In matches decided by ≤2 rounds

10Overtime games

Map breakdown

ancientBest map · 50% over 20infernoWeakest map · 15% over 13

Map	Grade	Played	Record	Win rate	Avg rating
ancient	B	20	10–10	50%	-0.03
nuke	B	19	9–10	47%	-0.02
overpass	B	15	7–8	47%	-0.03
dust2	D	14	3–11	21%	-0.03
inferno	D	13	2–11	15%	-0.03
mirage	D	9	3–6	33%	-0.06
anubis	C	5	2–3	40%	-0.03
train	—	3	1–2	33%	-0.02
cache	—	2	0–2	0%	-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (15% over 13). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

9Matches

22%Win rate

0.46Avg K/D

49.3ADR

40%Headshot %

Clutches & streaks

0%1v1 clutch win

0%1v2 clutch win

1Longest win streak

Recent Faceit resultsLLWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	2	50%	0.59	11.0
Dust2	2	0%	0.29	4.5
Overpass	1	0%	0.31	5.0
Vertigo	1	0%	0.38	6.0
Inferno	1	100%	0.62	10.0
Nuke	1	0%	0.79	11.0
Ancient	1	0%	0.24	4.0

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.

13.1%Headshot accuracy

31.9%Accuracy (enemy spotted)

35.3%Spray accuracy

80.3%Counter-strafing

10.6°Preaim

678msReaction time

8.4%T opening success

33.4%CT opening success

0.47Enemies flashed / flash

0.0%Flash assists

6.34HE damage / grenade

2.33Flashes / 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 13.1324% — 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 0.4682 — 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 8.4209% — 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.

15% win rate across 13 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	7–13	0.01	8%	22 Jul →
cache	8–13	0.02	10%	22 Jul →
overpass	4–13	0.04	12%	26 Jun →
inferno	5–13	-0.06	15%	22 Jun →
nuke	9–13	-0.02	14%	17 Jun →
ancient	13–9	-0.01	15%	17 Jun →
overpass	13–3	0.05	8%	17 Jun →
dust2	1–13	-0.11	8%	17 Jun →
nuke	8–13	0.00	18%	16 Jun →
ancient	3–13	-0.05	19%	22 May →
overpass	8–13	-0.05	15%	22 May →
anubis	13–8	-0.00	14%	22 May →
mirage	3–13	-0.08	14%	20 May →
inferno	13–11	-0.02	33%	20 May →
cache	3–13	-0.10	0%	29 Apr →
overpass	2–13	-0.04	15%	26 Apr →
nuke	5–13	0.02	18%	22 Apr →
anubis	1–13	-0.11	7%	14 Apr →
nuke	8–13	-0.03	4%	7 Apr →
inferno	5–13	-0.03	13%	3 Apr →
anubis	6–13	0.04	11%	1 Apr →
dust2	6–13	-0.01	25%	26 Mar →
anubis	7–13	-0.12	9%	25 Mar →
overpass	13–11	-0.03	13%	25 Mar →
ancient	13–3	0.04	8%	22 Mar →
nuke	7–13	-0.06	6%	3 Mar →
ancient	8–13	-0.06	16%	26 Feb →
nuke	1–13	-0.12	27%	26 Feb →
inferno	9–13	-0.05	9%	23 Feb →
nuke	11–13	-0.04	7%	23 Feb →
dust2	16–13	-0.03	6%	22 Feb →
anubis	13–4	0.03	12%	22 Feb →
nuke	8–13	-0.07	4%	8 Dec →
inferno	8–13	-0.01	16%	8 Dec →
mirage	13–4	0.01	8%	23 Oct →
dust2	10–13	-0.02	15%	23 Oct →
dust2	7–13	-0.03	21%	21 Oct →
inferno	11–13	-0.07	11%	21 Oct →
dust2	4–13	-0.09	11%	21 Oct →
nuke	13–9	-0.03	11%	21 Oct →
ancient	13–8	0.02	9%	21 Oct →
dust2	12–16	-0.05	11%	18 Oct →
ancient	13–16	-0.08	7%	18 Oct →
mirage	16–13	-0.04	15%	18 Oct →
dust2	3–13	-0.02	7%	17 Oct →
nuke	16–13	0.01	15%	17 Oct →
nuke	13–4	0.07	12%	17 Oct →
ancient	5–13	-0.03	3%	17 Oct →
inferno	3–13	-0.09	21%	17 Oct →
overpass	13–5	-0.04	11%	17 Oct →
train	8–13	-0.06	17%	6 Oct →
overpass	8–13	-0.01	7%	6 Oct →
overpass	13–6	-0.01	8%	6 Oct →
ancient	13–10	0.02	12%	6 Oct →
nuke	13–6	-0.06	10%	6 Oct →
ancient	13–9	0.01	20%	6 Oct →
inferno	13–16	-0.06	23%	6 Oct →
dust2	11–13	-0.02	16%	6 Oct →
inferno	1–13	-0.05	13%	3 Oct →
ancient	13–2	0.05	12%	19 Sept →
inferno	9–13	-0.01	5%	19 Sept →
inferno	13–16	-0.01	11%	16 Sept →
ancient	13–6	-0.07	6%	16 Sept →
mirage	11–13	-0.06	10%	16 Sept →
ancient	13–8	-0.01	11%	16 Sept →
inferno	4–13	0.03	20%	16 Sept →
overpass	13–6	-0.03	13%	16 Sept →
nuke	13–11	0.01	11%	14 Sept →
ancient	7–13	-0.08	8%	14 Sept →
inferno	13–5	0.09	7%	14 Sept →
train	13–9	-0.01	18%	12 Sept →
overpass	13–7	-0.00	10%	12 Sept →
ancient	8–13	-0.06	6%	12 Sept →
nuke	13–8	0.11	6%	12 Sept →
nuke	13–9	-0.06	11%	12 Sept →
mirage	2–13	-0.13	21%	10 Sept →
dust2	13–9	0.11	10%	10 Sept →
ancient	9–13	0.05	8%	10 Sept →
ancient	3–13	-0.09	11%	10 Sept →
overpass	11–13	-0.06	12%	10 Sept →
nuke	10–13	-0.05	8%	10 Sept →
mirage	13–8	-0.01	14%	10 Sept →
train	5–13	0.01	21%	10 Sept →
overpass	13–11	-0.07	15%	10 Sept →
overpass	15–15	0.00	10%	10 Sept →
mirage	7–13	-0.06	23%	8 Sept →
dust2	14–16	-0.01	6%	8 Sept →
overpass	7–13	-0.02	9%	4 Sept →
mirage	14–16	-0.12	0%	4 Sept →
dust2	8–13	-0.05	11%	4 Sept →
ancient	4–13	-0.05	11%	2 Sept →
mirage	4–13	-0.02	15%	2 Sept →
ancient	13–8	-0.01	6%	2 Sept →
nuke	13–10	-0.07	8%	2 Sept →
dust2	13–9	-0.03	22%	2 Sept →
nuke	13–6	0.02	26%	2 Sept →
ancient	13–5	-0.03	8%	2 Sept →
nuke	5–13	-0.08	3%	1 Sept →
ancient	9–13	-0.05	15%	1 Sept →
overpass	4–13	-0.12	6%	1 Sept →