Grande — CS2 Stats

76561197990757520[U:1:30491792]Steam profile ↗✓ No bans

1,056Tracked matches64%Win rate2020Tracked since

CSDB Rating6.3 SolidAggressive Rifler

Premier CS Rating19,999Purple band · top ~8.5% of ranked players (population est.)

CSDB Leaderboard#21580 of 55847 tracked

FaceitLevel 8 · 1,512 ELOTop 31.2% of ranked FACEIT players

WingmanLegendary Eagle Master

Ladder ranks via Leetify

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Performance scores

Aim71

Positioning59

Utility49

0–100 skill scores via Leetify.

Recent form

HOT55–43–2Last 10055%Win rateWWWWWWWWLW

Last 10 vs previous 10: +50pp win rate · -0.01 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim7.1

Aggression6.9

Utility4.9

Positioning5.9

Opening Duels2.4

Clutch2.8

Strong CT-side openerLimited 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 ropz 90% 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

T-side openings. Opening success drops from 51% on CT to 28% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 564ms 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

Aim7.1

Positioning5.9

Utility4.9

Mechanics6.5

Opening Duels2.7

Win Impact9.8

Composite 6.3/10 (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-0.00+0.00

first ⅓ avg -0.01 → last ⅓ avg -0.00

Reaction time568ms−40ms

first ⅓ avg 607ms → last ⅓ avg 568ms

Headshot accuracy21.4%+5.9%

first ⅓ avg 15.5% → last ⅓ avg 21.4%

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

0.13Best rating — dust2 13–2

13–0Biggest win — dust2

8Longest win streak

W8Current streak

11–5In matches decided by ≤2 rounds

12Overtime games

Map breakdown

nukeBest map · 70% over 10cacheWeakest map · 17% over 6

Map	Grade	Played	Record	Win rate	Avg rating
dust2	A	36	23–13	64%	-0.01
inferno	B	16	8–8	50%	-0.00
ancient	B	15	7–8	47%	-0.02
nuke	S	10	7–3	70%	0.01
mirage	B	8	4–4	50%	-0.02
anubis	A	8	5–3	63%	-0.00
cache	D	6	1–5	17%	0.00
overpass	—	1	0–1	0%	-0.07

Across the last 100 tracked matches.

Faceit stats

Combat

549Matches

50%Win rate

1.18Avg K/D

84.9ADR

43%Headshot %

Clutches & streaks

34%1v1 clutch win

24%1v2 clutch win

10Longest win streak

Recent Faceit resultsWLWLL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	129	56%	1.26	17.1
Inferno	97	46%	1.13	16.9
Ancient	91	52%	1.21	17.3
Mirage	71	46%	1.25	16.8
Nuke	55	45%	1.14	17.5
Anubis	20	65%	1.03	16.5
Overpass	4	0%	0.83	16.5
Train	2	50%	1.65	20.0

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.

21.4%Headshot accuracy

34.4%Accuracy (enemy spotted)

34.1%Spray accuracy

79.4%Counter-strafing

10.7°Preaim

564msReaction time

28.0%T opening success

51.3%CT opening success

0.48Enemies flashed / flash

6.5%Flash assists

8.35HE damage / grenade

4.47Flashes / 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 0.4826 — 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 28.0234% — below the 40% mark we flag

Spend your practice time on Cache

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

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Cache callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
dust2	16–14	-0.02	28%	20 Aug →
dust2	16–14	-0.00	18%	20 Aug →
mirage	13–11	-0.02	23%	20 Aug →
dust2	13–5	-0.02	24%	20 Aug →
anubis	13–6	0.03	26%	18 Aug →
nuke	13–8	0.03	23%	15 Aug →
dust2	13–0	0.02	20%	15 Aug →
nuke	13–6	-0.02	25%	15 Aug →
ancient	6–13	-0.10	9%	15 Aug →
mirage	13–10	-0.02	22%	12 Aug →
cache	2–13	-0.01	21%	12 Aug →
cache	15–15	0.01	18%	9 Aug →
dust2	13–2	0.04	8%	9 Aug →
anubis	14–16	-0.02	16%	9 Aug →
inferno	13–2	0.05	29%	9 Aug →
inferno	15–15	-0.02	24%	7 Aug →
ancient	10–13	-0.01	20%	1 Aug →
anubis	5–13	-0.07	12%	31 Jul →
anubis	13–10	0.03	19%	28 Jul →
inferno	16–13	0.01	15%	28 Jul →
anubis	8–13	0.01	38%	28 Jul →
dust2	13–9	-0.03	18%	27 Jul →
ancient	4–13	-0.05	24%	26 Jul →
nuke	13–9	0.04	36%	26 Jul →
cache	13–7	-0.03	17%	25 Jul →
cache	13–16	-0.00	22%	25 Jul →
nuke	6–13	0.05	24%	25 Jul →
dust2	13–4	0.02	19%	21 Jul →
cache	11–13	0.02	26%	21 Jul →
anubis	13–8	0.01	16%	21 Jul →
inferno	8–13	-0.02	29%	19 Jul →
nuke	13–9	0.02	19%	15 Jul →
nuke	10–13	-0.01	16%	10 Jul →
dust2	7–13	0.01	15%	6 Jul →
nuke	16–13	0.02	24%	5 Jul →
ancient	2–13	-0.06	23%	23 Jun →
dust2	13–16	-0.09	18%	22 Jun →
ancient	13–9	-0.02	14%	18 Jun →
dust2	6–13	-0.02	19%	18 Jun →
anubis	16–14	0.04	23%	16 Jun →
mirage	8–13	0.01	23%	10 Jun →
inferno	13–11	0.03	13%	3 Jun →
dust2	13–2	0.13	26%	1 Jun →
dust2	13–9	0.02	15%	26 May →
ancient	5–13	-0.06	15%	23 May →
dust2	9–13	-0.06	27%	23 May →
dust2	13–7	0.00	27%	22 May →
dust2	13–2	-0.02	31%	21 May →
dust2	1–13	-0.02	19%	21 May →
dust2	8–13	-0.02	18%	20 May →
dust2	13–10	0.00	25%	19 May →
inferno	13–5	-0.01	19%	19 May →
dust2	9–13	-0.03	13%	19 May →
ancient	5–13	0.03	26%	18 May →
inferno	13–7	0.06	10%	16 May →
mirage	10–13	-0.04	19%	16 May →
mirage	10–13	-0.01	16%	16 May →
ancient	13–3	0.07	16%	16 May →
inferno	3–13	-0.04	12%	15 May →
dust2	13–11	-0.04	22%	15 May →
dust2	13–11	-0.06	31%	14 May →
inferno	4–13	-0.02	11%	10 May →
inferno	5–13	-0.03	15%	10 May →
mirage	13–11	-0.00	15%	10 May →
dust2	5–13	-0.08	9%	10 May →
anubis	13–10	-0.04	24%	10 May →
ancient	13–4	-0.01	19%	9 May →
inferno	13–5	-0.06	10%	9 May →
dust2	9–13	-0.09	9%	9 May →
dust2	11–13	0.01	14%	7 May →
dust2	13–10	-0.01	14%	7 May →
inferno	10–13	-0.00	13%	5 May →
dust2	5–13	-0.04	25%	4 May →
nuke	13–4	-0.00	20%	4 May →
dust2	13–5	0.04	7%	2 May →
inferno	13–6	0.05	10%	2 May →
dust2	13–8	-0.00	11%	2 May →
dust2	6–13	-0.01	14%	2 May →
inferno	13–10	0.01	29%	2 May →
dust2	13–10	0.00	15%	30 Apr →
mirage	5–13	-0.03	3%	30 Apr →
ancient	16–14	-0.02	17%	30 Apr →
ancient	7–13	-0.09	4%	30 Apr →
nuke	13–7	0.06	21%	30 Apr →
cache	10–13	0.03	17%	30 Apr →
ancient	13–8	0.01	21%	30 Apr →
dust2	13–11	-0.00	16%	29 Apr →
ancient	13–11	-0.00	21%	29 Apr →
ancient	13–3	0.06	17%	28 Apr →
dust2	11–13	0.00	14%	28 Apr →
dust2	13–1	0.01	19%	28 Apr →
inferno	10–13	0.04	11%	27 Apr →
overpass	10–13	-0.07	14%	27 Apr →
nuke	9–13	-0.08	15%	26 Apr →
dust2	13–10	-0.01	15%	25 Apr →
mirage	13–5	-0.03	18%	25 Apr →
inferno	5–13	-0.08	19%	22 Apr →
dust2	13–5	0.04	19%	22 Apr →
ancient	14–16	0.01	8%	19 Apr →
dust2	13–10	0.09	32%	18 Apr →