grong — CS2 Stats

JP76561198046230416[U:1:85964688]Steam profile ↗✓ No bans

472Tracked matches40%Win rate2020Tracked since

CSDB Rating4.9 DevelopingPassive Rifler

FaceitLevel 7Top 42.3% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim61

Positioning43

Utility54

0–100 skill scores via Leetify.

Recent form

STEADY47–49–4Last 10047%Win rateLWWLWWWLWL

Last 10 vs previous 10: +30pp win rate · -0.01 avg rating

Player DNA

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

Aim6.1

Aggression3.9

Utility5.4

Positioning4.3

Opening Duels1.8

Clutch1.8

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 86% playstyle similarity

Most alike: opening-duel success, utility contribution.

Where you differ: lower positioning profile; 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. 629ms 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

Aim6.1

Positioning4.3

Utility5.4

Mechanics7.3

Opening Duels1.8

Win Impact1.7

Composite 4.9/10 (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 rating-0.01−0.02

first ⅓ avg 0.02 → last ⅓ avg -0.01

Reaction time640ms+44ms

first ⅓ avg 596ms → last ⅓ avg 640ms

Headshot accuracy22.3%−0.4%

first ⅓ avg 22.7% → last ⅓ avg 22.3%

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

0.16Best rating — train 13–10

13–1Biggest win — cache

5Longest win streak

7–4In matches decided by ≤2 rounds

8Overtime games

Map breakdown

anubisBest map · 62% over 13ancientWeakest map · 33% over 9

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	22	11–11	50%	-0.01
nuke	A	14	8–6	57%	-0.01
mirage	C	13	5–8	38%	-0.02
anubis	A	13	8–5	62%	-0.00
ancient	D	9	3–6	33%	-0.01
vertigo	C	7	3–4	43%	-0.00
inferno	C	7	3–4	43%	-0.04
overpass	A	5	3–2	60%	0.01
train	—	4	2–2	50%	0.07
cache	—	3	1–2	33%	0.00
office	—	2	0–2	0%	0.06
italy	—	1	0–1	0%	0.07

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

71Matches

63%Win rate

1.01Avg K/D

78.1ADR

57%Headshot %

Clutches & streaks

29%1v1 clutch win

21%1v2 clutch win

8Longest win streak

Recent Faceit resultsLLLWL

Map	Matches	Win rate	Avg K/D	Avg kills
Dust2	14	64%	0.96	13.7
Cache	14	57%	0.84	14.6
Anubis	11	82%	1.14	18.4
Mirage	9	56%	1.15	16.8
Nuke	7	57%	0.91	14.1
Ancient	4	50%	0.82	12.3
Vertigo	3	67%	0.88	12.3
Inferno	3	67%	0.84	10.7

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.

22.5%Headshot accuracy

31.0%Accuracy (enemy spotted)

34.7%Spray accuracy

82.7%Counter-strafing

11.7°Preaim

629msReaction time

33.6%T opening success

40.9%CT opening success

0.65Enemies flashed / flash

4.9%Flash assists

9.24HE damage / grenade

9.73Flashes / 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
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 33.6044% — below the 40% mark we flag

Spend your practice time on Ancient

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

33% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
dust2	9–13	0.03	30%	10 Aug →
ancient	13–6	0.08	37%	8 Aug →
ancient	13–10	-0.01	24%	23 Jul →
mirage	0–13	-0.11	10%	23 Jul →
cache	13–1	0.04	18%	12 Jul →
mirage	13–4	0.02	22%	10 Jul →
nuke	13–8	0.05	19%	9 Jul →
anubis	16–19	-0.01	18%	7 Jul →
anubis	16–13	-0.05	22%	30 Jun →
nuke	9–13	-0.05	12%	24 Jun →
nuke	13–11	0.01	24%	18 Jun →
overpass	4–13	-0.08	29%	17 Jun →
vertigo	11–13	-0.01	18%	15 Jun →
dust2	8–13	-0.04	15%	13 Jun →
dust2	9–13	0.06	24%	13 Jun →
cache	9–13	0.03	21%	13 Jun →
dust2	11–13	-0.05	15%	3 Jun →
dust2	13–9	0.03	36%	3 Jun →
inferno	13–4	0.09	20%	31 May →
mirage	14–16	-0.01	25%	25 May →
mirage	8–13	0.01	25%	25 May →
mirage	13–2	0.05	24%	25 May →
mirage	3–13	-0.02	29%	24 May →
ancient	8–13	-0.05	13%	22 May →
anubis	13–7	0.02	37%	20 May →
mirage	13–10	-0.00	19%	18 May →
ancient	7–13	-0.05	21%	12 May →
dust2	1–13	-0.07	20%	3 May →
nuke	7–13	-0.02	38%	2 May →
anubis	5–13	-0.01	12%	2 May →
nuke	13–9	-0.03	20%	2 May →
dust2	13–9	0.00	25%	2 May →
ancient	9–13	-0.06	15%	2 May →
inferno	9–13	-0.01	14%	2 May →
nuke	13–7	0.03	16%	1 May →
ancient	13–16	-0.03	10%	30 Apr →
dust2	13–10	-0.00	18%	30 Apr →
anubis	8–13	-0.01	9%	30 Apr →
nuke	13–4	-0.02	28%	30 Apr →
cache	10–13	-0.06	23%	29 Apr →
inferno	13–9	0.03	35%	29 Apr →
nuke	16–13	-0.06	21%	28 Apr →
mirage	9–13	-0.06	13%	28 Apr →
dust2	11–13	-0.03	15%	28 Apr →
mirage	4–13	-0.06	13%	28 Apr →
overpass	13–7	-0.00	21%	28 Apr →
anubis	13–5	0.06	18%	28 Apr →
overpass	13–11	-0.01	32%	27 Apr →
inferno	13–9	0.00	16%	27 Apr →
dust2	15–15	0.00	19%	26 Apr →
nuke	9–13	-0.00	19%	26 Apr →
dust2	13–10	-0.01	23%	26 Apr →
anubis	16–14	0.01	22%	26 Apr →
nuke	10–13	-0.01	21%	26 Apr →
dust2	13–10	-0.06	31%	25 Apr →
mirage	13–9	0.02	20%	25 Apr →
mirage	10–13	-0.05	16%	25 Apr →
dust2	8–13	-0.02	29%	9 Feb →
anubis	2–13	-0.05	20%	8 Feb →
ancient	7–13	-0.05	14%	22 Jan →
inferno	2–9	-0.31	27%	3 Oct →
inferno	6–9	-0.03	26%	3 Oct →
office	12–12	0.01	16%	1 Oct →
nuke	9–13	-0.05	41%	27 Sept →
dust2	13–10	0.05	22%	27 Sept →
overpass	13–5	0.07	29%	27 Sept →
train	13–3	0.10	20%	24 Dec →
train	5–13	-0.01	29%	20 Nov →
train	13–10	0.16	39%	17 Nov →
train	6–13	0.01	22%	14 Nov →
nuke	13–7	0.04	27%	9 Nov →
mirage	10–13	-0.01	17%	19 Oct →
dust2	13–11	-0.01	20%	11 Oct →
nuke	9–13	-0.04	25%	8 Oct →
vertigo	10–13	-0.01	19%	8 Oct →
dust2	1–13	-0.03	28%	7 Oct →
nuke	13–8	0.10	26%	7 Oct →
anubis	3–13	-0.08	17%	6 Oct →
dust2	10–13	0.05	21%	6 Oct →
ancient	8–13	0.01	13%	4 Oct →
dust2	13–4	0.03	40%	4 Oct →
office	12–12	0.12	19%	3 Oct →
italy	12–12	0.07	21%	3 Oct →
anubis	13–7	-0.03	18%	30 Sept →
ancient	13–8	0.04	30%	26 Sept →
vertigo	8–13	-0.04	19%	26 Sept →
anubis	13–6	0.06	23%	25 Sept →
anubis	13–2	0.00	35%	25 Sept →
dust2	13–5	-0.03	16%	24 Sept →
vertigo	13–5	0.05	14%	24 Sept →
dust2	16–14	0.02	31%	23 Sept →
dust2	4–13	-0.06	22%	23 Sept →
vertigo	13–11	0.02	14%	22 Sept →
dust2	13–5	-0.02	21%	20 Sept →
inferno	5–13	-0.02	19%	20 Sept →
anubis	13–6	0.05	14%	19 Sept →
mirage	13–5	0.02	17%	19 Sept →
vertigo	2–13	-0.14	19%	19 Sept →
vertigo	13–11	0.11	28%	18 Sept →
overpass	8–13	0.07	27%	18 Sept →