GrimSkies — CS2 Stats

76561199397337157[U:1:1437071429]Steam profile ↗✓ No bans

1,547Tracked matches68%Win rate2023Tracked since

1,353Hours in CS3Hrs last 2 wks

CSDB Rating5.3 DevelopingEntry Fragger

Ladder ranks via Leetify

Performance scores

Aim35

Positioning62

Utility61

0–100 skill scores via Leetify.

Recent form

HOT47–45–8Last 10047%Win rateWWWLLWTWWW

Last 10 vs previous 10: +30pp win rate · -0.03 avg rating

Player DNA

Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.

Aim3.5

Aggression10.0

Utility6.1

Positioning6.2

Opening Duels6.6

Clutch1.8

Effective flashes

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 s1mple 83% playstyle similarity

Most alike: opening-fight frequency, 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

Strengths

CT openings. 63% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

Areas to improve

Reaction time. 574ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 62% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim3.5

Positioning6.2

Utility6.1

Mechanics2.7

Opening Duels6.6

Win Impact10.0

Composite 5.3/10 (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 rating0.03+0.02

first ⅓ avg 0.02 → last ⅓ avg 0.03

Reaction time585ms−61ms

first ⅓ avg 645ms → last ⅓ avg 585ms

Headshot accuracy14.0%−1.1%

first ⅓ avg 15.1% → last ⅓ avg 14.0%

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

0.22Best rating — mirage 13–11

13–3Biggest win — ancient

11Longest win streak

W3Current streak

6–14In matches decided by ≤2 rounds

3Overtime games

Map breakdown

mirageBest map · 64% over 11ancientWeakest map · 17% over 6

Map	Grade	Played	Record	Win rate	Avg rating
dust2	B	29	13–16	45%	0.02
cache	A	15	9–6	60%	0.01
inferno	C	12	5–7	42%	0.03
mirage	A	11	7–4	64%	0.04
nuke	C	8	3–5	38%	0.02
ancient	D	6	1–5	17%	0.02
train	A	5	3–2	60%	0.06
overpass	C	5	2–3	40%	0.02
office	—	4	2–2	50%	0.06
anubis	—	3	1–2	33%	0.07
vertigo	—	1	1–0	100%	-0.03
fachwerk	—	1	0–1	0%	-0.05

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

28,581Lifetime kills

0.93K/D

1,826Matches

47.6%Match win rate · Top 50% of tracked players

38.1%Headshot %

4.1%Shot accuracy

3,692MVPs

691Hours (in match)

1,133Bombs planted

329Bombs defused

Most-used weapons

AWP7,071

AK-475,102

M4A4 / M4A1-S2,691

P2502,219

P2000 / USP-S1,799

Glock-181,405

Desert Eagle1,290

FAMAS1,090

MP91,010

MAC-10749

Lifetime map wins

4,678dust2

2,582inferno

2,205nuke

1,484vertigo

463train

377office

18cbble

8ar_shoots

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

Faceit stats

Combat

15Matches

40%Win rate

0.69Avg K/D

55.2ADR

33%Headshot %

Clutches & streaks

29%1v1 clutch win

17%1v2 clutch win

1Longest win streak

Recent Faceit resultsLWLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	6	67%	1.04	13.7
Dust2	5	40%	0.50	10.6
Inferno	2	0%	0.33	5.5
Vertigo	1	0%	0.36	5.0
Ancient	1	0%	0.67	14.0

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.

14.0%Headshot accuracy

31.6%Accuracy (enemy spotted)

31.3%Spray accuracy

62.3%Counter-strafing

12.2°Preaim

574msReaction time

49.5%T opening success

63.1%CT opening success

0.70Enemies flashed / flash

9.5%Flash assists

14.01HE damage / grenade

7.28Flashes / 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 12.2158° — 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 13.9575% — below the 15% mark we flag
Aim Training →

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.

17% win rate across 6 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
mirage	13–10	-0.05	21%	28 Aug →
cache	13–6	0.03	11%	28 Aug →
dust2	13–6	0.04	18%	27 Aug →
nuke	10–13	0.04	11%	27 Aug →
mirage	11–13	0.04	8%	27 Aug →
cache	13–10	-0.02	16%	8 Aug →
dust2	12–12	0.03	6%	7 Aug →
dust2	13–10	0.06	14%	7 Aug →
vertigo	13–8	-0.03	10%	7 Aug →
dust2	13–8	0.02	11%	6 Aug →
dust2	13–6	0.02	17%	6 Aug →
inferno	12–12	0.06	20%	5 Aug →
dust2	5–13	0.06	18%	5 Aug →
dust2	11–13	-0.07	15%	5 Aug →
inferno	6–13	0.08	10%	4 Aug →
dust2	13–9	0.03	10%	4 Aug →
office	10–13	0.13	6%	1 Aug →
office	13–9	0.01	18%	1 Aug →
train	13–4	0.14	12%	1 Aug →
overpass	5–13	-0.01	13%	1 Aug →
inferno	4–13	-0.02	18%	1 Aug →
dust2	11–13	-0.01	12%	1 Aug →
ancient	13–3	0.12	17%	1 Aug →
cache	13–9	0.01	16%	1 Aug →
nuke	13–6	0.02	22%	28 Jul →
dust2	13–6	0.13	15%	28 Jul →
overpass	13–4	0.07	17%	28 Jul →
dust2	13–10	0.03	15%	27 Jul →
inferno	13–8	0.03	18%	27 Jul →
dust2	13–10	-0.03	9%	27 Jul →
train	13–5	0.01	8%	27 Jul →
nuke	13–6	0.12	15%	24 Jul →
cache	13–11	-0.00	16%	24 Jul →
dust2	11–13	0.00	19%	24 Jul →
nuke	11–13	-0.08	15%	23 Jul →
anubis	4–13	0.13	25%	23 Jul →
anubis	5–13	0.06	4%	23 Jul →
dust2	12–12	0.10	14%	23 Jul →
dust2	11–13	0.02	22%	23 Jul →
mirage	11–13	0.12	15%	23 Jul →
fachwerk	9–13	-0.05	17%	18 Jul →
overpass	5–13	0.02	8%	14 Jul →
dust2	11–13	0.01	6%	14 Jul →
dust2	12–12	0.09	30%	14 Jul →
cache	4–13	-0.07	14%	13 Jul →
cache	13–7	-0.04	13%	13 Jul →
cache	13–9	-0.06	11%	13 Jul →
mirage	11–13	0.06	18%	11 Jul →
cache	2–13	-0.07	8%	11 Jul →
mirage	3–0	-0.01	0%	11 Jul →
ancient	2–13	-0.06	20%	10 Jul →
nuke	13–5	0.04	16%	10 Jul →
overpass	5–13	0.04	11%	10 Jul →
ancient	3–13	-0.06	5%	10 Jul →
mirage	13–6	-0.02	13%	10 Jul →
inferno	13–9	0.17	13%	10 Jul →
cache	12–12	0.04	9%	10 Jul →
nuke	10–13	0.07	10%	9 Jul →
dust2	13–6	0.01	6%	9 Jul →
cache	11–13	0.01	9%	9 Jul →
mirage	10–13	-0.01	33%	9 Jul →
mirage	13–7	-0.01	19%	8 Jul →
mirage	13–11	0.22	16%	8 Jul →
inferno	8–13	0.02	28%	8 Jul →
cache	13–5	0.02	15%	8 Jul →
cache	13–7	0.09	14%	7 Jul →
dust2	6–11	0.10	19%	7 Jul →
dust2	13–10	0.00	17%	7 Jul →
ancient	11–13	0.02	9%	6 Jul →
train	8–13	0.04	17%	6 Jul →
mirage	13–9	0.06	21%	6 Jul →
office	13–6	-0.05	21%	6 Jul →
cache	8–13	0.12	17%	6 Jul →
cache	13–5	0.06	5%	4 Jul →
dust2	12–12	-0.10	14%	4 Jul →
dust2	12–12	-0.01	7%	4 Jul →
nuke	10–13	-0.07	14%	3 Jul →
dust2	11–13	0.11	10%	1 Jul →
dust2	13–10	0.11	15%	1 Jul →
dust2	12–12	0.08	5%	1 Jul →
anubis	13–8	0.02	5%	30 Jun →
inferno	10–13	0.06	12%	30 Jun →
office	10–13	0.16	33%	30 Jun →
overpass	13–11	-0.04	16%	30 Jun →
cache	11–13	-0.01	12%	30 Jun →
train	3–13	0.01	14%	30 Jun →
inferno	11–13	-0.07	30%	29 Jun →
dust2	2–13	-0.08	14%	27 Jun →
inferno	13–6	0.00	25%	24 Jun →
inferno	13–10	0.11	16%	23 Jun →
train	13–11	0.09	16%	23 Jun →
ancient	9–13	0.09	7%	23 Jun →
dust2	6–13	-0.08	9%	21 Jun →
inferno	16–14	-0.02	32%	21 Jun →
inferno	12–16	-0.07	14%	20 Jun →
mirage	16–14	-0.00	15%	20 Jun →
dust2	13–8	0.00	8%	18 Jun →
dust2	10–3	0.02	21%	18 Jun →
nuke	8–13	0.03	10%	17 Jun →
ancient	3–13	-0.01	17%	12 Jun →