Rick Ross — CS2 Stats

CA76561198800060386[U:1:839794658]Steam profile ↗✓ No bans

1,244Tracked matches60%Win rate2021Tracked since

1,668Hours in CS5Hrs last 2 wks

CSDB Rating5.5 SolidPassive Rifler

WingmanGold Nova Master

Ladder ranks via Leetify

Performance scores

Aim63

Positioning41

Utility49

0–100 skill scores via Leetify.

Recent form

STEADY49–50–1Last 10049%Win rateWLWLWLWLWW

Last 10 vs previous 10: +0pp win rate · -0.02 avg rating

Player DNA

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

Aim6.3

Aggression4.0

Utility4.9

Positioning4.1

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 82% 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

Areas to improve

Reaction time. 639ms 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

Aim6.3

Positioning4.1

Utility4.9

Mechanics8.1

Opening Duels0.4

Win Impact8.3

Composite 5.5/10 (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 time641ms−46ms

first ⅓ avg 687ms → last ⅓ avg 641ms

Headshot accuracy20.5%+3.3%

first ⅓ avg 17.2% → last ⅓ avg 20.5%

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

0.14Best rating — train 13–2

13–0Biggest win — inferno

5Longest win streak

9–7In matches decided by ≤2 rounds

7Overtime games

Map breakdown

trainBest map · 71% over 7anubisWeakest map · 20% over 5

Map	Grade	Played	Record	Win rate	Avg rating
inferno	A	25	14–11	56%	0.01
ancient	B	21	10–11	48%	-0.00
nuke	A	16	9–7	56%	0.00
dust2	D	9	3–6	33%	0.01
mirage	C	8	3–5	38%	0.00
train	S	7	5–2	71%	0.02
anubis	D	5	1–4	20%	-0.03
cache	A	5	3–2	60%	-0.04
overpass	—	4	1–3	25%	0.01

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

33,135Lifetime kills

0.89K/D

2,197Matches

42.1%Match win rate

46.4%Headshot % · Top 50% of tracked players

5.7%Shot accuracy

3,472MVPs

1,016Hours (in match)

2,129Bombs planted

407Bombs defused

Most-used weapons

AK-4711,164

M4A4 / M4A1-S6,476

AWP3,117

Glock-181,932

P2000 / USP-S1,802

Desert Eagle1,374

MAC-101,206

MP91,051

Galil AR729

P90512

Lifetime map wins

4,261inferno

2,964dust2

1,483vertigo

1,169nuke

443train

87office

36cbble

12lake

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

Faceit stats

Combat

1Matches

0%Win rate

0.71Avg K/D

78.2ADR

50%Headshot %

Clutches & streaks

0%1v1 clutch win

0%1v2 clutch win

0Longest win streak

Recent Faceit resultsLLLLL

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

29.8%Accuracy (enemy spotted)

30.2%Spray accuracy

86.4%Counter-strafing

9.6°Preaim

639msReaction time

25.3%T opening success

33.2%CT opening success

0.61Enemies flashed / flash

2.4%Flash assists

6.65HE damage / grenade

11.19Flashes / 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 25.2817% — below the 40% mark we flag

Spend your practice time on Anubis

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
anubis	13–11	-0.04	8%	28 Aug →
mirage	14–16	0.03	20%	27 Aug →
ancient	13–9	0.03	33%	5 Aug →
ancient	4–13	-0.07	24%	5 Aug →
cache	16–13	-0.04	25%	5 Aug →
nuke	8–13	-0.05	24%	4 Aug →
inferno	13–10	-0.02	29%	4 Aug →
inferno	10–13	-0.05	24%	3 Aug →
ancient	13–7	-0.07	23%	3 Aug →
cache	13–8	-0.04	18%	3 Aug →
inferno	13–10	-0.03	16%	3 Aug →
nuke	11–13	-0.06	23%	3 Aug →
nuke	10–8	-0.01	17%	15 Jun →
ancient	16–14	-0.02	19%	15 Jun →
anubis	8–13	-0.03	28%	15 Jun →
anubis	9–13	-0.06	17%	4 Jun →
mirage	13–6	0.04	19%	4 Jun →
ancient	11–13	0.04	39%	4 Jun →
inferno	13–9	0.04	21%	15 May →
ancient	13–11	-0.02	18%	13 May →
anubis	12–16	0.01	10%	12 May →
cache	2–13	-0.07	10%	12 May →
inferno	8–13	-0.04	8%	11 May →
inferno	13–0	0.03	24%	11 May →
mirage	13–2	0.06	14%	11 May →
inferno	13–7	0.10	19%	10 May →
cache	10–13	-0.04	28%	9 May →
nuke	13–1	0.09	25%	9 May →
cache	13–8	0.00	24%	8 May →
dust2	13–11	-0.03	35%	8 May →
nuke	10–13	-0.00	12%	19 Apr →
inferno	7–13	-0.01	14%	18 Apr →
overpass	8–13	-0.00	10%	14 Apr →
inferno	13–2	0.04	20%	10 Apr →
ancient	11–13	0.14	13%	23 Mar →
mirage	8–13	-0.04	13%	23 Mar →
ancient	8–13	-0.02	16%	22 Mar →
ancient	13–9	0.03	29%	19 Mar →
nuke	13–9	-0.07	18%	17 Mar →
inferno	10–13	0.02	20%	17 Mar →
nuke	13–10	0.02	25%	13 Mar →
ancient	7–13	-0.02	17%	12 Mar →
overpass	13–8	0.01	24%	12 Mar →
overpass	11–13	0.01	14%	21 Feb →
inferno	11–13	0.00	25%	21 Feb →
dust2	13–7	0.10	27%	19 Feb →
nuke	8–13	-0.05	9%	14 Feb →
dust2	3–13	-0.04	14%	14 Feb →
inferno	13–5	0.05	12%	13 Feb →
inferno	15–15	-0.00	18%	23 Jan →
ancient	13–0	-0.03	23%	23 Jan →
ancient	4–13	0.06	19%	28 Dec →
train	13–11	0.07	19%	24 Dec →
ancient	10–13	-0.06	8%	23 Dec →
train	16–14	-0.02	24%	23 Dec →
ancient	7–13	0.03	20%	22 Dec →
inferno	13–3	0.11	29%	22 Dec →
nuke	13–9	0.02	22%	21 Dec →
nuke	13–5	0.04	19%	21 Dec →
dust2	10–13	0.09	22%	20 Dec →
inferno	13–5	0.03	12%	19 Dec →
train	13–8	0.02	20%	18 Dec →
mirage	0–8	0.00	0%	18 Dec →
inferno	14–16	0.04	15%	18 Dec →
dust2	5–13	-0.08	11%	18 Dec →
ancient	10–13	-0.06	24%	18 Dec →
mirage	13–10	0.01	16%	18 Dec →
ancient	13–9	0.02	25%	18 Dec →
inferno	13–6	0.06	21%	18 Dec →
nuke	8–5	0.01	11%	18 Dec →
dust2	13–10	-0.02	17%	18 Dec →
train	7–13	-0.04	20%	1 Dec →
ancient	5–13	-0.07	18%	1 Dec →
mirage	7–13	-0.03	18%	1 Dec →
nuke	4–13	-0.06	28%	29 Nov →
inferno	8–13	0.05	11%	29 Nov →
inferno	13–0	-0.01	24%	29 Nov →
ancient	13–11	0.04	11%	29 Nov →
inferno	9–13	-0.12	21%	29 Nov →
nuke	10–13	0.08	13%	28 Nov →
dust2	9–13	0.07	23%	28 Nov →
ancient	13–8	-0.01	21%	27 Nov →
overpass	9–13	0.03	10%	27 Nov →
train	13–2	0.14	24%	27 Nov →
anubis	1–4	-0.02	7%	27 Nov →
dust2	8–13	-0.01	17%	27 Nov →
ancient	13–9	-0.03	17%	26 Nov →
nuke	13–4	0.06	18%	26 Nov →
inferno	13–4	0.07	15%	26 Nov →
mirage	9–13	-0.05	20%	26 Nov →
inferno	13–6	-0.01	19%	26 Nov →
inferno	13–8	0.02	17%	25 Nov →
nuke	5–13	0.00	13%	25 Nov →
train	13–9	-0.03	12%	25 Nov →
nuke	13–11	0.05	14%	24 Nov →
dust2	4–13	-0.02	16%	24 Nov →
train	5–13	0.04	13%	24 Nov →
ancient	9–13	0.02	12%	24 Nov →
inferno	6–13	0.04	25%	23 Nov →
inferno	8–13	-0.02	17%	23 Nov →