Rzor™ — CS2 Stats

76561198103663114[U:1:143397386]

496Tracked matches46%Win rate2021Tracked since

CSDB Rating5.3 DevelopingHybrid Rifler

Ladder ranks via Leetify

Performance scores

Aim66

Positioning48

Utility42

0–100 skill scores via Leetify.

Recent form

STEADY41–48–11Last 10041%Win rateWLLWLLWWLT

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

Player DNA

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

Aim6.6

Aggression6.7

Utility4.2

Positioning4.8

Opening Duels1.7

Clutch6.0

Strong CT-side opener

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 Twistzz 84% playstyle similarity

Most alike: opening-fight frequency, opening-duel success.

Where you differ: lower aim profile; lower utility contribution.

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 49% on CT to 25% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 685ms 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

Aim6.6

Positioning4.8

Utility4.2

Mechanics7.3

Opening Duels2.4

Win Impact3.8

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 rating-0.02−0.01

first ⅓ avg -0.00 → last ⅓ avg -0.02

Reaction time675ms+23ms

first ⅓ avg 652ms → last ⅓ avg 675ms

Headshot accuracy20.0%+1.3%

first ⅓ avg 18.7% → last ⅓ avg 20.0%

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

0.12Best rating — inferno 13–5

13–0Biggest win — overpass

4Longest win streak

6–8In matches decided by ≤2 rounds

5Overtime games

Map breakdown

mirageBest map · 50% over 18ancientWeakest map · 20% over 5

Map	Grade	Played	Record	Win rate	Avg rating
dust2	D	35	9–26	26%	-0.02
mirage	B	18	9–9	50%	-0.01
nuke	C	14	6–8	43%	0.02
inferno	C	12	5–7	42%	-0.01
ancient	D	5	1–4	20%	-0.03
anubis	—	4	2–2	50%	0.03
overpass	—	2	2–0	100%	-0.04
vertigo	—	2	2–0	100%	0.06
train	—	2	2–0	100%	-0.01
cache	—	1	1–0	100%	-0.04
agency	—	1	1–0	100%	-0.01
office	—	1	1–0	100%	0.01
golden	—	1	0–1	0%	0.02
palacio	—	1	0–1	0%	-0.09
italy	—	1	0–1	0%	0.05

Across the last 100 tracked matches.

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

Faceit stats

Combat

17Matches

53%Win rate

0.98Avg K/D

82.0ADR

44%Headshot %

Clutches & streaks

50%1v1 clutch win

15%1v2 clutch win

3Longest win streak

Recent Faceit resultsWWLWW

Map	Matches	Win rate	Avg K/D	Avg kills
Mirage	4	50%	1.18	18.3
Inferno	3	67%	0.92	13.7
Train	2	50%	0.61	10.0
Nuke	2	100%	1.32	17.0
Vertigo	2	50%	0.82	14.5
Anubis	2	50%	0.86	18.0
Dust2	1	0%	0.53	8.0
Ancient	1	0%	1.41	24.0

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.

19.5%Headshot accuracy

37.5%Accuracy (enemy spotted)

33.9%Spray accuracy

83.0%Counter-strafing

10.3°Preaim

685msReaction time

24.8%T opening success

49.2%CT opening success

0.63Enemies flashed / flash

2.3%Flash assists

9.12HE damage / grenade

10.05Flashes / 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 24.7635% — 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.

20% win rate across 5 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
cache	13–9	-0.04	16%	23 Jul →
dust2	3–13	-0.09	14%	22 Jul →
ancient	11–13	-0.01	17%	22 Jul →
dust2	13–1	0.04	18%	16 Jul →
mirage	10–13	-0.02	25%	21 Jun →
dust2	10–13	-0.05	15%	21 Jun →
nuke	13–7	-0.01	32%	13 Apr →
inferno	16–14	0.00	27%	12 Feb →
dust2	2–13	-0.09	18%	22 Jan →
mirage	12–12	-0.05	13%	22 Jan →
dust2	5–13	-0.04	22%	22 Jan →
dust2	13–9	0.07	17%	22 Jan →
nuke	12–12	0.02	26%	22 Jan →
inferno	0–7	-0.05	38%	21 Jan →
dust2	4–13	-0.01	12%	21 Jan →
mirage	13–10	0.01	16%	20 Jan →
dust2	13–5	-0.00	19%	20 Jan →
dust2	13–11	0.04	15%	20 Jan →
mirage	13–8	-0.05	9%	20 Jan →
ancient	8–13	-0.05	15%	20 Jan →
nuke	2–13	0.02	23%	20 Jan →
anubis	13–5	0.04	16%	18 Jan →
agency	13–5	-0.01	15%	18 Jan →
office	13–5	0.01	20%	18 Jan →
overpass	13–8	-0.05	18%	18 Jan →
golden	6–13	0.02	11%	18 Jan →
palacio	11–13	-0.09	19%	18 Jan →
italy	8–13	0.05	23%	18 Jan →
dust2	0–8	-0.02	43%	13 Jan →
dust2	11–13	-0.02	32%	13 Jan →
nuke	13–8	0.08	23%	13 Jan →
ancient	4–13	-0.09	17%	13 Jan →
dust2	7–13	-0.07	18%	13 Jan →
dust2	11–13	-0.08	16%	12 Jan →
dust2	12–12	-0.04	9%	12 Jan →
dust2	12–12	-0.03	16%	12 Jan →
inferno	10–13	-0.07	13%	8 Jan →
dust2	8–13	0.00	7%	8 Jan →
inferno	13–5	0.12	21%	8 Jan →
dust2	13–4	0.01	19%	8 Jan →
inferno	3–13	-0.05	14%	8 Jan →
dust2	13–11	-0.05	12%	8 Jan →
nuke	10–13	-0.04	14%	7 Jan →
vertigo	13–10	0.03	26%	1 Jan →
vertigo	13–3	0.08	14%	1 Jan →
dust2	12–12	0.04	20%	1 Jan →
inferno	12–12	0.02	15%	1 Jan →
mirage	13–8	0.07	27%	1 Jan →
overpass	13–0	-0.02	8%	1 Jan →
dust2	5–13	-0.00	23%	31 Dec →
nuke	13–5	-0.02	29%	31 Dec →
dust2	8–13	-0.06	27%	31 Dec →
dust2	5–13	0.02	31%	31 Dec →
nuke	6–13	0.06	25%	31 Dec →
dust2	9–13	-0.02	23%	11 Dec →
dust2	6–13	-0.03	14%	11 Dec →
nuke	13–7	0.06	24%	27 Nov →
dust2	4–13	-0.01	22%	11 Nov →
nuke	11–13	-0.02	15%	11 Nov →
dust2	13–11	0.01	21%	11 Nov →
dust2	11–4	-0.02	19%	10 Nov →
dust2	12–12	-0.04	18%	9 Nov →
dust2	3–13	-0.05	12%	20 Sept →
mirage	1–13	-0.04	16%	18 Jul →
nuke	13–8	0.04	13%	14 Jul →
nuke	12–12	-0.01	15%	14 Jul →
mirage	7–13	-0.07	18%	21 Jun →
dust2	13–10	-0.03	4%	21 Jun →
mirage	13–7	-0.02	9%	20 Jun →
mirage	13–10	0.08	11%	7 Jun →
dust2	15–15	0.01	12%	7 Jun →
mirage	13–4	0.03	18%	7 Jun →
mirage	13–2	0.02	25%	7 Jun →
inferno	7–1	0.06	15%	7 Jun →
dust2	11–13	0.00	14%	7 Jun →
anubis	8–13	0.11	23%	7 Jun →
mirage	8–13	-0.10	19%	7 Jun →
ancient	10–13	-0.01	13%	7 Jun →
inferno	13–6	0.03	21%	22 May →
nuke	13–10	-0.00	29%	22 May →
mirage	4–13	-0.05	36%	22 May →
train	5–0	-0.01	17%	22 May →
nuke	11–13	0.02	26%	19 May →
train	13–4	-0.02	12%	19 May →
dust2	15–15	0.04	22%	18 May →
dust2	6–13	0.03	39%	15 May →
mirage	16–14	0.03	19%	14 May →
anubis	5–13	-0.04	17%	14 May →
mirage	8–13	-0.03	21%	14 May →
mirage	13–6	-0.01	12%	14 May →
mirage	10–13	-0.06	3%	14 May →
inferno	5–13	-0.00	26%	6 May →
nuke	11–13	0.06	22%	6 May →
inferno	2–13	-0.09	38%	4 May →
dust2	8–13	-0.06	20%	3 May →
inferno	13–7	-0.05	14%	3 May →
anubis	13–10	0.00	13%	3 May →
inferno	6–13	-0.08	16%	3 May →
mirage	15–15	-0.01	20%	3 May →
ancient	13–11	0.00	13%	3 May →