Ren1 — CS2 Stats

DE76561198052145753[U:1:91880025]Steam profile ↗✓ No bans

4,308Tracked matches50%Win rate2020Tracked since

CSDB Rating5.3 DevelopingPassive Rifler

FaceitLevel 9 · 2,088 ELOTop 20.7% of ranked FACEIT players

WingmanSupreme Master First Class

Ladder ranks via Leetify

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Performance scores

Aim72

Positioning50

Utility35

0–100 skill scores via Leetify.

Recent form

COLD44–49–7Last 10044%Win rateWLLWLLLLLW

Last 10 vs previous 10: -20pp win rate · -0.05 avg rating

Player DNA

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

Aim7.2

Aggression4.2

Utility3.5

Positioning5.0

Opening Duels0.5

Clutch4.2

Limited 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 NiKo 84% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

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

Aim7.2

Positioning5.0

Utility3.5

Mechanics6.8

Opening Duels0.7

Win Impact5.0

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 rating-0.01−0.02

first ⅓ avg 0.01 → last ⅓ avg -0.01

Reaction time556ms−24ms

first ⅓ avg 580ms → last ⅓ avg 556ms

Headshot accuracy20.1%−3.3%

first ⅓ avg 23.4% → last ⅓ avg 20.1%

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

0.17Best rating — anubis 13–2

13–1Biggest win — dust2

6Longest win streak

5–10In matches decided by ≤2 rounds

8Overtime games

Map breakdown

infernoBest map · 64% over 11mirageWeakest map · 14% over 7

Map	Grade	Played	Record	Win rate	Avg rating
cache	C	27	10–17	37%	0.01
ancient	C	18	8–10	44%	-0.02
dust2	A	12	7–5	58%	-0.00
inferno	A	11	7–4	64%	0.00
anubis	C	9	4–5	44%	0.01
nuke	C	8	3–5	38%	-0.04
mirage	D	7	1–6	14%	0.00
office	—	3	1–2	33%	0.02
overpass	—	3	2–1	67%	0.01
italy	—	1	1–0	100%	-0.10
train	—	1	0–1	0%	-0.06

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (14% over 7). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

5,249Matches

50%Win rate

1.04Avg K/D

70.5ADR

49%Headshot %

Clutches & streaks

41%1v1 clutch win

22%1v2 clutch win

9Longest win streak

Recent Faceit resultsLWWWW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	384	51%	0.98	14.8
Inferno	308	51%	1.02	14.8
Anubis	301	50%	1.06	15.2
Nuke	186	52%	0.99	13.8
Dust2	149	40%	0.91	13.7
Overpass	110	52%	1.05	14.6
Mirage	89	45%	0.88	13.5
Vertigo	65	49%	1.00	14.5

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

33.9%Accuracy (enemy spotted)

36.9%Spray accuracy

80.7%Counter-strafing

10.2°Preaim

564msReaction time

28.5%T opening success

35.2%CT opening success

0.40Enemies flashed / flash

2.5%Flash assists

6.53HE damage / grenade

4.41Flashes / 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 0.399 — 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 28.4544% — below the 40% mark we flag

Spend your practice time on Mirage

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

14% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
italy	9–9	-0.10	20%	19 Aug →
train	4–13	-0.06	14%	19 Aug →
office	5–13	-0.05	26%	19 Aug →
inferno	13–8	-0.04	13%	17 Aug →
nuke	3–13	-0.05	7%	14 Aug →
dust2	14–16	-0.02	28%	11 Aug →
anubis	14–16	-0.04	16%	10 Aug →
dust2	11–13	0.01	25%	10 Aug →
ancient	10–13	-0.07	21%	5 Aug →
nuke	13–9	-0.02	13%	2 Aug →
ancient	13–10	0.05	13%	31 Jul →
mirage	9–13	0.03	15%	28 Jul →
nuke	13–10	-0.03	11%	27 Jul →
dust2	13–1	0.07	27%	27 Jul →
cache	13–3	0.02	15%	27 Jul →
inferno	13–4	-0.02	21%	26 Jul →
inferno	11–13	-0.01	24%	21 Jul →
mirage	9–13	0.03	22%	20 Jul →
anubis	9–13	-0.00	13%	18 Jul →
ancient	13–16	-0.05	19%	17 Jul →
dust2	13–10	0.02	26%	17 Jul →
ancient	13–10	0.03	19%	14 Jul →
ancient	13–11	-0.01	22%	11 Jul →
mirage	13–10	-0.01	19%	10 Jul →
cache	11–13	-0.04	19%	10 Jul →
dust2	13–2	0.06	19%	10 Jul →
dust2	13–11	0.04	28%	7 Jul →
anubis	10–13	-0.06	21%	4 Jul →
ancient	13–9	0.01	21%	3 Jul →
dust2	4–13	-0.04	27%	26 Jun →
ancient	13–6	-0.02	22%	25 Jun →
inferno	10–13	-0.02	26%	25 Jun →
mirage	0–6	0.01	33%	25 Jun →
ancient	8–13	-0.03	25%	22 Jun →
inferno	13–11	0.06	20%	18 Jun →
ancient	13–10	-0.03	14%	14 Jun →
ancient	0–13	-0.04	25%	7 Jun →
cache	13–9	-0.00	22%	2 Jun →
overpass	13–9	0.07	30%	2 Jun →
dust2	13–9	-0.02	31%	30 May →
anubis	13–16	-0.00	18%	30 May →
cache	5–13	-0.05	22%	30 May →
cache	11–13	-0.01	20%	30 May →
anubis	11–13	-0.02	22%	28 May →
inferno	15–15	-0.02	27%	28 May →
mirage	10–13	-0.06	21%	28 May →
ancient	5–13	-0.02	18%	28 May →
ancient	4–13	-0.09	30%	23 May →
nuke	11–13	0.03	14%	22 May →
ancient	5–13	-0.01	10%	22 May →
cache	6–13	-0.03	14%	21 May →
cache	13–8	-0.00	29%	20 May →
nuke	0–13	-0.03	0%	17 May →
nuke	13–9	-0.06	38%	17 May →
cache	4–13	-0.00	24%	15 May →
cache	6–13	-0.01	21%	15 May →
cache	13–8	0.03	16%	15 May →
cache	12–12	-0.05	16%	14 May →
cache	4–13	0.01	20%	14 May →
cache	13–3	-0.02	19%	14 May →
cache	13–9	0.03	23%	14 May →
cache	13–3	0.02	22%	14 May →
overpass	13–6	-0.02	17%	14 May →
cache	8–13	0.06	24%	13 May →
cache	13–6	0.11	28%	13 May →
cache	12–12	0.07	24%	13 May →
cache	12–12	-0.03	19%	13 May →
cache	6–13	-0.00	20%	9 May →
anubis	13–10	-0.03	14%	9 May →
inferno	13–8	-0.01	25%	9 May →
inferno	13–5	0.11	21%	9 May →
dust2	13–10	-0.04	22%	8 May →
cache	13–1	0.15	19%	8 May →
cache	13–6	0.00	24%	7 May →
cache	5–13	-0.02	27%	7 May →
nuke	10–13	-0.06	32%	5 May →
cache	12–12	0.02	25%	4 May →
cache	12–12	0.00	26%	3 May →
cache	6–13	0.05	26%	3 May →
anubis	16–12	0.05	24%	3 May →
inferno	13–1	0.10	21%	2 May →
cache	8–13	-0.03	27%	1 May →
dust2	9–13	-0.06	24%	28 Apr →
ancient	3–13	-0.04	16%	27 Apr →
mirage	5–13	-0.03	23%	26 Apr →
anubis	13–2	0.17	13%	26 Apr →
anubis	13–11	0.02	21%	26 Apr →
office	13–8	0.02	40%	26 Apr →
overpass	14–16	-0.04	18%	23 Apr →
ancient	3–13	-0.08	40%	23 Apr →
inferno	13–10	-0.04	19%	23 Apr →
dust2	8–13	-0.04	33%	20 Apr →
ancient	8–13	0.07	20%	16 Apr →
ancient	13–4	0.01	16%	14 Apr →
inferno	9–13	-0.06	31%	14 Apr →
mirage	14–16	0.04	26%	13 Apr →
nuke	5–13	-0.07	11%	13 Apr →
office	12–12	0.08	30%	13 Apr →
dust2	13–8	0.01	20%	13 Apr →
ancient	13–10	0.01	19%	13 Apr →