cr1es — CS2 Stats

76561198136471595[U:1:176205867]✓ No bans

1,229Tracked matches30%Win rate2020Tracked since

CSDB Rating4.7 DevelopingHybrid Rifler

FaceitLevel 10 · 2,163 ELOTop 12.4% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim66

Positioning66

Utility12

0–100 skill scores via Leetify.

Recent form

COLD43–57Last 10043%Win rateLLLWLWLLWL

Last 10 vs previous 10: -20pp win rate · +0.01 avg rating

Player DNA

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

Aim6.6

Aggression9.0

Utility1.2

Positioning6.6

Opening Duels3.9

Clutch3.8

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 jL 83% playstyle similarity

Most alike: opening-duel success, 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. 583ms 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

Positioning6.6

Utility1.2

Mechanics5.5

Opening Duels3.9

Win Impact0.0

Composite 4.7/10 (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 rating0.01−0.01

first ⅓ avg 0.02 → last ⅓ avg 0.01

Reaction time585ms+29ms

first ⅓ avg 557ms → last ⅓ avg 585ms

Headshot accuracy22.8%−2.5%

first ⅓ avg 25.4% → last ⅓ avg 22.8%

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 — ancient 13–3

13–1Biggest win — inferno

5Longest win streak

L3Current streak

4–7In matches decided by ≤2 rounds

15Overtime games

Map breakdown

overpassBest map · 69% over 13nukeWeakest map · 13% over 15

Map	Grade	Played	Record	Win rate	Avg rating
ancient	B	30	14–16	47%	0.02
inferno	C	19	7–12	37%	0.02
mirage	B	16	8–8	50%	0.02
nuke	D	15	2–13	13%	-0.00
overpass	S	13	9–4	69%	0.03
anubis	—	3	1–2	33%	0.03
dust2	—	2	1–1	50%	-0.00
train	—	1	0–1	0%	-0.05
vertigo	—	1	1–0	100%	0.01

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (13% over 15). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

2,893Matches

51%Win rate

1.27Avg K/D

84.3ADR

44%Headshot %

Clutches & streaks

39%1v1 clutch win

21%1v2 clutch win

10Longest win streak

Recent Faceit resultsWWWLW

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	138	53%	1.49	19.1
Mirage	111	53%	1.26	18.1
Ancient	111	50%	1.33	16.9
Nuke	81	51%	1.37	19.2
Dust2	46	39%	1.30	18.7
Overpass	39	64%	1.44	20.2
Train	24	42%	1.25	18.8
Anubis	11	36%	1.07	16.8

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.

23.0%Headshot accuracy

32.7%Accuracy (enemy spotted)

30.5%Spray accuracy

74.9%Counter-strafing

9.6°Preaim

583msReaction time

45.6%T opening success

45.2%CT opening success

0.58Enemies flashed / flash

3.3%Flash assists

9.22HE damage / grenade

2.78Flashes / 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
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 2.7767 — below the 4 mark we flag
Grenade Lineups →

Spend your practice time on Nuke

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

13% win rate across 15 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
overpass	6–12	0.04	30%	18 Nov →
nuke	4–13	0.01	35%	26 Oct →
nuke	4–12	-0.04	21%	22 Oct →
inferno	13–2	0.10	24%	19 Oct →
nuke	5–13	0.05	31%	13 Oct →
nuke	16–13	0.03	29%	9 Sept →
nuke	9–13	0.04	33%	24 Aug →
ancient	11–13	0.01	30%	6 Aug →
mirage	13–7	-0.01	30%	29 Jul →
inferno	9–13	-0.03	18%	9 Jun →
inferno	9–13	-0.02	25%	30 May →
inferno	7–12	-0.02	29%	29 May →
inferno	13–5	0.09	18%	24 May →
inferno	13–11	0.02	8%	23 May →
nuke	5–12	-0.03	31%	9 May →
ancient	9–13	-0.04	22%	7 May →
inferno	13–7	0.10	33%	26 Apr →
ancient	10–13	-0.02	20%	25 Apr →
mirage	13–10	0.01	11%	20 Apr →
dust2	13–8	0.02	18%	5 Apr →
mirage	13–16	-0.04	17%	5 Apr →
dust2	7–13	-0.02	30%	5 Apr →
ancient	5–13	-0.00	26%	30 Mar →
ancient	4–13	-0.01	29%	29 Mar →
train	5–13	-0.05	10%	23 Mar →
nuke	9–13	-0.02	24%	29 Aug →
nuke	8–13	-0.03	12%	22 Aug →
nuke	10–13	-0.01	16%	22 Jul →
inferno	13–4	0.12	20%	21 Jul →
ancient	6–13	-0.00	16%	9 Jul →
vertigo	16–13	0.01	23%	8 Jul →
inferno	16–19	0.00	22%	8 Jul →
nuke	7–13	-0.02	12%	27 Jun →
ancient	13–6	0.03	21%	24 Jun →
anubis	14–16	0.01	28%	21 Jun →
nuke	17–19	-0.01	19%	10 Jun →
ancient	9–13	-0.02	23%	10 Jun →
inferno	11–13	0.03	14%	4 Jun →
anubis	10–13	-0.00	22%	9 May →
anubis	13–8	0.09	40%	2 May →
inferno	13–1	0.02	17%	2 May →
ancient	9–13	-0.03	23%	1 May →
mirage	13–2	0.10	15%	1 May →
overpass	8–13	0.03	26%	4 Dec →
mirage	7–13	0.01	50%	4 Dec →
ancient	13–7	0.02	55%	3 Dec →
mirage	10–13	-0.03	33%	1 Dec →
ancient	9–13	0.06	19%	1 Dec →
ancient	13–16	-0.00	31%	1 Dec →
ancient	6–13	0.02	32%	1 Dec →
inferno	10–13	0.03	24%	29 Nov →
nuke	9–13	0.05	18%	29 Nov →
overpass	13–9	0.02	56%	29 Nov →
ancient	22–18	0.01	25%	24 Nov →
overpass	13–11	-0.01	25%	24 Nov →
mirage	13–16	0.00	35%	22 Nov →
ancient	13–4	0.00	21%	21 Nov →
ancient	13–10	0.04	28%	21 Nov →
ancient	3–13	-0.04	18%	21 Nov →
overpass	3–13	-0.06	50%	20 Nov →
ancient	13–3	0.12	36%	19 Nov →
overpass	16–13	0.03	19%	18 Nov →
ancient	13–4	0.09	19%	18 Nov →
ancient	13–9	0.07	30%	17 Nov →
inferno	7–13	-0.00	24%	17 Nov →
mirage	13–10	0.02	21%	16 Nov →
overpass	13–10	0.04	21%	14 Nov →
inferno	3–13	-0.05	39%	14 Nov →
mirage	13–9	0.01	27%	14 Nov →
mirage	8–13	0.03	42%	14 Nov →
overpass	13–3	0.10	42%	13 Nov →
ancient	9–13	0.02	24%	12 Nov →
inferno	5–13	-0.03	0%	12 Nov →
mirage	7–13	0.02	17%	11 Nov →
ancient	1–13	-0.02	32%	9 Nov →
overpass	13–7	0.03	19%	9 Nov →
ancient	11–13	-0.04	21%	8 Nov →
ancient	13–5	0.11	19%	7 Nov →
mirage	13–7	0.08	40%	6 Nov →
ancient	13–9	0.06	22%	3 Nov →
inferno	4–12	-0.03	24%	2 Nov →
ancient	13–9	-0.03	22%	1 Nov →
inferno	16–18	0.00	0%	1 Nov →
ancient	9–13	0.05	29%	1 Nov →
ancient	13–7	0.10	17%	31 Oct →
nuke	12–16	0.00	22%	30 Oct →
nuke	13–16	-0.03	16%	29 Oct →
mirage	13–4	0.02	13%	29 Oct →
ancient	16–14	0.03	38%	29 Oct →
overpass	13–11	0.06	35%	29 Oct →
nuke	13–6	-0.05	18%	29 Oct →
mirage	8–13	-0.01	15%	28 Oct →
mirage	13–10	0.05	44%	27 Oct →
inferno	13–4	0.02	50%	28 Sept →
overpass	13–7	0.02	21%	27 Sept →
ancient	13–5	0.11	41%	26 Sept →
overpass	13–7	0.03	25%	24 Sept →
mirage	12–16	0.02	19%	23 Sept →
overpass	11–13	0.01	19%	23 Sept →
inferno	10–13	-0.01	27%	22 Sept →