Hypest Hype — CS2 Stats

76561197985192237[U:1:24926509]Steam profile ↗✓ No bans

1,033Tracked matches48%Win rate2020Tracked since

CSDB Rating5.5 SolidHybrid Rifler

FaceitLevel 8 · 2,116 ELOTop 31.2% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim60

Positioning56

Utility64

0–100 skill scores via Leetify.

Recent form

STEADY50–47–3Last 10050%Win rateWLLWLLWLWW

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.

Aim6.0

Aggression5.5

Utility6.4

Positioning5.6

Opening Duels2.9

Clutch2.8

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 NiKo 91% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: 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

T-side openings. Opening success drops from 52% on CT to 31% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 633ms 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

Aim6.0

Positioning5.6

Utility6.4

Mechanics6.0

Opening Duels2.9

Win Impact4.4

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 rating0.00+0.03

first ⅓ avg -0.03 → last ⅓ avg 0.00

Reaction time638ms+85ms

first ⅓ avg 554ms → last ⅓ avg 638ms

Headshot accuracy18.1%−1.2%

first ⅓ avg 19.3% → last ⅓ avg 18.1%

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

0.19Best rating — inferno 13–1

13–1Biggest win — inferno

5Longest win streak

9–8In matches decided by ≤2 rounds

14Overtime games

Map breakdown

mirageBest map · 83% over 6anubisWeakest map · 29% over 14

Map	Grade	Played	Record	Win rate	Avg rating
inferno	A	17	10–7	59%	0.00
ancient	C	16	7–9	44%	-0.02
nuke	B	16	8–8	50%	-0.01
anubis	D	14	4–10	29%	0.00
dust2	A	14	8–6	57%	0.01
vertigo	C	9	4–5	44%	-0.03
mirage	S	6	5–1	83%	0.06
overpass	A	5	3–2	60%	0.00
cache	—	2	1–1	50%	0.01
train	—	1	0–1	0%	0.01

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (29% over 14). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,148Matches

52%Win rate

0.93Avg K/D

65.2ADR

47%Headshot %

Clutches & streaks

34%1v1 clutch win

14%1v2 clutch win

8Longest win streak

Recent Faceit resultsLLWWL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	156	62%	0.95	13.3
Nuke	113	60%	0.98	14.2
Ancient	110	53%	0.93	13.9
Dust2	81	44%	0.81	13.1
Vertigo	42	57%	0.90	13.3
Anubis	36	17%	0.81	12.8
Mirage	24	50%	0.82	12.1
Overpass	17	41%	0.79	12.9

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.

17.9%Headshot accuracy

35.0%Accuracy (enemy spotted)

37.8%Spray accuracy

77.1%Counter-strafing

11.1°Preaim

633msReaction time

30.7%T opening success

52.2%CT opening success

0.59Enemies flashed / flash

10.0%Flash assists

10.62HE damage / grenade

10.08Flashes / 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 30.7309% — 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.

29% win rate across 14 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
ancient	13–2	0.04	9%	24 Jul →
anubis	2–13	-0.08	9%	17 Jul →
ancient	8–13	0.02	19%	12 Jul →
overpass	16–14	-0.04	23%	3 Jul →
overpass	10–13	0.00	13%	28 Jun →
anubis	5–13	-0.03	14%	26 Jun →
anubis	13–8	0.03	27%	26 Jun →
anubis	7–13	-0.01	25%	23 Jun →
cache	13–10	0.03	19%	22 Jun →
dust2	13–7	-0.03	16%	14 May →
cache	14–16	-0.00	17%	24 Apr →
dust2	13–11	0.04	11%	5 Apr →
inferno	13–1	0.19	33%	4 Apr →
anubis	10–13	0.09	24%	4 Apr →
inferno	12–12	-0.05	14%	4 Apr →
dust2	4–13	-0.07	14%	30 Mar →
ancient	13–9	-0.01	11%	23 Mar →
dust2	1–13	0.01	25%	23 Mar →
dust2	19–16	0.01	18%	4 Mar →
ancient	7–13	-0.08	10%	4 Mar →
dust2	6–13	0.04	28%	12 Feb →
anubis	5–13	0.04	31%	5 Feb →
dust2	13–8	0.01	28%	2 Feb →
inferno	13–9	0.02	18%	31 Jan →
nuke	10–13	-0.03	10%	31 Jan →
ancient	8–13	-0.04	9%	29 Jan →
dust2	4–13	-0.05	23%	23 Jan →
overpass	16–14	0.00	9%	21 Jan →
inferno	13–11	0.03	15%	18 Jan →
nuke	13–8	0.02	25%	11 Jan →
inferno	13–10	0.02	12%	10 Jan →
inferno	17–19	-0.05	16%	30 Dec →
train	10–13	0.01	21%	14 Dec →
nuke	13–7	0.06	22%	5 Aug →
inferno	11–13	-0.02	20%	5 Aug →
ancient	10–13	-0.06	29%	4 Jul →
mirage	13–7	0.11	19%	11 Jun →
anubis	15–15	0.04	15%	5 Jun →
dust2	13–8	0.02	35%	2 Jun →
nuke	13–4	0.08	20%	1 Jun →
inferno	13–9	0.07	19%	31 May →
mirage	13–11	-0.02	16%	29 May →
dust2	13–10	0.04	22%	29 May →
inferno	4–10	-0.02	13%	11 May →
dust2	8–13	-0.04	24%	10 May →
ancient	9–1	-0.02	22%	10 May →
anubis	14–16	-0.03	22%	10 May →
mirage	13–1	0.04	40%	10 May →
inferno	13–6	0.04	21%	8 May →
inferno	13–16	-0.03	22%	28 Apr →
ancient	7–13	-0.00	11%	15 Apr →
anubis	8–13	-0.04	14%	9 Apr →
ancient	11–13	0.00	14%	23 Mar →
nuke	13–2	0.01	13%	23 Mar →
dust2	13–5	0.02	16%	18 Mar →
ancient	11–13	-0.05	30%	11 Mar →
inferno	9–13	-0.01	23%	7 Feb →
nuke	4–13	-0.06	16%	7 Feb →
dust2	15–19	0.01	17%	26 Jan →
vertigo	13–11	0.02	16%	6 Jan →
vertigo	3–13	-0.03	26%	5 Jan →
mirage	12–12	0.08	24%	4 Jan →
dust2	13–9	0.10	30%	26 Dec →
mirage	9–1	0.13	15%	26 Dec →
nuke	13–8	0.05	21%	20 Dec →
vertigo	13–11	-0.01	23%	7 Dec →
nuke	19–15	-0.01	17%	27 Nov →
inferno	14–16	-0.05	21%	21 Nov →
vertigo	13–7	-0.01	23%	19 May →
inferno	13–10	-0.08	3%	21 Apr →
anubis	13–10	0.00	30%	7 Apr →
nuke	13–9	-0.01	21%	6 Apr →
nuke	5–13	-0.05	38%	10 Mar →
nuke	1–10	-0.14	18%	6 Mar →
ancient	13–7	-0.01	21%	3 Mar →
nuke	10–13	-0.05	20%	3 Mar →
nuke	9–13	-0.05	8%	2 Mar →
inferno	16–14	-0.05	10%	2 Mar →
anubis	13–10	0.06	27%	2 Mar →
overpass	13–9	0.08	16%	1 Mar →
nuke	10–13	0.02	18%	1 Mar →
vertigo	9–13	-0.13	26%	1 Mar →
ancient	13–10	-0.07	19%	1 Mar →
mirage	16–13	0.01	14%	29 Feb →
ancient	13–11	-0.03	14%	29 Feb →
ancient	10–13	-0.04	10%	29 Feb →
nuke	13–8	-0.02	22%	27 Feb →
anubis	13–4	0.02	15%	27 Feb →
vertigo	7–13	-0.05	30%	27 Feb →
vertigo	14–16	0.03	38%	25 Feb →
anubis	1–13	-0.05	24%	25 Feb →
ancient	13–6	-0.03	18%	25 Feb →
inferno	13–9	0.02	18%	22 Feb →
vertigo	13–9	-0.03	24%	22 Feb →
nuke	10–13	-0.04	11%	22 Feb →
inferno	13–9	-0.01	0%	22 Feb →
anubis	5–13	0.01	22%	21 Feb →
vertigo	4–13	-0.07	25%	20 Feb →
overpass	6–13	-0.04	13%	20 Feb →
ancient	7–13	-0.02	20%	20 Feb →