`Vayra — CS2 Stats

76561198004635034[U:1:44369306]Steam profile ↗✓ No bans

1,598Tracked matches47%Win rate2021Tracked since

2,346Hours in CS8Hrs last 2 wks

CSDB Rating7.3 StrongSupport

Premier CS Rating26,528Top 5% of 212,695 CSDB-tracked playersRed band · top ~2.3% of ranked players (population est.)

CSDB Leaderboard#9621 of 259565 tracked

FaceitLevel 10 · 2,075 ELOTop 12.4% of ranked FACEIT players

WingmanSupreme Master First Class

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 1 Nov 2026 (yesterday). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 26,528 -637 1 Jul – 1 Nov · 26 days played

Faceit ELO: 2,075 +0 2 Sept – 19 Oct · 3 observations

27,356Peak Premier in tracked matches

2,075Highest Faceit ELO seen on CSDB

32Days played since 2026-06-30

Faceit ELO

At peak — 2,075
Next: 2,500 ELO at 2,500 — 425 to go
Reached: Level 10 · Level 9 · Level 8 · Level 7
Level 10 first seen 2026-09-02
Level 9 first seen 2026-09-02

Premier CS Rating

828 below peak (27,356)
+803 over 30 days · improving
+250 over 90 days
Next: Gold band at 30,000 — 3,472 to go
Reached: Red band · Pink band · Purple band · Blue band
Red band first seen 2026-09-02
Pink band first seen 2026-09-02

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

How this compares with the same rank

Median values for Level 10 among CSDB-tracked players (n=30,986), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

Metric	This player	Level 10 median
Headshot rate	44.4%	50.9%
Shot accuracy	13.4%	13.7%
Kill/death ratio	1.46	1.09
Match win rate	52.1%	48.4%

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Performance scores

Aim79

Positioning68

Utility69

0–100 skill scores via Leetify.

Recent form

STEADY49–48–3Last 10049%Win rateWLWWLLWLLW

Last 10 vs previous 10: 0pp win rate · −0.00 avg rating · +2.5pp headshot accuracy · −26ms reaction

Win rate 0pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

3–2 · 60% win rate
Avg rating 0.01
Avg headshot accuracy 18%
Avg reaction 464ms

Last 10

5–5 · 50% win rate
Avg rating -0.00
Avg headshot accuracy 16%
Avg reaction 484ms

Last 20

10–10 · 50% win rate
Avg rating -0.00
Avg headshot accuracy 15%
Avg reaction 497ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Support — Utility contribution stands above the rest of this profile (+1.2 against its own average).

Aim7.9

Utility6.9

Positioning6.8

Opening Duels5.2

Clutch3.8

Effective flashes

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

Plays most like Twistzz 89% playstyle similarity

Most alike: utility contribution, opening-duel success.

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

Strengths

Flashes. 0.79 enemies blinded per flash — utility that consistently lands.

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

Aim7.9

Positioning6.8

Utility6.9

Mechanics7.8

Opening Duels5.8

Win Impact3.9

Composite 7.3/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.00−0.01

first ⅓ avg 0.01 → last ⅓ avg 0.00

Reaction time501ms−30ms

first ⅓ avg 531ms → last ⅓ avg 501ms

Headshot accuracy15.2%−2.2%

first ⅓ avg 17.4% → last ⅓ avg 15.2%

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.

Personal bests

0.16Best match rating · 13–5 · cache, 9 Oct →

30%Best headshot accuracy · 13–9 · dust2, 6 Aug →

359msFastest reaction time · 3–13 · inferno, 19 Jul →

13–0Biggest win · ancient, 24 Jul →

Across the last 100 tracked matches.

Highlights

4Longest win streak

4–5In matches decided by ≤2 rounds

8Overtime games

Map breakdown

dust2Best map · 59% over 17anubisWeakest map · 22% over 9

Map	Grade	Played	Record	Win rate	Avg rating
inferno	B	22	11–11	50%	0.01
dust2	A	17	10–7	59%	0.01
cache	B	15	7–8	47%	0.03
ancient	B	15	8–7	53%	0.02
mirage	A	11	6–5	55%	0.01
anubis	D	9	2–7	22%	-0.02
nuke	C	7	3–4	43%	-0.04
boulder	—	2	2–0	100%	0.02
vertigo	—	1	0–1	0%	-0.01
shelter	—	1	0–1	0%	0.01

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (22% over 9). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

81,942Lifetime kills

1.46K/D · Top 10% of Level 10 players

3,509Matches

52.1%Match win rate · Top 25% of Level 10 players

44.4%Headshot %

13.4%Shot accuracy

9,656MVPs

1,382Hours (in match)

2,469Bombs planted

1,004Bombs defused

Most-used weapons

AK-4721,724

M4A4 / M4A1-S17,383

AWP7,264

P2000 / USP-S4,825

Desert Eagle4,289

Glock-183,092

P2502,523

P901,823

MP91,764

MAC-101,656

Lifetime map wins

7,701inferno

4,172dust2

2,417nuke

2,328vertigo

590train

506cbble

87lake

67safehouse

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

Faceit stats

Combat

212Matches

59%Win rate

1.31Avg K/D

87.9ADR

40%Headshot %

Clutches & streaks

39%1v1 clutch win

23%1v2 clutch win

7Longest win streak

Recent Faceit resultsWWLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	44	59%	1.27	17.4
Inferno	40	58%	1.34	16.4
Dust2	29	66%	1.19	18.5
Mirage	27	59%	1.38	18.0
Anubis	24	58%	1.27	17.3
Nuke	12	58%	1.28	16.8
Cache	4	75%	1.34	19.0
Train	3	67%	1.24	18.3

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.

15.1%Headshot accuracy

34.8%Accuracy (enemy spotted)

34.9%Spray accuracy

85.0%Counter-strafing

8.4°Preaim

498msReaction time

52.7%T opening success

54.1%CT opening success

0.79Enemies flashed / flash

4.1%Flash assists

11.32HE damage / grenade

12.87Flashes / match

Recommended for you

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.

22% win rate across 9 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
dust2	13–8	0.01	15%	1 Nov →
anubis	5–13	-0.00	22%	1 Nov →
inferno	13–6	0.05	17%	28 Oct →
dust2	13–5	-0.00	22%	28 Oct →
dust2	6–13	-0.00	16%	28 Oct →
cache	6–13	-0.01	18%	24 Oct →
nuke	13–9	-0.04	11%	24 Oct →
inferno	3–13	-0.02	8%	24 Oct →
mirage	13–16	-0.02	16%	21 Oct →
mirage	13–9	-0.00	15%	21 Oct →
mirage	13–10	0.05	11%	21 Oct →
dust2	10–13	-0.02	12%	21 Oct →
anubis	6–13	-0.09	11%	17 Oct →
nuke	13–9	-0.05	9%	11 Oct →
inferno	11–13	-0.02	16%	11 Oct →
mirage	8–13	-0.01	16%	11 Oct →
inferno	13–9	-0.02	10%	11 Oct →
cache	10–13	0.00	15%	10 Oct →
ancient	13–5	0.07	23%	10 Oct →
inferno	13–11	0.07	11%	10 Oct →
anubis	7–13	-0.02	28%	10 Oct →
dust2	13–4	0.04	13%	10 Oct →
ancient	13–5	0.06	11%	10 Oct →
mirage	13–5	0.04	25%	10 Oct →
nuke	2–13	-0.11	10%	9 Oct →
cache	13–5	0.16	16%	9 Oct →
anubis	5–13	-0.02	21%	9 Oct →
inferno	8–13	-0.02	13%	9 Oct →
ancient	6–13	-0.04	16%	6 Oct →
inferno	9–13	0.01	9%	6 Oct →
anubis	6–13	-0.05	14%	6 Oct →
cache	8–13	0.02	26%	1 Oct →
ancient	9–13	0.00	8%	1 Oct →
inferno	9–13	-0.04	24%	1 Oct →
inferno	13–8	0.10	27%	1 Oct →
dust2	13–9	0.03	11%	25 Sept →
cache	13–11	0.05	17%	24 Sept →
ancient	12–9	0.03	14%	3 Sept →
nuke	7–13	-0.02	12%	3 Sept →
dust2	13–1	0.06	22%	17 Aug →
ancient	15–15	-0.06	18%	17 Aug →
cache	10–13	-0.07	24%	17 Aug →
dust2	13–10	0.01	18%	16 Aug →
inferno	13–3	0.09	15%	16 Aug →
inferno	13–4	0.04	12%	16 Aug →
dust2	3–13	-0.05	20%	16 Aug →
nuke	15–15	-0.02	20%	14 Aug →
ancient	13–11	0.03	14%	13 Aug →
inferno	13–11	0.01	10%	13 Aug →
dust2	10–13	-0.03	17%	13 Aug →
dust2	13–9	0.05	30%	6 Aug →
ancient	13–8	-0.00	17%	6 Aug →
anubis	9–13	-0.03	12%	6 Aug →
vertigo	9–13	-0.01	17%	6 Aug →
inferno	8–13	0.04	18%	6 Aug →
cache	3–13	0.06	20%	3 Aug →
mirage	8–13	0.04	10%	3 Aug →
nuke	13–9	0.01	20%	3 Aug →
inferno	16–13	-0.02	17%	3 Aug →
dust2	11–13	0.03	21%	29 Jul →
ancient	13–8	0.07	24%	29 Jul →
cache	7–13	0.01	20%	29 Jul →
inferno	13–10	0.03	15%	27 Jul →
inferno	13–8	0.03	27%	27 Jul →
cache	10–13	0.00	17%	27 Jul →
cache	13–5	0.03	17%	24 Jul →
ancient	13–0	0.03	27%	24 Jul →
inferno	13–16	-0.02	25%	19 Jul →
ancient	16–12	-0.04	9%	19 Jul →
dust2	13–8	0.00	23%	19 Jul →
inferno	3–13	-0.04	26%	19 Jul →
cache	13–8	0.03	18%	19 Jul →
ancient	2–13	0.04	27%	19 Jul →
mirage	13–8	-0.04	18%	16 Jul →
dust2	8–13	-0.02	15%	16 Jul →
anubis	13–7	0.01	16%	16 Jul →
cache	11–13	0.00	9%	16 Jul →
nuke	0–13	-0.08	0%	16 Jul →
mirage	10–13	-0.03	7%	14 Jul →
dust2	13–7	0.08	21%	14 Jul →
cache	13–6	0.02	14%	14 Jul →
anubis	6–13	-0.00	11%	14 Jul →
mirage	13–5	0.06	15%	14 Jul →
boulder	13–10	0.03	25%	13 Jul →
boulder	8–0	0.00	0%	13 Jul →
shelter	5–13	0.01	25%	13 Jul →
dust2	8–13	0.01	21%	12 Jul →
ancient	9–13	0.05	30%	12 Jul →
inferno	14–16	0.04	18%	12 Jul →
anubis	13–2	0.07	18%	11 Jul →
dust2	13–5	0.03	19%	11 Jul →
inferno	10–13	-0.01	26%	9 Jul →
cache	13–4	-0.01	16%	9 Jul →
inferno	13–9	0.03	12%	9 Jul →
mirage	15–15	0.01	17%	9 Jul →
cache	13–6	0.08	22%	9 Jul →
mirage	13–10	-0.03	29%	5 Jul →
ancient	10–13	0.07	22%	1 Jul →
ancient	7–13	-0.03	9%	30 Jun →
inferno	11–13	-0.04	13%	30 Jun →