Vega — CS2 Stats

76561197962512331[U:1:2246603]

256Tracked matches29%Win rate2023Tracked since

CSDB Rating3.8 Learning

Ladder ranks via Leetify

Performance scores

Aim43

Positioning41

Utility47

0–100 skill scores via Leetify.

Recent form

COLD30–63–7Last 10030%Win rateWLLWLLWTLL

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

Player DNA

Aim4.3

Aggression3.8

Utility4.7

Positioning4.1

Opening Duels0.0

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 73% playstyle similarity

Most alike: opening-fight frequency, utility contribution.

Where you differ: lower opening-duel success; 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

Reaction time. 637ms 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

Aim4.3

Positioning4.1

Utility4.7

Mechanics6.0

Opening Duels0.5

Win Impact0.0

Composite 3.8/10 (Learning), 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-0.03−0.00

first ⅓ avg -0.03 → last ⅓ avg -0.03

Reaction time634ms−76ms

first ⅓ avg 710ms → last ⅓ avg 634ms

Headshot accuracy17.8%−1.8%

first ⅓ avg 19.6% → last ⅓ avg 17.8%

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

0.07Best rating — cache 13–10

12–0Biggest win — inferno

3Longest win streak

6–9In matches decided by ≤2 rounds

Map breakdown

trainBest map · 67% over 6mirageWeakest map · 11% over 9

Map	Grade	Played	Record	Win rate	Avg rating
dust2	D	38	12–26	32%	-0.04
inferno	C	14	6–8	43%	-0.04
mirage	D	9	1–8	11%	-0.04
ancient	D	8	1–7	13%	-0.03
cache	D	7	2–5	29%	-0.01
nuke	D	7	1–6	14%	-0.05
train	S	6	4–2	67%	-0.03
vertigo	—	4	1–3	25%	-0.06
anubis	—	3	1–2	33%	-0.07
overpass	—	2	0–2	0%	-0.06
boulder	—	1	0–1	0%	-0.03
office	—	1	1–0	100%	-0.03

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (11% over 9). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

18.3%Headshot accuracy

27.8%Accuracy (enemy spotted)

29.9%Spray accuracy

76.8%Counter-strafing

11.0°Preaim

637msReaction time

34.0%T opening success

23.0%CT opening success

0.60Enemies flashed / flash

4.7%Flash assists

8.16HE damage / grenade

4.49Flashes / 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 33.9575% — 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.

11% win rate across 9 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
mirage	13–11	-0.03	23%	30 Aug →
dust2	9–13	-0.08	23%	28 Aug →
dust2	9–13	-0.06	11%	28 Aug →
dust2	13–9	0.03	11%	28 Aug →
dust2	7–13	-0.03	20%	27 Aug →
cache	7–13	-0.09	11%	26 Aug →
cache	13–10	0.07	21%	25 Aug →
inferno	12–12	-0.04	14%	24 Aug →
dust2	9–13	-0.05	17%	24 Aug →
nuke	11–13	-0.02	23%	15 Aug →
inferno	13–10	-0.07	15%	15 Aug →
cache	9–13	-0.01	26%	15 Aug →
nuke	7–13	-0.11	7%	11 Aug →
inferno	12–0	-0.01	0%	11 Aug →
dust2	6–13	-0.03	24%	10 Aug →
dust2	7–13	-0.03	20%	10 Aug →
dust2	4–13	-0.05	25%	9 Aug →
inferno	12–12	-0.06	24%	9 Aug →
mirage	8–13	-0.04	24%	9 Aug →
cache	10–13	-0.03	20%	9 Aug →
dust2	5–13	-0.06	25%	9 Aug →
ancient	13–5	0.04	18%	3 Aug →
mirage	10–13	0.01	23%	2 Aug →
dust2	7–13	-0.06	15%	2 Aug →
anubis	2–13	-0.09	13%	2 Aug →
dust2	11–13	0.00	21%	2 Aug →
mirage	3–13	-0.03	21%	1 Aug →
nuke	7–2	0.03	24%	31 Jul →
inferno	3–13	-0.07	14%	31 Jul →
inferno	13–7	0.04	10%	27 Jul →
dust2	13–11	-0.04	20%	27 Jul →
vertigo	2–13	-0.11	10%	26 Jul →
inferno	13–9	-0.07	15%	26 Jul →
ancient	6–13	-0.03	11%	26 Jul →
dust2	11–13	-0.07	14%	26 Jul →
mirage	5–13	-0.07	17%	25 Jul →
dust2	13–7	-0.04	14%	25 Jul →
anubis	5–13	-0.05	7%	25 Jul →
mirage	8–13	0.00	9%	24 Jul →
vertigo	4–13	-0.04	19%	24 Jul →
ancient	2–13	-0.00	12%	24 Jul →
anubis	13–7	-0.06	8%	22 Jul →
dust2	3–13	-0.06	10%	18 Jul →
dust2	5–13	-0.09	5%	18 Jul →
dust2	13–10	0.00	17%	18 Jul →
dust2	5–13	-0.06	9%	18 Jul →
mirage	1–13	-0.07	5%	18 Jul →
nuke	12–12	-0.05	27%	15 Jul →
dust2	11–13	-0.09	16%	15 Jul →
ancient	4–13	-0.01	23%	15 Jul →
train	12–12	-0.05	12%	14 Jul →
inferno	9–13	-0.07	12%	14 Jul →
cache	4–13	-0.03	11%	13 Jul →
ancient	3–13	-0.10	11%	13 Jul →
boulder	6–13	-0.03	22%	13 Jul →
vertigo	13–11	-0.02	13%	12 Jul →
ancient	12–12	-0.07	29%	12 Jul →
dust2	12–12	0.01	14%	12 Jul →
ancient	3–13	-0.06	19%	12 Jul →
dust2	9–13	-0.01	30%	12 Jul →
train	13–8	-0.01	25%	5 Jul →
inferno	2–13	-0.07	13%	5 Jul →
dust2	13–11	-0.00	10%	4 Jul →
nuke	11–13	-0.10	25%	22 Jun →
mirage	5–13	-0.07	13%	16 Jun →
cache	13–4	0.01	19%	16 Jun →
overpass	6–13	-0.06	21%	10 Jun →
dust2	13–4	-0.05	13%	7 Jun →
ancient	10–13	-0.01	30%	7 Jun →
train	13–9	-0.01	14%	7 Jun →
dust2	6–13	-0.09	12%	26 May →
cache	11–13	-0.02	16%	19 May →
dust2	8–13	-0.09	16%	19 May →
inferno	12–12	0.02	15%	16 May →
overpass	2–13	-0.06	13%	12 May →
train	13–8	-0.04	19%	3 May →
dust2	13–5	0.06	18%	2 May →
train	11–13	-0.07	24%	27 Apr →
dust2	13–6	0.00	37%	27 Apr →
train	13–11	-0.02	27%	26 Apr →
inferno	13–3	-0.00	43%	26 Apr →
dust2	6–13	-0.10	22%	12 Apr →
dust2	8–13	-0.02	8%	12 Apr →
mirage	0–13	-0.03	24%	12 Apr →
vertigo	8–13	-0.06	18%	28 Mar →
dust2	4–13	-0.06	20%	25 Dec →
dust2	12–6	0.02	18%	25 Dec →
office	13–6	-0.03	13%	23 Dec →
dust2	11–13	0.04	20%	23 Dec →
inferno	13–6	-0.02	22%	23 Dec →
nuke	10–13	-0.05	31%	23 Dec →
dust2	13–7	-0.03	14%	12 Dec →
inferno	6–13	-0.04	9%	8 Dec →
dust2	13–11	-0.01	25%	8 Dec →
inferno	11–13	-0.08	22%	7 Dec →
dust2	8–13	-0.06	14%	7 Dec →
dust2	10–13	-0.00	15%	24 Nov →
dust2	13–10	-0.06	19%	20 Nov →
dust2	9–13	-0.07	15%	27 Oct →
nuke	6–13	-0.04	21%	27 Oct →