VecticBeastYT — CS2 Stats
76561198170188985[U:1:209923257]✓ No bans
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -10pp win rate · -0.00 avg rating
Player DNA
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 78% playstyle similarity
Most alike: opening-fight frequency, opening-duel success.
Where you differ: lower positioning profile; 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 44% on CT to 23% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 634ms 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
Composite 3.6/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.
Trends
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
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
| A | 26 | 16–10 | 62% | -0.02 | |
| B | 12 | 6–6 | 50% | -0.02 | |
| B | 12 | 6–6 | 50% | -0.02 | |
| B | 11 | 5–6 | 45% | -0.03 | |
| C | 10 | 4–6 | 40% | -0.05 | |
| A | 8 | 5–3 | 63% | -0.03 | |
| D | 7 | 1–6 | 14% | -0.02 | |
| — | 3 | 2–1 | 67% | -0.01 | |
| — | 3 | 1–2 | 33% | -0.03 | |
| italy | — | 2 | 0–2 | 0% | -0.07 |
| warden | — | 2 | 1–1 | 50% | -0.02 |
| — | 2 | 0–2 | 0% | -0.02 | |
| boulder | — | 1 | 0–1 | 0% | -0.06 |
| alpine | — | 1 | 0–1 | 0% | 0.00 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (14% over 7). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.
Lifetime stats
Most-used weapons
Lifetime map wins
Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.
Skill profile
Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.
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 MechanicsAim Training →
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 12.3236° — above the 12° mark we flag
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.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 6–13 | -0.00 | 22% | 17 Aug → | ||
| 13–8 | -0.01 | 22% | 17 Aug → | ||
| 13–9 | -0.02 | 14% | 15 Aug → | ||
| 11–5 | -0.06 | 8% | 15 Aug → | ||
| 9–13 | -0.05 | 27% | 13 Aug → | ||
| 10–13 | -0.03 | 22% | 25 Jul → | ||
| 8–13 | -0.01 | 9% | 25 Jul → | ||
| boulder | 9–13 | -0.06 | 14% | 21 Jul → | |
| italy | 11–13 | -0.04 | 9% | 20 Jul → | |
| 9–13 | -0.02 | 33% | 20 Jul → | ||
| 10–13 | 0.04 | 4% | 14 Jul → | ||
| 5–13 | -0.10 | 22% | 13 Jul → | ||
| 3–13 | -0.05 | 21% | 12 Jul → | ||
| 12–12 | -0.05 | 33% | 12 Jul → | ||
| 10–13 | 0.04 | 14% | 9 Jul → | ||
| 13–5 | 0.04 | 16% | 9 Jul → | ||
| 13–2 | -0.01 | 20% | 9 Jul → | ||
| 13–11 | -0.02 | 17% | 7 Jul → | ||
| 10–3 | -0.07 | 12% | 6 Jul → | ||
| 9–13 | -0.08 | 19% | 5 Jul → | ||
| 13–8 | -0.04 | 3% | 5 Jul → | ||
| 13–16 | -0.04 | 15% | 3 Jul → | ||
| 9–13 | -0.07 | 15% | 2 Jul → | ||
| 6–9 | -0.13 | 24% | 2 Jul → | ||
| 12–12 | -0.02 | 21% | 1 Jul → | ||
| italy | 9–13 | -0.11 | 8% | 30 Jun → | |
| 13–7 | -0.00 | 21% | 29 Jun → | ||
| 13–2 | -0.06 | 8% | 29 Jun → | ||
| 7–13 | -0.07 | 13% | 29 Jun → | ||
| 12–12 | -0.00 | 12% | 21 Jun → | ||
| 8–13 | 0.00 | 18% | 21 Jun → | ||
| 10–13 | -0.01 | 19% | 20 Jun → | ||
| 13–3 | 0.06 | 22% | 20 Jun → | ||
| 13–5 | -0.07 | 25% | 20 Jun → | ||
| 13–4 | 0.04 | 14% | 20 Jun → | ||
| 13–10 | -0.00 | 18% | 20 Jun → | ||
| 13–5 | -0.09 | 23% | 20 Jun → | ||
| 5–13 | -0.06 | 75% | 20 Jun → | ||
| 13–11 | -0.07 | 16% | 19 Jun → | ||
| 6–13 | -0.08 | 7% | 19 Jun → | ||
| 12–12 | -0.01 | 8% | 13 Jun → | ||
| 13–8 | -0.06 | 15% | 7 Jun → | ||
| warden | 13–7 | -0.04 | 15% | 7 Jun → | |
| 13–11 | 0.01 | 14% | 6 Jun → | ||
| 13–11 | -0.04 | 11% | 5 Jun → | ||
| 13–10 | -0.03 | 9% | 5 Jun → | ||
| 13–10 | -0.04 | 16% | 5 Jun → | ||
| 13–10 | -0.09 | 8% | 2 Jun → | ||
| 13–7 | -0.01 | 26% | 2 Jun → | ||
| 13–10 | 0.05 | 22% | 1 Jun → | ||
| 9–13 | -0.02 | 17% | 31 May → | ||
| 13–7 | 0.03 | 7% | 31 May → | ||
| 11–13 | -0.04 | 10% | 31 May → | ||
| warden | 12–12 | -0.01 | 17% | 31 May → | |
| 12–12 | 0.01 | 20% | 31 May → | ||
| 6–13 | -0.03 | 17% | 31 May → | ||
| 13–11 | 0.05 | 24% | 27 May → | ||
| 13–9 | -0.01 | 11% | 27 May → | ||
| 2–1 | -0.05 | 0% | 27 May → | ||
| 9–1 | -0.03 | 0% | 27 May → | ||
| 8–13 | -0.03 | 9% | 25 May → | ||
| 9–13 | -0.08 | 11% | 25 May → | ||
| 13–8 | -0.07 | 15% | 24 May → | ||
| 13–8 | -0.02 | 20% | 24 May → | ||
| 13–11 | -0.01 | 7% | 23 May → | ||
| 15–15 | -0.03 | 11% | 22 May → | ||
| 13–6 | -0.05 | 2% | 21 May → | ||
| 13–4 | -0.08 | 36% | 20 May → | ||
| 13–6 | -0.02 | 14% | 20 May → | ||
| 11–13 | -0.06 | 10% | 19 May → | ||
| 2–13 | -0.10 | 18% | 17 May → | ||
| 13–9 | -0.02 | 14% | 17 May → | ||
| 6–13 | -0.02 | 7% | 15 May → | ||
| 10–13 | -0.12 | 6% | 15 May → | ||
| 10–13 | 0.03 | 21% | 14 May → | ||
| 6–0 | 0.03 | 33% | 14 May → | ||
| 7–13 | -0.05 | 9% | 14 May → | ||
| 13–10 | -0.00 | 11% | 13 May → | ||
| 13–7 | -0.02 | 25% | 9 May → | ||
| 7–13 | -0.06 | 23% | 8 May → | ||
| 13–9 | -0.03 | 17% | 6 May → | ||
| 8–12 | 0.06 | 17% | 6 May → | ||
| alpine | 7–5 | 0.00 | 33% | 6 May → | |
| 13–8 | 0.02 | 12% | 3 May → | ||
| 13–3 | -0.02 | 11% | 3 May → | ||
| 13–5 | 0.05 | 12% | 3 May → | ||
| 3–13 | -0.06 | 11% | 3 May → | ||
| 9–13 | -0.07 | 23% | 2 May → | ||
| 3–13 | -0.06 | 12% | 26 Apr → | ||
| 1–13 | -0.08 | 0% | 26 Apr → | ||
| 13–10 | -0.05 | 8% | 22 Mar → | ||
| 12–12 | -0.04 | 9% | 22 Mar → | ||
| 13–16 | 0.07 | 15% | 13 Mar → | ||
| 9–13 | -0.01 | 23% | 13 Mar → | ||
| 16–13 | 0.00 | 10% | 13 Mar → | ||
| 11–13 | -0.04 | 20% | 12 Mar → | ||
| 13–5 | 0.04 | 20% | 12 Mar → | ||
| 6–13 | -0.06 | 10% | 12 Mar → | ||
| 12–1 | -0.00 | 14% | 11 Mar → | ||
| 15–15 | 0.01 | 19% | 11 Mar → |
Match data via Leetify.
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