VanDe — CS2 Stats
PL76561198018039184[U:1:57773456]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Level 4 among CSDB-tracked players (n=1,711), 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 4 median | Level 5 median | vs Level 5 |
|---|---|---|---|---|
| Headshot rate | 39.7% | 42.7% | 44.0% | 4.4% short |
| Shot accuracy | 15.2% | 10.8% | 11.6% | above |
| Kill/death ratio | 0.75 | 1.00 | 1.03 | 0.28 short |
| Match win rate | 45.0% | 44.1% | 45.1% | meets |
This profile matches the typical Level 5 player on 2 of 4 comparable metrics.
Widest gap: Kill/death ratio. That is the metric furthest from the Level 5 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -20pp 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 56% playstyle similarity
Most alike: utility contribution, opening-duel success.
Where you differ: lower opening-fight frequency; 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. 753ms 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 3.1/10 (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
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 |
|---|---|---|---|---|---|
 overpass | B | 18 | 9–9 | 50% | -0.06 |
 inferno | A | 17 | 10–7 | 59% | -0.05 |
 mirage | D | 14 | 3–11 | 21% | -0.05 |
 train | D | 12 | 3–9 | 25% | -0.05 |
 cache | C | 11 | 4–7 | 36% | -0.05 |
 anubis | D | 9 | 1–8 | 11% | -0.03 |
 nuke | C | 8 | 3–5 | 38% | -0.06 |
 vertigo | D | 6 | 2–4 | 33% | -0.07 |
 ancient | — | 3 | 2–1 | 67% | -0.03 |
 dust2 | — | 1 | 1–0 | 100% | 0.01 |
| office | — | 1 | 0–1 | 0% | -0.04 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (11% over 9). 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.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsLWWLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Anubis | 27 | 59% | 0.67 | 9.6 |
| Vertigo | 20 | 55% | 0.58 | 9.2 |
| Ancient | 17 | 47% | 0.57 | 7.7 |
| Inferno | 12 | 42% | 0.48 | 8.6 |
| Mirage | 6 | 50% | 0.69 | 8.3 |
| Nuke | 6 | 67% | 0.95 | 11.5 |
| Overpass | 4 | 100% | 0.82 | 7.3 |
| Train | 2 | 100% | 0.48 | 6.5 |
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.
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 12.0826° — above the 12° mark we flag
- Best CS2 CrosshairAim Training →
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 14.4373% — below the 15% mark we flag
- Best CS2 SettingsAim Training →
Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.
Reaction time 753.2154ms — above the 700ms mark we flag
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.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| cache | 8–13 | -0.05 | 9% | 3 May → | |
| mirage | 3–13 | -0.05 | 24% | 19 Mar → | |
| dust2 | 9–1 | 0.01 | 14% | 7 Feb → | |
| inferno | 13–4 | -0.08 | 24% | 1 Jan → | |
| anubis | 5–13 | -0.04 | 20% | 15 Dec → | |
| nuke | 13–7 | -0.06 | 24% | 16 Nov → | |
| train | 13–8 | -0.00 | 8% | 5 Nov → | |
| train | 2–13 | -0.10 | 11% | 5 Nov → | |
| inferno | 4–13 | -0.07 | 8% | 8 Oct → | |
| inferno | 13–9 | -0.05 | 5% | 6 Oct → | |
| mirage | 13–3 | -0.02 | 13% | 2 Oct → | |
| ancient | 13–6 | -0.01 | 17% | 1 Oct → | |
| inferno | 7–1 | -0.03 | 22% | 1 Oct → | |
| overpass | 13–6 | -0.07 | 0% | 30 Sept → | |
| overpass | 13–10 | -0.05 | 10% | 28 Sept → | |
| overpass | 2–1 | -0.05 | 25% | 28 Sept → | |
| inferno | 12–12 | -0.03 | 11% | 30 Aug → | |
| train | 10–13 | -0.08 | 8% | 30 Aug → | |
| nuke | 6–13 | -0.08 | 5% | 28 Aug → | |
| train | 13–3 | -0.05 | 17% | 10 Jul → | |
| train | 10–13 | -0.06 | 41% | 1 Jul → | |
| inferno | 7–13 | -0.06 | 13% | 4 Mar → | |
| vertigo | 4–13 | -0.09 | 8% | 4 Mar → | |
| ancient | 13–8 | 0.01 | 14% | 28 Nov → | |
| nuke | 13–10 | -0.06 | 15% | 6 Nov → | |
| mirage | 10–13 | -0.07 | 18% | 29 Oct → | |
| mirage | 4–13 | -0.09 | 8% | 28 Oct → | |
| mirage | 12–12 | -0.08 | 19% | 24 Oct → | |
| inferno | 7–13 | -0.09 | 29% | 21 Oct → | |
| overpass | 13–9 | -0.04 | 5% | 20 Oct → | |
| anubis | 12–12 | -0.09 | 8% | 13 Oct → | |
| nuke | 12–12 | -0.07 | 3% | 13 Oct → | |
| mirage | 12–12 | -0.09 | 13% | 10 Sept → | |
| ancient | 6–13 | -0.07 | 21% | 1 Sept → | |
| anubis | 10–13 | 0.01 | 16% | 21 May → | |
| office | 5–13 | -0.04 | 33% | 16 May → | |
| vertigo | 11–13 | -0.07 | 15% | 29 Apr → | |
| vertigo | 13–2 | -0.05 | 17% | 28 Apr → | |
| anubis | 6–13 | -0.03 | 18% | 28 Apr → | |
| vertigo | 1–13 | -0.12 | 6% | 27 Apr → | |
| nuke | 11–13 | -0.05 | 9% | 2 Apr → | |
| overpass | 4–13 | -0.04 | 6% | 24 Mar → | |
| overpass | 7–13 | -0.03 | 12% | 20 Mar → | |
| overpass | 13–8 | -0.10 | 10% | 17 Mar → | |
| anubis | 13–9 | -0.00 | 23% | 12 Mar → | |
| inferno | 13–9 | -0.07 | 9% | 12 Mar → | |
| nuke | 1–13 | -0.11 | 17% | 12 Mar → | |
| anubis | 8–13 | 0.05 | 27% | 11 Mar → | |
| vertigo | 13–6 | -0.03 | 25% | 4 Mar → | |
| inferno | 10–13 | -0.14 | 0% | 3 Mar → | |
| mirage | 13–6 | -0.07 | 11% | 7 Jan → | |
| mirage | 6–13 | -0.05 | 10% | 12 Dec → | |
| overpass | 16–14 | -0.11 | 12% | 10 Dec → | |
| overpass | 11–13 | -0.12 | 5% | 24 Sept → | |
| overpass | 13–8 | -0.06 | 9% | 20 Sept → | |
| anubis | 7–13 | -0.06 | 7% | 8 Sept → | |
| inferno | 13–8 | -0.07 | 8% | 8 Sept → | |
| overpass | 13–8 | -0.07 | 6% | 6 Sept → | |
| vertigo | 10–13 | -0.05 | 13% | 3 Sept → | |
| mirage | 13–16 | -0.06 | 9% | 3 Sept → | |
| train | 7–16 | -0.08 | 13% | 21 Aug → | |
| overpass | 10–16 | -0.09 | 14% | 12 Aug → | |
| train | 15–15 | -0.03 | 14% | 28 Jun → | |
| overpass | 9–16 | -0.06 | 11% | 28 May → | |
| nuke | 9–3 | -0.02 | 8% | 25 May → | |
| overpass | 7–16 | -0.10 | 0% | 25 May → | |
| cache | 3–16 | -0.10 | 14% | 25 May → | |
| cache | 6–16 | -0.07 | 10% | 10 May → | |
| cache | 16–12 | -0.08 | 5% | 7 May → | |
| cache | 4–16 | -0.10 | 11% | 21 Apr → | |
| anubis | 5–16 | -0.02 | 16% | 21 Apr → | |
| cache | 16–10 | -0.04 | 8% | 16 Apr → | |
| inferno | 16–9 | -0.06 | 6% | 15 Apr → | |
| overpass | 16–5 | -0.05 | 12% | 11 Apr → | |
| cache | 13–16 | -0.04 | 7% | 5 Apr → | |
| mirage | 15–15 | -0.10 | 16% | 2 Apr → | |
| anubis | 15–15 | -0.05 | 12% | 27 Mar → | |
| mirage | 8–16 | -0.04 | 10% | 26 Mar → | |
| inferno | 10–16 | -0.06 | 17% | 21 Mar → | |
| cache | 16–5 | -0.03 | 12% | 10 Mar → | |
| overpass | 7–9 | -0.09 | 14% | 1 Mar → | |
| inferno | 16–12 | -0.07 | 2% | 20 Feb → | |
| train | 10–16 | -0.05 | 17% | 18 Feb → | |
| train | 7–16 | -0.10 | 5% | 14 Feb → | |
| inferno | 6–9 | -0.05 | 22% | 13 Feb → | |
| train | 9–16 | 0.00 | 15% | 21 Jun → | |
| mirage | 16–12 | 0.00 | 15% | 13 Jun → | |
| train | 16–10 | 0.00 | 4% | 9 Jun → | |
| mirage | 10–16 | 0.00 | 16% | 9 Jun → | |
| inferno | 16–1 | 0.00 | 7% | 9 Jun → | |
| overpass | 9–16 | 0.00 | 10% | 7 Jun → | |
| nuke | 4–16 | 0.00 | 10% | 7 Jun → | |
| inferno | 16–11 | 0.00 | 0% | 7 Jun → | |
| mirage | 10–16 | 0.00 | 6% | 6 Jun → | |
| cache | 9–16 | 0.00 | 3% | 1 Jun → | |
| train | 3–10 | 0.00 | 0% | 1 Jun → | |
| overpass | 3–16 | 0.00 | 10% | 31 May → | |
| cache | 7–16 | 0.00 | 13% | 31 May → | |
| cache | 16–7 | 0.00 | 11% | 28 May → | |
| inferno | 16–13 | 0.00 | 10% | 28 May → |
Match data via Leetify.
