Wutangable — CS2 Stats
US76561198060683752[U:1:100418024]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Level 4 among CSDB-tracked players (n=928), 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 | 43.3% | 42.5% | 44.2% | 0.9% short |
| Shot accuracy | 7.6% | 10.9% | 11.2% | 3.6% short |
| Kill/death ratio | 0.85 | 0.99 | 1.04 | 0.19 short |
| Match win rate | 41.5% | 44.2% | 45.3% | 3.8% short |
This profile sits below the typical Level 5 player on every metric we can compare.
Widest gap: Shot accuracy. 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: +10pp win rate · +0.01 avg rating
Player DNA
Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.
Excellent counter-strafingStrong 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 iM 92% playstyle similarity
Most alike: utility contribution, positioning profile.
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 56% on CT to 35% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 653ms 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 6.9/10 (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
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 |
|---|---|---|---|---|---|
| D | 21 | 7–14 | 33% | -0.02 | |
| A | 18 | 11–7 | 61% | -0.02 | |
| B | 13 | 6–7 | 46% | -0.01 | |
| A | 13 | 8–5 | 62% | 0.00 | |
| A | 11 | 7–4 | 64% | -0.03 | |
| A | 10 | 6–4 | 60% | 0.01 | |
| S | 7 | 5–2 | 71% | -0.00 | |
| B | 6 | 3–3 | 50% | 0.01 | |
| — | 1 | 1–0 | 100% | 0.02 |
Across the last 100 tracked matches.
Nuke is currently your weakest sufficiently-sampled map (33% over 21). Start with the 6 essential Nuke 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 resultsLLLLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 24 | 29% | 0.80 | 13.3 |
| Inferno | 19 | 47% | 0.75 | 11.4 |
| Dust2 | 14 | 50% | 0.97 | 13.2 |
| Nuke | 12 | 42% | 0.86 | 13.3 |
| Overpass | 7 | 29% | 0.95 | 16.4 |
| Train | 5 | 20% | 0.91 | 12.8 |
| Ancient | 2 | 50% | 0.61 | 11.0 |
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 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 35.262% — below the 40% mark we flag
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
33% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–4 | 0.03 | 27% | 19 Aug → | ||
| 13–6 | 0.04 | 16% | 17 Aug → | ||
| 13–9 | 0.01 | 26% | 17 Aug → | ||
| 13–7 | 0.05 | 20% | 17 Aug → | ||
| 13–2 | 0.07 | 13% | 17 Aug → | ||
| 13–9 | 0.00 | 11% | 17 Aug → | ||
| 3–13 | -0.03 | 19% | 16 Aug → | ||
| 11–13 | 0.03 | 20% | 16 Aug → | ||
| 4–13 | 0.01 | 16% | 16 Aug → | ||
| 2–13 | -0.06 | 31% | 16 Aug → | ||
| 13–3 | 0.10 | 21% | 20 Jul → | ||
| 13–9 | 0.04 | 22% | 20 Jul → | ||
| 11–13 | 0.02 | 20% | 20 Jul → | ||
| 13–3 | 0.04 | 18% | 20 Jul → | ||
| 11–13 | -0.07 | 18% | 19 Jul → | ||
| 13–10 | 0.02 | 24% | 19 Jul → | ||
| 8–13 | 0.04 | 7% | 18 Jul → | ||
| 13–16 | -0.05 | 17% | 18 Jul → | ||
| 13–7 | -0.09 | 11% | 18 Jul → | ||
| 7–13 | -0.00 | 18% | 18 Jul → | ||
| 16–13 | 0.03 | 17% | 18 Jul → | ||
| 13–3 | 0.07 | 22% | 17 Jul → | ||
| 15–15 | -0.02 | 8% | 17 Jul → | ||
| 13–7 | -0.06 | 8% | 17 Jul → | ||
| 13–6 | 0.04 | 24% | 17 Jul → | ||
| 13–9 | -0.03 | 13% | 17 Jul → | ||
| 13–5 | 0.01 | 13% | 17 Jul → | ||
| 13–6 | -0.01 | 15% | 17 Jul → | ||
| 13–9 | -0.01 | 16% | 15 Jul → | ||
| 13–7 | 0.06 | 12% | 14 Jul → | ||
| 12–16 | 0.01 | 16% | 14 Jul → | ||
| 13–8 | 0.03 | 10% | 14 Jul → | ||
| 4–12 | -0.07 | 21% | 14 Jul → | ||
| 6–13 | -0.08 | 9% | 14 Jul → | ||
| 11–13 | -0.04 | 5% | 14 Jul → | ||
| 13–11 | -0.04 | 5% | 14 Jul → | ||
| 4–13 | -0.04 | 9% | 13 Jul → | ||
| 7–13 | -0.04 | 20% | 13 Jul → | ||
| 5–13 | -0.13 | 14% | 12 Jul → | ||
| 8–13 | -0.07 | 9% | 12 Jul → | ||
| 13–10 | 0.03 | 19% | 12 Jul → | ||
| 13–9 | -0.03 | 15% | 12 Jul → | ||
| 9–13 | -0.03 | 13% | 12 Jul → | ||
| 13–3 | 0.02 | 16% | 12 Jul → | ||
| 13–8 | -0.07 | 6% | 11 Jul → | ||
| 15–15 | 0.03 | 14% | 9 Jul → | ||
| 15–15 | 0.01 | 14% | 9 Jul → | ||
| 13–6 | 0.04 | 22% | 9 Jul → | ||
| 13–10 | -0.05 | 18% | 9 Jul → | ||
| 10–13 | 0.06 | 25% | 9 Jul → | ||
| 13–11 | 0.00 | 17% | 9 Jul → | ||
| 7–13 | 0.01 | 8% | 9 Jul → | ||
| 14–16 | -0.03 | 7% | 9 Jul → | ||
| 5–13 | -0.03 | 14% | 6 Jul → | ||
| 13–8 | -0.05 | 19% | 5 Jul → | ||
| 9–13 | -0.02 | 21% | 5 Jul → | ||
| 13–10 | 0.00 | 29% | 5 Jul → | ||
| 16–13 | -0.01 | 11% | 3 Jul → | ||
| 13–9 | 0.01 | 13% | 3 Jul → | ||
| 16–14 | -0.02 | 13% | 30 Jun → | ||
| 1–13 | -0.03 | 10% | 30 Jun → | ||
| 13–9 | 0.02 | 6% | 29 Jun → | ||
| 9–13 | -0.06 | 24% | 29 Jun → | ||
| 13–2 | 0.03 | 14% | 29 Jun → | ||
| 4–13 | -0.08 | 22% | 29 Jun → | ||
| 11–13 | -0.03 | 15% | 28 Jun → | ||
| 13–9 | -0.08 | 11% | 28 Jun → | ||
| 14–16 | 0.02 | 15% | 25 Jun → | ||
| 13–10 | -0.03 | 13% | 24 Jun → | ||
| 13–4 | 0.01 | 7% | 24 Jun → | ||
| 11–13 | -0.01 | 17% | 24 Jun → | ||
| 13–9 | -0.02 | 13% | 24 Jun → | ||
| 13–5 | -0.01 | 15% | 23 Jun → | ||
| 13–8 | -0.01 | 17% | 23 Jun → | ||
| 13–6 | 0.07 | 9% | 22 Jun → | ||
| 13–8 | -0.04 | 13% | 22 Jun → | ||
| 1–9 | -0.08 | 19% | 19 Jun → | ||
| 9–13 | 0.02 | 14% | 19 Jun → | ||
| 1–9 | -0.10 | 0% | 19 Jun → | ||
| 13–7 | 0.01 | 13% | 17 Jun → | ||
| 8–4 | -0.07 | 10% | 17 Jun → | ||
| 11–13 | -0.02 | 15% | 17 Jun → | ||
| 8–13 | -0.04 | 11% | 13 Jun → | ||
| 11–13 | -0.03 | 7% | 13 Jun → | ||
| 13–10 | -0.09 | 8% | 7 Jun → | ||
| 13–6 | -0.04 | 9% | 7 Jun → | ||
| 3–13 | -0.01 | 16% | 7 Jun → | ||
| 7–13 | 0.04 | 9% | 7 Jun → | ||
| 13–1 | 0.06 | 13% | 7 Jun → | ||
| 11–13 | 0.04 | 19% | 6 Jun → | ||
| 13–5 | -0.02 | 20% | 6 Jun → | ||
| 13–4 | 0.04 | 17% | 6 Jun → | ||
| 13–6 | 0.02 | 15% | 6 Jun → | ||
| 13–11 | 0.01 | 17% | 31 May → | ||
| 9–13 | -0.05 | 15% | 28 May → | ||
| 0–13 | -0.02 | 42% | 27 May → | ||
| 9–13 | -0.01 | 10% | 27 May → | ||
| 3–13 | -0.07 | 13% | 21 May → | ||
| 7–13 | -0.09 | 10% | 21 May → | ||
| 13–10 | -0.01 | 17% | 17 May → |
Match data via Leetify.