W1LDG2 — CS2 Stats
76561198799372400[U:1:839106672]
Rating over time
Faceit ELO
- At peak — 2,885
- Next: 3,000 ELO at 3,000 — 115 to go
- Reached: 2,500 ELO · Level 10 · Level 9 · Level 8
CSDB's own observations — this history builds from the day a profile is first viewed and cannot be backfilled.
How this compares with the same rank
Median values for Level 10 among CSDB-tracked players (n=218), 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 | 70.7% | 52.8% |
| Shot accuracy | 17.4% | 13.7% |
| Kill/death ratio | 1.26 | 1.08 |
| Match win rate | 50.0% | 49.2% |
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -10pp win rate · -0.05 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
Sharp aimer
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 donk 94% playstyle similarity
Most alike: opening-duel success, opening-fight frequency.
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
Aim. Aim score of 85 — the mechanical foundation is a clear strength.
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
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 7.3/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.02 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 |
|---|---|---|---|---|---|
 nuke | S | 19 | 13–6 | 68% | 0.03 |
 overpass | S | 17 | 11–6 | 65% | 0.02 |
 dust2 | S | 17 | 13–4 | 76% | 0.01 |
 anubis | S | 12 | 8–4 | 67% | 0.00 |
 mirage | S | 9 | 6–3 | 67% | 0.02 |
 cache | A | 8 | 5–3 | 63% | 0.00 |
 inferno | B | 8 | 4–4 | 50% | 0.01 |
 ancient | S | 6 | 5–1 | 83% | 0.03 |
 train | — | 4 | 1–3 | 25% | 0.02 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (50% over 8). Start with the 6 essential Inferno 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 resultsWLLWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 138 | 59% | 1.31 | 18.2 |
| Nuke | 105 | 59% | 1.21 | 15.6 |
| Dust2 | 72 | 51% | 1.15 | 15.6 |
| Anubis | 66 | 61% | 1.33 | 16.5 |
| Ancient | 65 | 48% | 1.20 | 17.1 |
| Overpass | 63 | 56% | 1.25 | 17.9 |
| Inferno | 58 | 43% | 1.15 | 15.2 |
| Train | 35 | 54% | 1.39 | 17.8 |
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.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| nuke | 13–6 | 0.08 | 30% | 28 Jun → | |
| cache | 9–13 | -0.00 | 30% | 11 Jun → | |
| anubis | 8–13 | -0.05 | 22% | 3 Jun → | |
| overpass | 13–11 | -0.08 | 22% | 3 Jun → | |
| dust2 | 13–10 | -0.01 | 16% | 31 May → | |
| cache | 13–7 | -0.02 | 14% | 31 May → | |
| overpass | 13–9 | -0.00 | 19% | 29 May → | |
| anubis | 2–13 | -0.02 | 15% | 24 May → | |
| ancient | 13–5 | -0.02 | 12% | 24 May → | |
| dust2 | 13–2 | 0.02 | 23% | 24 May → | |
| ancient | 13–2 | 0.18 | 16% | 24 May → | |
| mirage | 19–16 | 0.02 | 13% | 24 May → | |
| inferno | 5–13 | -0.05 | 26% | 24 May → | |
| mirage | 13–7 | 0.07 | 41% | 22 May → | |
| dust2 | 13–5 | 0.07 | 17% | 21 May → | |
| mirage | 13–6 | 0.08 | 26% | 19 May → | |
| anubis | 13–11 | -0.02 | 16% | 15 May → | |
| overpass | 13–8 | 0.04 | 25% | 13 May → | |
| anubis | 13–11 | 0.02 | 22% | 12 May → | |
| overpass | 8–13 | 0.02 | 13% | 12 May → | |
| overpass | 13–5 | 0.08 | 32% | 10 May → | |
| nuke | 16–12 | -0.02 | 17% | 10 May → | |
| ancient | 13–5 | -0.03 | 17% | 9 May → | |
| overpass | 17–19 | 0.02 | 19% | 9 May → | |
| cache | 9–13 | 0.07 | 25% | 8 May → | |
| anubis | 13–7 | 0.03 | 20% | 8 May → | |
| anubis | 8–13 | -0.02 | 24% | 6 May → | |
| anubis | 13–10 | 0.03 | 31% | 6 May → | |
| cache | 13–3 | -0.01 | 16% | 3 May → | |
| cache | 13–3 | -0.02 | 19% | 3 May → | |
| overpass | 13–8 | -0.03 | 32% | 2 May → | |
| anubis | 9–13 | 0.08 | 23% | 2 May → | |
| nuke | 13–6 | -0.01 | 19% | 2 May → | |
| ancient | 13–10 | 0.08 | 17% | 2 May → | |
| cache | 13–5 | -0.01 | 22% | 2 May → | |
| mirage | 4–13 | -0.05 | 11% | 2 May → | |
| dust2 | 3–13 | -0.03 | 11% | 1 May → | |
| inferno | 10–13 | 0.00 | 16% | 30 Apr → | |
| dust2 | 13–9 | -0.01 | 14% | 30 Apr → | |
| cache | 13–10 | 0.03 | 17% | 29 Apr → | |
| cache | 8–13 | -0.00 | 14% | 29 Apr → | |
| dust2 | 13–5 | 0.04 | 14% | 22 Apr → | |
| dust2 | 9–13 | 0.00 | 21% | 21 Apr → | |
| nuke | 16–12 | 0.03 | 17% | 18 Apr → | |
| nuke | 13–6 | 0.13 | 21% | 18 Apr → | |
| overpass | 9–13 | 0.06 | 17% | 18 Apr → | |
| mirage | 13–3 | 0.07 | 15% | 18 Apr → | |
| overpass | 13–10 | 0.04 | 20% | 15 Apr → | |
| dust2 | 9–13 | 0.02 | 15% | 14 Apr → | |
| anubis | 13–4 | 0.01 | 21% | 10 Apr → | |
| dust2 | 13–7 | -0.03 | 11% | 8 Apr → | |
| mirage | 13–5 | 0.10 | 18% | 30 Mar → | |
| dust2 | 28–25 | 0.01 | 16% | 27 Feb → | |
| mirage | 11–13 | -0.06 | 21% | 20 Feb → | |
| overpass | 13–3 | 0.11 | 19% | 15 Feb → | |
| dust2 | 13–5 | -0.01 | 21% | 8 Feb → | |
| overpass | 16–14 | 0.01 | 20% | 8 Feb → | |
| overpass | 17–19 | -0.03 | 19% | 6 Feb → | |
| anubis | 13–8 | -0.03 | 16% | 4 Feb → | |
| anubis | 13–10 | -0.00 | 14% | 29 Jan → | |
| dust2 | 8–13 | -0.06 | 13% | 28 Jan → | |
| anubis | 13–11 | -0.01 | 10% | 23 Jan → | |
| nuke | 13–3 | 0.05 | 27% | 21 Jan → | |
| nuke | 13–11 | 0.05 | 23% | 16 Jan → | |
| nuke | 7–13 | -0.02 | 18% | 14 Jan → | |
| overpass | 13–11 | 0.03 | 13% | 11 Jan → | |
| nuke | 13–8 | -0.01 | 15% | 11 Jan → | |
| nuke | 13–11 | 0.01 | 13% | 9 Jan → | |
| overpass | 11–13 | -0.02 | 21% | 6 Jan → | |
| dust2 | 13–8 | 0.05 | 21% | 6 Jan → | |
| nuke | 7–13 | -0.08 | 21% | 4 Jan → | |
| train | 11–13 | -0.01 | 24% | 3 Jan → | |
| ancient | 7–13 | -0.02 | 15% | 3 Jan → | |
| inferno | 13–5 | 0.14 | 25% | 30 Dec → | |
| inferno | 13–8 | -0.01 | 19% | 30 Dec → | |
| mirage | 14–16 | -0.04 | 18% | 30 Dec → | |
| overpass | 13–7 | 0.05 | 23% | 28 Dec → | |
| overpass | 13–10 | 0.08 | 28% | 28 Dec → | |
| dust2 | 13–7 | 0.06 | 27% | 28 Dec → | |
| train | 16–19 | 0.01 | 18% | 28 Dec → | |
| train | 13–6 | 0.03 | 19% | 20 Dec → | |
| train | 6–13 | 0.03 | 22% | 14 Dec → | |
| nuke | 6–13 | 0.02 | 21% | 14 Dec → | |
| overpass | 8–13 | -0.04 | 16% | 7 Dec → | |
| nuke | 13–8 | 0.03 | 30% | 7 Dec → | |
| nuke | 11–13 | -0.01 | 22% | 7 Dec → | |
| dust2 | 13–8 | 0.01 | 25% | 1 Dec → | |
| nuke | 8–13 | 0.06 | 28% | 30 Nov → | |
| inferno | 13–8 | -0.00 | 14% | 30 Nov → | |
| inferno | 13–3 | 0.13 | 20% | 24 Nov → | |
| dust2 | 13–11 | 0.01 | 27% | 24 Nov → | |
| ancient | 13–10 | -0.01 | 14% | 18 Nov → | |
| nuke | 13–1 | 0.05 | 27% | 15 Nov → | |
| nuke | 13–6 | 0.06 | 24% | 15 Nov → | |
| inferno | 7–13 | -0.03 | 17% | 15 Nov → | |
| nuke | 8–13 | -0.04 | 15% | 15 Nov → | |
| dust2 | 13–11 | 0.04 | 29% | 14 Nov → | |
| nuke | 13–5 | 0.10 | 31% | 14 Nov → | |
| mirage | 13–5 | 0.03 | 29% | 14 Nov → | |
| inferno | 9–13 | -0.07 | 8% | 14 Nov → |
Match data via Leetify.
