FACEIT_Darwin — CS2 Stats
76561199875696260[U:1:1915430532]
Rating over time
Premier CS Rating
- At peak — 29,461
- Next: Gold band at 30,000 — 539 to go
- Reached: Red band · Pink band · Purple band · Blue band
- Red band first seen 2026-08-28
- Pink band first seen 2026-08-28
CSDB's own observations — this history builds from the day a profile is first viewed and cannot be backfilled.
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -30pp win rate · +0.05 avg rating
Player DNA
Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.
Sharp aimerLimited utility dependence
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 s1mple 85% playstyle similarity
Most alike: opening-fight frequency, aim profile.
Where you differ: lower utility contribution.
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 100 — the mechanical foundation is a clear strength.
CT openings. 60% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
T openings. 64% T opening-duel success — entries that actually open the round.
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
Counter-strafing. Only 0% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.
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 6.8/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.05 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 |
|---|---|---|---|---|---|
| S | 36 | 25–11 | 69% | 0.06 | |
| A | 31 | 19–12 | 61% | 0.07 | |
| S | 13 | 9–4 | 69% | 0.06 | |
| D | 6 | 2–4 | 33% | 0.06 | |
| D | 6 | 2–4 | 33% | -0.01 | |
| S | 6 | 4–2 | 67% | -0.01 | |
| — | 2 | 2–0 | 100% | 0.05 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (33% over 6). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWWWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Dust2 | 76 | 53% | 1.34 | 18.2 |
| Mirage | 67 | 43% | 1.14 | 17.9 |
| Ancient | 66 | 74% | 1.41 | 17.9 |
| Anubis | 61 | 69% | 1.29 | 17.7 |
| Inferno | 37 | 62% | 1.42 | 19.7 |
| Nuke | 18 | 33% | 1.46 | 17.4 |
| Overpass | 13 | 77% | 1.39 | 19.0 |
| Cache | 13 | 85% | 1.53 | 19.1 |
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.
- Movement GuidePractice Config →
Under half your shots are taken fully stopped, so the bullets are going where the spread sends them rather than where you aim.
Counter-strafing 0% — below the 45% mark we flag
- Advanced MechanicsPractice Config →
Sustained sprays are missing more than they land, which is a recoil-control pattern you can drill directly.
Spray accuracy 0% — below the 20% mark we flag
- Grenades & UtilityGrenade Lineups →
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0 — below the 0.5 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 6 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 2–11 | 0.14 | 100% | 27 Jul → | ||
| 13–2 | 0.12 | 100% | 27 Jul → | ||
| 2–8 | 0.27 | 100% | 27 Jul → | ||
| 13–1 | 0.28 | 100% | 27 Jul → | ||
| 8–13 | 0.07 | 100% | 27 Jul → | ||
| 1–13 | 0.03 | 75% | 27 Jul → | ||
| 0–5 | -0.12 | 100% | 26 Jul → | ||
| 13–2 | 0.33 | 100% | 26 Jul → | ||
| 0–7 | 0.02 | 50% | 21 Jul → | ||
| 13–3 | 0.28 | 67% | 21 Jul → | ||
| 0–2 | -0.17 | 0% | 21 Jul → | ||
| 10–13 | 0.09 | 100% | 20 Jul → | ||
| 13–10 | 0.36 | 50% | 19 Jul → | ||
| 13–0 | 0.15 | 71% | 18 Jul → | ||
| 13–4 | 0.09 | 90% | 18 Jul → | ||
| 13–0 | 0.09 | 100% | 18 Jul → | ||
| 9–13 | 0.06 | 70% | 17 Jul → | ||
| 13–0 | 0.03 | 67% | 17 Jul → | ||
| 13–4 | 0.16 | 80% | 17 Jul → | ||
| 13–0 | 0.08 | 100% | 17 Jul → | ||
| 13–2 | 0.14 | 89% | 17 Jul → | ||
| 13–0 | 0.03 | 100% | 17 Jul → | ||
| 13–0 | 0.04 | 100% | 17 Jul → | ||
| 6–0 | 0.03 | 75% | 17 Jul → | ||
| 13–0 | 0.17 | 94% | 17 Jul → | ||
| 9–13 | 0.10 | 70% | 17 Jul → | ||
| 13–0 | 0.16 | 82% | 17 Jul → | ||
| 13–0 | 0.12 | 63% | 17 Jul → | ||
| 13–9 | 0.13 | 75% | 17 Jul → | ||
| 13–0 | 0.11 | 71% | 17 Jul → | ||
| 4–0 | 0.01 | 100% | 17 Jul → | ||
| 0–13 | -0.03 | 100% | 17 Jul → | ||
| 3–13 | -0.04 | 65% | 17 Jul → | ||
| 5–13 | -0.12 | 67% | 17 Jul → | ||
| 6–13 | 0.15 | 100% | 17 Jul → | ||
| 2–0 | 0.04 | 50% | 17 Jul → | ||
| 1–13 | 0.02 | 100% | 17 Jul → | ||
| 13–5 | 0.36 | 100% | 17 Jul → | ||
| 11–13 | 0.46 | 84% | 17 Jul → | ||
| 3–0 | 0.10 | 100% | 17 Jul → | ||
| 13–0 | 0.02 | 100% | 17 Jul → | ||
| 13–0 | 0.08 | 100% | 16 Jul → | ||
| 13–1 | 0.40 | 77% | 16 Jul → | ||
| 16–14 | -0.00 | 50% | 16 Jul → | ||
| 13–0 | 0.06 | 100% | 16 Jul → | ||
| 13–6 | -0.04 | 88% | 16 Jul → | ||
| 13–0 | 0.04 | 60% | 16 Jul → | ||
| 13–2 | 0.16 | 50% | 16 Jul → | ||
| 5–13 | -0.05 | 67% | 16 Jul → | ||
| 13–9 | -0.06 | 100% | 15 Jul → | ||
| 13–0 | 0.01 | 75% | 15 Jul → | ||
| 13–2 | 0.00 | 50% | 15 Jul → | ||
| 13–0 | 0.05 | 100% | 15 Jul → | ||
| 13–6 | 0.00 | 89% | 15 Jul → | ||
| 13–0 | 0.08 | 67% | 15 Jul → | ||
| 1–5 | -0.03 | 100% | 15 Jul → | ||
| 13–0 | 0.10 | 80% | 15 Jul → | ||
| 13–1 | 0.02 | 80% | 15 Jul → | ||
| 13–1 | 0.10 | 100% | 15 Jul → | ||
| 13–0 | 0.06 | 80% | 14 Jul → | ||
| 13–0 | 0.02 | 0% | 14 Jul → | ||
| 5–13 | -0.13 | 9% | 5 Jul → | ||
| 13–7 | 0.00 | 19% | 5 Jul → | ||
| 13–11 | 0.02 | 27% | 4 Jul → | ||
| 2–6 | -0.02 | 38% | 4 Jul → | ||
| 4–13 | -0.13 | 0% | 4 Jul → | ||
| 8–13 | -0.02 | 27% | 4 Jul → | ||
| 13–11 | 0.11 | 19% | 4 Jul → | ||
| 9–13 | 0.03 | 10% | 4 Jul → | ||
| 13–7 | -0.00 | 21% | 4 Jul → | ||
| 0–5 | 0.04 | 50% | 4 Jul → | ||
| 13–8 | 0.05 | 30% | 4 Jul → | ||
| 13–6 | 0.06 | 29% | 4 Jul → | ||
| 13–4 | 0.00 | 19% | 4 Jul → | ||
| 1–2 | -0.06 | 100% | 4 Jul → | ||
| 8–13 | 0.04 | 30% | 4 Jul → | ||
| 13–5 | 0.07 | 40% | 4 Jul → | ||
| 16–13 | 0.02 | 46% | 4 Jul → | ||
| 13–8 | 0.01 | 12% | 4 Jul → | ||
| 13–5 | 0.06 | 14% | 3 Jul → | ||
| 3–13 | -0.03 | 47% | 3 Jul → | ||
| 13–2 | -0.03 | 40% | 3 Jul → | ||
| 13–9 | 0.04 | 39% | 3 Jul → | ||
| 13–5 | 0.10 | 37% | 3 Jul → | ||
| 13–4 | 0.02 | 24% | 3 Jul → | ||
| 4–13 | -0.06 | 20% | 3 Jul → | ||
| 13–6 | 0.06 | 32% | 3 Jul → | ||
| 3–13 | -0.01 | 42% | 3 Jul → | ||
| 4–9 | -0.05 | 22% | 3 Jul → | ||
| 8–13 | 0.02 | 25% | 2 Jul → | ||
| 7–13 | 0.06 | 24% | 2 Jul → | ||
| 8–13 | 0.00 | 25% | 1 Jul → | ||
| 13–9 | 0.02 | 33% | 1 Jul → | ||
| 13–9 | 0.00 | 23% | 1 Jul → | ||
| 8–13 | 0.01 | 13% | 1 Jul → | ||
| 9–13 | -0.05 | 44% | 1 Jul → | ||
| 13–10 | -0.01 | 30% | 1 Jul → | ||
| 2–13 | -0.06 | 20% | 1 Jul → | ||
| 13–7 | 0.04 | 28% | 30 Jun → | ||
| 1–13 | -0.01 | 30% | 30 Jun → |
Match data via Leetify.