Annulleddeer — CS2 Stats
76561198135847058[U:1:175581330]
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -30pp win rate · -0.02 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
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 b1t 90% playstyle similarity
Most alike: opening-duel success, opening-fight frequency.
Where you differ: lower utility contribution; 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
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
Reaction time. 563ms 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 6.1/10 (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 |
|---|---|---|---|---|---|
 mirage | C | 20 | 8–12 | 40% | -0.01 |
 inferno | B | 19 | 9–10 | 47% | 0.02 |
 nuke | A | 16 | 9–7 | 56% | -0.00 |
 ancient | A | 12 | 7–5 | 58% | 0.01 |
 anubis | D | 12 | 4–8 | 33% | 0.01 |
 cache | S | 8 | 6–2 | 75% | 0.03 |
 overpass | A | 8 | 5–3 | 63% | -0.00 |
 dust2 | — | 4 | 3–1 | 75% | 0.03 |
 train | — | 1 | 1–0 | 100% | 0.03 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (33% over 12). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWWLW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 14 | 36% | 1.25 | 16.2 |
| Ancient | 12 | 75% | 1.18 | 20.5 |
| Inferno | 8 | 75% | 1.55 | 21.1 |
| Anubis | 6 | 17% | 1.09 | 19.3 |
| Dust2 | 5 | 80% | 1.70 | 22.2 |
| Nuke | 5 | 60% | 0.81 | 13.2 |
| Train | 2 | 50% | 1.03 | 24.5 |
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.
- 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 0.4051 — below the 0.5 mark we flag
- 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 34.3885% — 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 12 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| inferno | 14–16 | -0.03 | 20% | 27 Aug → | |
| dust2 | 13–9 | 0.02 | 26% | 26 Aug → | |
| inferno | 4–13 | -0.07 | 10% | 25 Aug → | |
| ancient | 13–3 | 0.05 | 18% | 25 Aug → | |
| mirage | 2–13 | -0.05 | 16% | 24 Aug → | |
| inferno | 13–10 | 0.00 | 23% | 24 Aug → | |
| cache | 13–5 | -0.02 | 20% | 23 Aug → | |
| anubis | 12–16 | 0.02 | 18% | 23 Aug → | |
| mirage | 13–10 | 0.05 | 17% | 22 Aug → | |
| anubis | 5–13 | 0.01 | 14% | 21 Aug → | |
| inferno | 13–5 | 0.09 | 12% | 21 Aug → | |
| anubis | 13–7 | 0.01 | 6% | 21 Aug → | |
| inferno | 13–1 | 0.02 | 18% | 21 Aug → | |
| nuke | 13–10 | 0.04 | 25% | 21 Aug → | |
| mirage | 8–13 | -0.07 | 31% | 20 Aug → | |
| nuke | 13–9 | -0.03 | 19% | 20 Aug → | |
| mirage | 13–4 | 0.02 | 18% | 20 Aug → | |
| nuke | 6–13 | 0.00 | 67% | 8 Aug → | |
| inferno | 7–1 | 0.10 | 100% | 8 Aug → | |
| mirage | 13–11 | 0.00 | 16% | 8 Aug → | |
| overpass | 13–6 | 0.06 | 28% | 8 Aug → | |
| dust2 | 13–4 | 0.11 | 16% | 8 Aug → | |
| anubis | 13–5 | 0.05 | 18% | 8 Aug → | |
| nuke | 13–11 | 0.02 | 25% | 8 Aug → | |
| inferno | 6–13 | -0.02 | 24% | 8 Aug → | |
| cache | 11–13 | 0.06 | 20% | 8 Aug → | |
| mirage | 8–13 | 0.00 | 12% | 7 Aug → | |
| ancient | 10–13 | -0.04 | 16% | 7 Aug → | |
| inferno | 8–13 | 0.01 | 17% | 7 Aug → | |
| nuke | 13–10 | 0.00 | 14% | 7 Aug → | |
| mirage | 10–13 | -0.02 | 21% | 7 Aug → | |
| anubis | 9–13 | 0.00 | 11% | 7 Aug → | |
| anubis | 10–13 | -0.05 | 5% | 6 Aug → | |
| mirage | 5–13 | -0.08 | 26% | 6 Aug → | |
| ancient | 11–13 | -0.00 | 13% | 6 Aug → | |
| nuke | 4–13 | -0.09 | 7% | 6 Aug → | |
| inferno | 9–13 | -0.03 | 15% | 6 Aug → | |
| cache | 16–14 | 0.01 | 24% | 6 Aug → | |
| ancient | 13–11 | 0.03 | 19% | 6 Aug → | |
| mirage | 13–8 | -0.02 | 19% | 3 Aug → | |
| nuke | 13–4 | 0.06 | 18% | 3 Aug → | |
| inferno | 13–4 | 0.05 | 20% | 2 Aug → | |
| nuke | 0–5 | -0.07 | 0% | 31 Jul → | |
| inferno | 14–16 | -0.00 | 12% | 31 Jul → | |
| cache | 10–13 | 0.03 | 22% | 31 Jul → | |
| inferno | 10–13 | 0.01 | 0% | 29 Jul → | |
| ancient | 13–10 | 0.01 | 13% | 26 Jul → | |
| inferno | 9–13 | 0.01 | 26% | 24 Jul → | |
| mirage | 13–7 | 0.06 | 22% | 24 Jul → | |
| cache | 13–8 | 0.11 | 16% | 24 Jul → | |
| mirage | 10–13 | -0.01 | 16% | 20 Jul → | |
| ancient | 9–13 | -0.01 | 15% | 17 Jul → | |
| cache | 13–10 | 0.02 | 24% | 8 Jul → | |
| train | 13–5 | 0.03 | 29% | 7 Jul → | |
| nuke | 8–13 | 0.01 | 12% | 6 Jul → | |
| overpass | 13–7 | 0.03 | 13% | 6 Jul → | |
| ancient | 13–7 | 0.04 | 16% | 5 Jul → | |
| ancient | 13–16 | 0.03 | 16% | 27 Jun → | |
| cache | 13–8 | 0.01 | 24% | 26 Jun → | |
| anubis | 13–6 | 0.09 | 18% | 26 Jun → | |
| anubis | 11–13 | -0.04 | 14% | 25 Jun → | |
| nuke | 13–11 | -0.05 | 9% | 25 Jun → | |
| inferno | 13–6 | 0.09 | 28% | 17 Jun → | |
| inferno | 6–13 | -0.04 | 15% | 3 Jun → | |
| anubis | 13–7 | 0.01 | 17% | 3 Jun → | |
| mirage | 11–13 | -0.00 | 20% | 3 Jun → | |
| overpass | 8–13 | -0.03 | 16% | 2 Jun → | |
| overpass | 10–13 | -0.04 | 18% | 27 May → | |
| mirage | 13–9 | 0.02 | 18% | 27 May → | |
| nuke | 7–13 | -0.03 | 19% | 26 May → | |
| mirage | 8–13 | -0.02 | 26% | 21 May → | |
| mirage | 6–13 | -0.07 | 20% | 19 May → | |
| nuke | 13–9 | 0.10 | 17% | 19 May → | |
| nuke | 7–13 | 0.01 | 21% | 11 May → | |
| dust2 | 13–10 | 0.01 | 21% | 6 May → | |
| cache | 13–10 | -0.00 | 15% | 30 Apr → | |
| nuke | 11–13 | 0.02 | 18% | 28 Apr → | |
| anubis | 10–13 | 0.08 | 11% | 28 Apr → | |
| inferno | 9–13 | 0.08 | 18% | 28 Apr → | |
| mirage | 7–13 | 0.04 | 24% | 28 Apr → | |
| overpass | 13–8 | -0.03 | 3% | 28 Apr → | |
| inferno | 13–10 | -0.04 | 29% | 28 Apr → | |
| overpass | 10–13 | 0.03 | 14% | 27 Apr → | |
| mirage | 8–13 | -0.01 | 18% | 26 Apr → | |
| overpass | 13–10 | -0.00 | 12% | 26 Apr → | |
| mirage | 3–13 | -0.01 | 21% | 25 Apr → | |
| ancient | 4–13 | -0.02 | 23% | 25 Apr → | |
| dust2 | 10–13 | -0.02 | 14% | 25 Apr → | |
| mirage | 13–5 | -0.10 | 4% | 25 Apr → | |
| inferno | 13–3 | 0.03 | 22% | 22 Apr → | |
| ancient | 13–9 | 0.03 | 17% | 22 Apr → | |
| anubis | 9–13 | 0.00 | 12% | 19 Apr → | |
| ancient | 13–5 | 0.07 | 15% | 17 Apr → | |
| mirage | 13–5 | 0.04 | 30% | 17 Apr → | |
| nuke | 13–6 | -0.04 | 29% | 16 Apr → | |
| overpass | 13–3 | -0.03 | 17% | 16 Apr → | |
| ancient | 13–6 | -0.07 | 14% | 16 Apr → | |
| anubis | 5–13 | -0.02 | 15% | 16 Apr → | |
| inferno | 13–5 | 0.03 | 14% | 14 Apr → | |
| nuke | 13–10 | 0.01 | 16% | 14 Apr → |
Match data via Leetify.