Przybysz — CS2 Stats
76561198383118417[U:1:422852689]
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +40pp win rate · +0.02 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 b1t 93% playstyle similarity
Most alike: opening-duel success, opening-fight frequency.
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 92 — the mechanical foundation is a clear strength.
Areas to improve
Positioning. Positioning trails aim by 36 points — deaths here waste a strong aim profile.
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 7.2/10 (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 |
|---|---|---|---|---|---|
 dust2 | B | 23 | 12–11 | 52% | 0.01 |
| office | B | 19 | 10–9 | 53% | 0.03 |
 cache | A | 12 | 7–5 | 58% | 0.01 |
 nuke | D | 9 | 2–7 | 22% | -0.01 |
 mirage | B | 8 | 4–4 | 50% | -0.01 |
| italy | D | 6 | 2–4 | 33% | 0.00 |
 train | S | 6 | 4–2 | 67% | 0.05 |
 inferno | D | 5 | 1–4 | 20% | 0.00 |
 ancient | — | 4 | 3–1 | 75% | 0.02 |
 anubis | — | 3 | 2–1 | 67% | 0.09 |
| shelter | — | 3 | 2–1 | 67% | 0.09 |
 overpass | — | 2 | 1–1 | 50% | -0.02 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWLLLW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 7 | 43% | 1.16 | 19.3 |
| Nuke | 5 | 60% | 1.16 | 19.4 |
| Inferno | 3 | 100% | 1.94 | 20.0 |
| Anubis | 3 | 67% | 0.85 | 10.0 |
| Ancient | 1 | 0% | 1.18 | 20.0 |
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.
- 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 0.4967 — 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 37.0632% — 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.
20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| office | 13–8 | 0.07 | 21% | 27 Aug → | |
| dust2 | 13–6 | 0.03 | 16% | 27 Aug → | |
| cache | 13–3 | 0.03 | 13% | 27 Aug → | |
| dust2 | 13–2 | 0.05 | 9% | 27 Aug → | |
| cache | 13–8 | -0.09 | 16% | 27 Aug → | |
| dust2 | 6–13 | -0.00 | 21% | 26 Aug → | |
| dust2 | 13–7 | -0.00 | 21% | 26 Aug → | |
| office | 13–9 | 0.01 | 10% | 25 Aug → | |
| office | 13–11 | 0.05 | 15% | 24 Aug → | |
| office | 2–8 | 0.05 | 29% | 24 Aug → | |
| italy | 10–13 | 0.06 | 13% | 24 Aug → | |
| dust2 | 5–13 | -0.09 | 21% | 23 Aug → | |
| dust2 | 8–13 | 0.04 | 25% | 21 Aug → | |
| inferno | 0–6 | -0.01 | 43% | 21 Aug → | |
| italy | 12–12 | -0.03 | 12% | 20 Aug → | |
| office | 2–13 | 0.02 | 32% | 20 Aug → | |
| nuke | 11–2 | -0.02 | 19% | 20 Aug → | |
| dust2 | 13–5 | -0.02 | 16% | 19 Aug → | |
| mirage | 11–5 | 0.03 | 12% | 19 Aug → | |
| cache | 13–7 | 0.00 | 7% | 19 Aug → | |
| mirage | 13–7 | -0.05 | 30% | 18 Aug → | |
| nuke | 10–13 | 0.03 | 23% | 17 Aug → | |
| train | 13–7 | 0.03 | 24% | 17 Aug → | |
| office | 6–13 | -0.02 | 27% | 17 Aug → | |
| mirage | 13–11 | 0.02 | 24% | 16 Aug → | |
| ancient | 8–2 | 0.05 | 13% | 16 Aug → | |
| dust2 | 13–8 | 0.06 | 24% | 16 Aug → | |
| dust2 | 13–9 | -0.02 | 17% | 15 Aug → | |
| dust2 | 13–11 | 0.13 | 22% | 15 Aug → | |
| dust2 | 13–5 | 0.07 | 10% | 14 Aug → | |
| dust2 | 4–13 | -0.02 | 15% | 14 Aug → | |
| nuke | 3–13 | -0.00 | 12% | 13 Aug → | |
| cache | 12–12 | 0.04 | 17% | 12 Aug → | |
| train | 13–2 | 0.13 | 23% | 12 Aug → | |
| office | 13–4 | 0.06 | 28% | 12 Aug → | |
| cache | 9–13 | -0.11 | 13% | 12 Aug → | |
| dust2 | 13–11 | 0.06 | 7% | 12 Aug → | |
| dust2 | 13–4 | 0.07 | 20% | 12 Aug → | |
| dust2 | 8–13 | 0.01 | 20% | 10 Aug → | |
| mirage | 9–13 | 0.01 | 15% | 10 Aug → | |
| inferno | 0–13 | -0.06 | 25% | 10 Aug → | |
| italy | 13–6 | 0.01 | 29% | 9 Aug → | |
| nuke | 13–7 | 0.07 | 24% | 9 Aug → | |
| office | 13–8 | 0.01 | 20% | 9 Aug → | |
| office | 13–3 | -0.01 | 11% | 8 Aug → | |
| dust2 | 12–12 | -0.02 | 18% | 8 Aug → | |
| office | 4–13 | -0.00 | 36% | 8 Aug → | |
| dust2 | 6–13 | 0.02 | 18% | 7 Aug → | |
| italy | 0–13 | -0.05 | 10% | 7 Aug → | |
| office | 13–1 | 0.10 | 23% | 7 Aug → | |
| office | 2–0 | 0.00 | 0% | 7 Aug → | |
| italy | 13–7 | 0.01 | 18% | 6 Aug → | |
| office | 12–12 | 0.03 | 30% | 6 Aug → | |
| mirage | 9–13 | -0.03 | 19% | 6 Aug → | |
| dust2 | 12–12 | -0.01 | 20% | 5 Aug → | |
| mirage | 13–9 | 0.03 | 16% | 5 Aug → | |
| office | 9–13 | 0.01 | 24% | 3 Aug → | |
| dust2 | 11–13 | -0.04 | 18% | 3 Aug → | |
| cache | 9–13 | 0.00 | 17% | 2 Aug → | |
| inferno | 14–16 | -0.02 | 12% | 31 Jul → | |
| ancient | 13–10 | 0.00 | 16% | 30 Jul → | |
| cache | 13–7 | 0.13 | 32% | 30 Jul → | |
| inferno | 13–11 | 0.01 | 36% | 29 Jul → | |
| nuke | 5–13 | -0.13 | 20% | 29 Jul → | |
| mirage | 10–13 | -0.07 | 15% | 28 Jul → | |
| dust2 | 2–13 | -0.10 | 21% | 28 Jul → | |
| office | 10–13 | 0.04 | 40% | 25 Jul → | |
| office | 3–13 | -0.07 | 29% | 22 Jul → | |
| cache | 13–4 | 0.08 | 9% | 22 Jul → | |
| nuke | 9–13 | -0.04 | 20% | 22 Jul → | |
| anubis | 11–13 | 0.03 | 11% | 22 Jul → | |
| nuke | 9–13 | -0.05 | 17% | 20 Jul → | |
| train | 9–13 | 0.06 | 28% | 20 Jul → | |
| cache | 7–13 | 0.01 | 31% | 20 Jul → | |
| shelter | 12–12 | 0.05 | 18% | 19 Jul → | |
| shelter | 13–3 | 0.15 | 29% | 19 Jul → | |
| office | 5–13 | -0.00 | 29% | 19 Jul → | |
| italy | 5–13 | 0.03 | 34% | 19 Jul → | |
| shelter | 9–2 | 0.08 | 47% | 19 Jul → | |
| office | 13–9 | 0.01 | 27% | 19 Jul → | |
| train | 7–13 | 0.04 | 37% | 19 Jul → | |
| cache | 2–13 | -0.08 | 19% | 19 Jul → | |
| dust2 | 6–13 | -0.04 | 26% | 19 Jul → | |
| office | 6–2 | 0.20 | 47% | 18 Jul → | |
| anubis | 13–3 | 0.17 | 44% | 18 Jul → | |
| ancient | 7–13 | 0.05 | 19% | 18 Jul → | |
| inferno | 6–13 | 0.08 | 24% | 18 Jul → | |
| mirage | 9–13 | -0.03 | 16% | 18 Jul → | |
| train | 13–10 | -0.01 | 34% | 18 Jul → | |
| overpass | 12–12 | -0.02 | 33% | 18 Jul → | |
| cache | 13–7 | 0.07 | 25% | 18 Jul → | |
| dust2 | 13–7 | -0.02 | 24% | 18 Jul → | |
| nuke | 7–13 | 0.01 | 6% | 18 Jul → | |
| train | 13–1 | 0.05 | 15% | 17 Jul → | |
| anubis | 13–3 | 0.06 | 20% | 17 Jul → | |
| dust2 | 13–7 | -0.00 | 29% | 17 Jul → | |
| ancient | 13–11 | -0.01 | 14% | 17 Jul → | |
| nuke | 12–12 | 0.04 | 28% | 17 Jul → | |
| cache | 13–8 | -0.01 | 25% | 17 Jul → | |
| overpass | 13–9 | -0.01 | 19% | 17 Jul → |
Match data via Leetify.