miksoz — CS2 Stats
CA76561199055818824[U:1:1095553096]Steam profile ↗✓ No bans
Rating over time
Faceit ELO
- At peak — 3,793
- Next: 4,000 ELO at 4,000 — 207 to go
- Reached: 3,500 ELO · 3,000 ELO · 2,500 ELO · Level 10
- 3,500 ELO first seen 2026-08-29
- 3,000 ELO first seen 2026-08-29
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 · -0.02 avg rating
Player DNA
Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.
Sharp aimerStrong 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 m0NESY 94% playstyle similarity
Most alike: opening-fight frequency, positioning profile.
Where you differ: higher opening-duel success.
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 96 — the mechanical foundation is a clear strength.
CT openings. 78% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
T openings. 62% 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.
T-side openings. Opening success drops from 78% on CT to 62% on T — the same duels are being taken with worse setups on the attacking side.
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 8.8/10 (Elite), 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 |
|---|---|---|---|---|---|
| A | 22 | 14–8 | 64% | 0.06 | |
| A | 17 | 10–7 | 59% | 0.04 | |
| A | 16 | 9–7 | 56% | 0.03 | |
| B | 12 | 6–6 | 50% | 0.09 | |
| B | 12 | 6–6 | 50% | 0.04 | |
| S | 12 | 8–4 | 67% | 0.06 | |
| A | 5 | 3–2 | 60% | 0.09 | |
| — | 2 | 2–0 | 100% | 0.12 | |
| italy | — | 1 | 1–0 | 100% | 0.11 |
| — | 1 | 1–0 | 100% | 0.32 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (50% 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 resultsWWLWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 1160 | 55% | 1.32 | 18.1 |
| Ancient | 771 | 53% | 1.26 | 17.0 |
| Anubis | 619 | 51% | 1.24 | 17.6 |
| Dust2 | 592 | 55% | 1.27 | 16.9 |
| Inferno | 221 | 54% | 1.36 | 18.0 |
| Nuke | 95 | 52% | 1.23 | 16.2 |
| Vertigo | 49 | 41% | 1.22 | 17.5 |
| Train | 36 | 53% | 1.14 | 15.2 |
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 | |
|---|---|---|---|---|---|
| 10–13 | 0.05 | 29% | 29 Aug → | ||
| 7–13 | 0.12 | 29% | 28 Aug → | ||
| 9–13 | 0.08 | 22% | 28 Aug → | ||
| 13–6 | 0.17 | 26% | 28 Aug → | ||
| italy | 13–6 | 0.11 | 44% | 27 Aug → | |
| 3–6 | -0.03 | 21% | 27 Aug → | ||
| 7–13 | 0.00 | 24% | 27 Aug → | ||
| 13–4 | -0.00 | 16% | 27 Aug → | ||
| 13–10 | 0.12 | 32% | 26 Aug → | ||
| 13–11 | 0.09 | 27% | 26 Aug → | ||
| 13–10 | 0.10 | 40% | 25 Aug → | ||
| 13–2 | 0.07 | 33% | 24 Aug → | ||
| 13–10 | 0.09 | 33% | 23 Aug → | ||
| 13–2 | 0.17 | 24% | 19 Aug → | ||
| 13–8 | 0.05 | 39% | 16 Aug → | ||
| 2–13 | 0.06 | 26% | 16 Aug → | ||
| 13–11 | 0.19 | 46% | 16 Aug → | ||
| 13–11 | 0.06 | 27% | 15 Aug → | ||
| 13–7 | 0.03 | 46% | 15 Aug → | ||
| 9–13 | 0.09 | 30% | 14 Aug → | ||
| 13–11 | 0.06 | 52% | 14 Aug → | ||
| 13–11 | 0.12 | 20% | 14 Aug → | ||
| 13–3 | 0.21 | 32% | 14 Aug → | ||
| 13–7 | 0.18 | 21% | 13 Aug → | ||
| 13–4 | 0.06 | 33% | 13 Aug → | ||
| 13–5 | 0.13 | 33% | 11 Aug → | ||
| 10–13 | 0.02 | 32% | 9 Aug → | ||
| 13–11 | 0.02 | 27% | 9 Aug → | ||
| 12–12 | 0.16 | 33% | 9 Aug → | ||
| 10–8 | 0.22 | 39% | 9 Aug → | ||
| 14–16 | 0.05 | 32% | 7 Aug → | ||
| 9–1 | 0.32 | 30% | 6 Aug → | ||
| 9–2 | 0.32 | 23% | 6 Aug → | ||
| 11–13 | 0.07 | 37% | 6 Aug → | ||
| 7–13 | 0.01 | 24% | 5 Aug → | ||
| 13–7 | 0.08 | 24% | 30 Jul → | ||
| 13–9 | 0.19 | 20% | 30 Jul → | ||
| 11–13 | 0.07 | 29% | 25 Jul → | ||
| 13–0 | 0.16 | 44% | 25 Jul → | ||
| 10–13 | 0.02 | 41% | 24 Jul → | ||
| 11–13 | -0.04 | 24% | 23 Jul → | ||
| 13–4 | 0.11 | 43% | 29 May → | ||
| 16–14 | 0.01 | 33% | 15 May → | ||
| 10–13 | 0.08 | 26% | 11 May → | ||
| 4–13 | 0.04 | 36% | 11 May → | ||
| 13–2 | 0.13 | 31% | 11 May → | ||
| 1–3 | -0.01 | 17% | 9 May → | ||
| 5–13 | -0.07 | 13% | 9 May → | ||
| 2–3 | 0.02 | 25% | 9 May → | ||
| 13–8 | 0.06 | 45% | 7 May → | ||
| 7–13 | 0.03 | 25% | 5 May → | ||
| 13–4 | 0.05 | 24% | 5 May → | ||
| 10–0 | 0.08 | 0% | 5 May → | ||
| 0–4 | -0.03 | 33% | 18 Apr → | ||
| 13–2 | 0.13 | 19% | 18 Apr → | ||
| 5–13 | -0.02 | 36% | 18 Apr → | ||
| 3–1 | 0.07 | 57% | 18 Apr → | ||
| 13–4 | 0.01 | 35% | 18 Apr → | ||
| 3–13 | 0.03 | 32% | 18 Apr → | ||
| 10–13 | 0.01 | 24% | 18 Apr → | ||
| 13–3 | 0.01 | 48% | 13 Apr → | ||
| 13–10 | 0.05 | 22% | 29 Mar → | ||
| 13–4 | 0.15 | 36% | 28 Mar → | ||
| 13–2 | 0.14 | 23% | 28 Mar → | ||
| 11–13 | -0.02 | 11% | 28 Mar → | ||
| 13–2 | 0.27 | 36% | 27 Mar → | ||
| 7–13 | 0.03 | 18% | 23 Mar → | ||
| 6–12 | -0.02 | 28% | 23 Mar → | ||
| 7–13 | -0.04 | 38% | 23 Mar → | ||
| 6–13 | -0.00 | 27% | 8 Mar → | ||
| 6–13 | -0.07 | 18% | 8 Mar → | ||
| 6–13 | -0.00 | 27% | 8 Mar → | ||
| 13–10 | 0.00 | 43% | 8 Mar → | ||
| 19–17 | 0.05 | 14% | 8 Mar → | ||
| 13–10 | 0.00 | 43% | 8 Mar → | ||
| 19–17 | 0.05 | 14% | 8 Mar → | ||
| 13–6 | 0.11 | 24% | 8 Mar → | ||
| 13–7 | 0.05 | 21% | 8 Mar → | ||
| 13–7 | 0.05 | 21% | 8 Mar → | ||
| 13–6 | 0.11 | 24% | 8 Mar → | ||
| 2–13 | -0.07 | 50% | 7 Mar → | ||
| 1–13 | -0.07 | 28% | 7 Mar → | ||
| 13–8 | 0.00 | 9% | 7 Mar → | ||
| 2–13 | -0.07 | 50% | 7 Mar → | ||
| 1–13 | -0.07 | 28% | 7 Mar → | ||
| 13–8 | 0.00 | 9% | 7 Mar → | ||
| 13–7 | 0.04 | 27% | 7 Mar → | ||
| 13–11 | 0.00 | 18% | 7 Mar → | ||
| 13–7 | 0.04 | 27% | 7 Mar → | ||
| 13–11 | 0.00 | 18% | 7 Mar → | ||
| 13–1 | -0.00 | 30% | 26 Feb → | ||
| 13–8 | 0.01 | 23% | 7 Feb → | ||
| 5–13 | -0.01 | 37% | 4 Feb → | ||
| 13–5 | 0.07 | 17% | 4 Feb → | ||
| 6–13 | -0.02 | 34% | 4 Feb → | ||
| 13–7 | 0.04 | 33% | 5 Jan → | ||
| 4–13 | 0.15 | 34% | 10 Dec → | ||
| 11–13 | -0.06 | 17% | 21 Nov → | ||
| 13–8 | 0.08 | 24% | 13 Nov → | ||
| 13–10 | 0.01 | 17% | 12 Nov → |
Match data via Leetify.