Fessor — CS2 Stats
PROFree AgentDenmarkRiflerSettings & gear profile →
76561198271683669[U:1:311417941]
Rating over time
Faceit ELO
- At peak — 4,095
- Reached: 4,000 ELO · 3,500 ELO · 3,000 ELO · 2,500 ELO
- 4,000 ELO first seen 2026-08-28
- 3,500 ELO 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 · -0.03 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
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 donk 96% playstyle similarity
Most alike: utility contribution, 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 89 — the mechanical foundation is a clear strength.
Areas to improve
T-side openings. Opening success drops from 58% on CT to 41% 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 7.9/10 (Strong), 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 |
|---|---|---|---|---|---|
| B | 24 | 13–11 | 54% | 0.02 | |
| A | 24 | 14–10 | 58% | 0.04 | |
| S | 13 | 10–3 | 77% | 0.04 | |
| B | 13 | 6–7 | 46% | 0.00 | |
| A | 11 | 6–5 | 55% | 0.00 | |
| S | 9 | 6–3 | 67% | 0.02 | |
| A | 5 | 3–2 | 60% | 0.00 | |
| — | 1 | 0–1 | 0% | -0.08 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (46% over 13). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWWWW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 863 | 57% | 1.32 | 19.4 |
| Ancient | 493 | 54% | 1.27 | 18.6 |
| Nuke | 263 | 67% | 1.39 | 19.3 |
| Anubis | 204 | 54% | 1.25 | 18.5 |
| Overpass | 113 | 60% | 1.40 | 19.5 |
| Inferno | 110 | 55% | 1.26 | 18.8 |
| Vertigo | 104 | 58% | 1.28 | 18.8 |
| Dust2 | 50 | 54% | 1.14 | 16.5 |
Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.
Inventory
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
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
46% win rate across 13 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 8–13 | -0.06 | 29% | 24 Aug → | ||
| 16–14 | 0.00 | 45% | 24 Aug → | ||
| 11–13 | 0.04 | 30% | 24 Aug → | ||
| 13–7 | 0.07 | 28% | 24 Aug → | ||
| 13–4 | -0.02 | 23% | 23 Aug → | ||
| 10–13 | -0.02 | 25% | 19 Aug → | ||
| 13–9 | -0.04 | 24% | 19 Aug → | ||
| 8–13 | -0.05 | 11% | 19 Aug → | ||
| 13–5 | 0.05 | 31% | 19 Aug → | ||
| 7–13 | 0.01 | 21% | 18 Aug → | ||
| 7–13 | -0.03 | 22% | 18 Aug → | ||
| 13–3 | 0.08 | 24% | 18 Aug → | ||
| 13–6 | 0.00 | 17% | 18 Aug → | ||
| 19–16 | -0.00 | 16% | 16 Aug → | ||
| 13–4 | 0.06 | 19% | 16 Aug → | ||
| 6–13 | 0.01 | 19% | 16 Aug → | ||
| 13–8 | -0.03 | 33% | 16 Aug → | ||
| 13–6 | 0.10 | 20% | 16 Aug → | ||
| 13–9 | 0.09 | 27% | 15 Aug → | ||
| 13–9 | 0.03 | 13% | 15 Aug → | ||
| 8–13 | 0.01 | 22% | 15 Aug → | ||
| 13–10 | 0.05 | 10% | 15 Aug → | ||
| 8–13 | -0.05 | 20% | 14 Aug → | ||
| 13–4 | 0.08 | 22% | 14 Aug → | ||
| 16–14 | 0.05 | 24% | 14 Aug → | ||
| 13–4 | 0.04 | 20% | 14 Aug → | ||
| 13–10 | 0.01 | 25% | 14 Aug → | ||
| 9–13 | -0.05 | 24% | 8 Aug → | ||
| 11–13 | -0.01 | 40% | 8 Aug → | ||
| 13–5 | 0.02 | 16% | 7 Aug → | ||
| 13–7 | 0.03 | 34% | 7 Aug → | ||
| 15–19 | 0.01 | 27% | 7 Aug → | ||
| 10–13 | -0.03 | 23% | 7 Aug → | ||
| 5–13 | -0.10 | 24% | 4 Aug → | ||
| 13–16 | -0.03 | 17% | 4 Aug → | ||
| 5–13 | -0.10 | 24% | 4 Aug → | ||
| 13–16 | -0.03 | 17% | 4 Aug → | ||
| 19–17 | 0.04 | 23% | 31 Jul → | ||
| 8–13 | -0.03 | 22% | 31 Jul → | ||
| 13–10 | 0.05 | 22% | 31 Jul → | ||
| 19–17 | 0.04 | 23% | 31 Jul → | ||
| 13–10 | 0.05 | 22% | 31 Jul → | ||
| 8–13 | -0.03 | 22% | 31 Jul → | ||
| 13–7 | 0.02 | 33% | 31 Jul → | ||
| 13–3 | 0.07 | 22% | 31 Jul → | ||
| 13–3 | 0.07 | 22% | 31 Jul → | ||
| 13–7 | 0.02 | 33% | 31 Jul → | ||
| 11–13 | -0.02 | 17% | 31 Jul → | ||
| 6–13 | 0.01 | 25% | 31 Jul → | ||
| 11–13 | -0.02 | 17% | 31 Jul → | ||
| 6–13 | 0.01 | 25% | 31 Jul → | ||
| 16–14 | 0.05 | 20% | 9 Jul → | ||
| 7–13 | 0.02 | 31% | 9 Jul → | ||
| 6–13 | -0.04 | 28% | 9 Jul → | ||
| 13–10 | -0.01 | 27% | 24 Jun → | ||
| 10–13 | 0.04 | 31% | 23 Jun → | ||
| 13–2 | 0.09 | 23% | 23 Jun → | ||
| 11–13 | -0.02 | 39% | 16 Jun → | ||
| 9–13 | 0.07 | 29% | 3 Jun → | ||
| 13–3 | -0.01 | 24% | 31 May → | ||
| 11–13 | -0.01 | 21% | 31 May → | ||
| 13–7 | 0.01 | 17% | 31 May → | ||
| 13–5 | 0.05 | 33% | 30 May → | ||
| 13–10 | 0.01 | 20% | 30 May → | ||
| 13–2 | 0.05 | 28% | 30 May → | ||
| 9–13 | 0.10 | 33% | 27 May → | ||
| 11–13 | 0.02 | 29% | 17 May → | ||
| 13–2 | 0.05 | 20% | 23 Apr → | ||
| 9–13 | 0.04 | 25% | 23 Apr → | ||
| 13–7 | 0.00 | 26% | 22 Apr → | ||
| 16–14 | 0.06 | 42% | 21 Apr → | ||
| 13–11 | 0.05 | 25% | 16 Apr → | ||
| 13–8 | 0.13 | 29% | 8 Apr → | ||
| 13–7 | 0.08 | 18% | 8 Apr → | ||
| 16–14 | 0.03 | 22% | 8 Apr → | ||
| 13–3 | 0.27 | 32% | 7 Apr → | ||
| 13–4 | -0.03 | 18% | 6 Apr → | ||
| 9–13 | 0.00 | 14% | 1 Apr → | ||
| 14–16 | -0.05 | 32% | 1 Apr → | ||
| 13–10 | -0.01 | 15% | 31 Mar → | ||
| 13–10 | -0.02 | 24% | 31 Mar → | ||
| 13–8 | 0.05 | 27% | 31 Mar → | ||
| 9–13 | -0.05 | 13% | 31 Mar → | ||
| 13–10 | 0.05 | 10% | 31 Mar → | ||
| 4–13 | -0.08 | 27% | 31 Mar → | ||
| 7–13 | -0.04 | 29% | 31 Mar → | ||
| 13–7 | -0.01 | 12% | 30 Mar → | ||
| 14–16 | 0.01 | 22% | 30 Mar → | ||
| 13–11 | -0.00 | 21% | 29 Mar → | ||
| 13–2 | 0.13 | 29% | 29 Mar → | ||
| 13–7 | 0.15 | 23% | 26 Mar → | ||
| 17–19 | -0.03 | 25% | 25 Mar → | ||
| 13–2 | 0.01 | 27% | 25 Mar → | ||
| 10–13 | 0.06 | 24% | 25 Mar → | ||
| 13–5 | 0.07 | 30% | 25 Mar → | ||
| 7–13 | -0.02 | 22% | 25 Mar → | ||
| 13–8 | -0.00 | 24% | 23 Mar → | ||
| 7–13 | -0.01 | 34% | 23 Mar → | ||
| 13–7 | 0.07 | 38% | 23 Mar → | ||
| 13–3 | 0.08 | 29% | 19 Mar → |
Match data via Leetify.
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