AquaRS — CS2 Stats
76561198800147622[U:1:839881894]
Rating over time
Faceit ELO
- At peak — 3,956
- Next: 4,000 ELO at 4,000 — 44 to go
- Reached: 3,500 ELO · 3,000 ELO · 2,500 ELO · Level 10
- 3,500 ELO first seen 2026-08-28
- 3,000 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: -20pp win rate · -0.01 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
Sharp aimerExcellent counter-strafingStrong 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 Twistzz 94% playstyle similarity
Most alike: aim profile, positioning 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 94 — the mechanical foundation is a clear strength.
Areas to improve
Preaim. Mechanical aim is strong but the crosshair sits 10.3° off target when enemies appear — placement, not flicking, is the bigger win available.
Positioning. Positioning trails aim by 35 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.
T-side openings. Opening success drops from 55% on CT to 30% 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 7.8/10 (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 | 23 | 11–12 | 48% | 0.00 | |
| S | 19 | 13–6 | 68% | 0.00 | |
| S | 18 | 14–4 | 78% | 0.01 | |
| S | 15 | 10–5 | 67% | -0.00 | |
| S | 11 | 8–3 | 73% | 0.03 | |
| A | 8 | 5–3 | 63% | 0.01 | |
| S | 6 | 5–1 | 83% | 0.01 |
Across the last 100 tracked matches.
Dust 2 is currently your weakest sufficiently-sampled map (48% over 23). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsLLWWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 796 | 59% | 1.32 | 18.4 |
| Dust2 | 425 | 58% | 1.37 | 17.7 |
| Ancient | 383 | 53% | 1.27 | 17.8 |
| Anubis | 313 | 55% | 1.33 | 17.8 |
| Nuke | 187 | 52% | 1.30 | 18.1 |
| Train | 94 | 66% | 1.37 | 18.8 |
| Vertigo | 69 | 54% | 1.28 | 18.0 |
| Overpass | 64 | 64% | 1.36 | 18.8 |
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 0.4609 — 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 29.5978% — 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.
48% win rate across 23 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–4 | -0.01 | 23% | 9 Aug → | ||
| 3–13 | -0.01 | 36% | 9 Aug → | ||
| 11–13 | -0.00 | 22% | 9 Aug → | ||
| 13–11 | 0.02 | 30% | 8 Aug → | ||
| 13–11 | 0.06 | 27% | 8 Aug → | ||
| 13–11 | -0.05 | 17% | 7 Aug → | ||
| 13–8 | 0.05 | 29% | 7 Aug → | ||
| 10–13 | -0.01 | 20% | 30 Jul → | ||
| 13–6 | 0.05 | 27% | 30 Jul → | ||
| 9–13 | -0.04 | 15% | 30 Jul → | ||
| 7–13 | -0.06 | 16% | 30 Jul → | ||
| 13–7 | 0.07 | 21% | 30 Jul → | ||
| 13–7 | 0.02 | 39% | 30 Jul → | ||
| 8–13 | -0.01 | 18% | 30 Jul → | ||
| 13–10 | 0.03 | 21% | 30 Jul → | ||
| 13–4 | 0.00 | 25% | 29 Jul → | ||
| 13–7 | 0.03 | 30% | 29 Jul → | ||
| 13–8 | 0.04 | 21% | 29 Jul → | ||
| 16–12 | 0.02 | 30% | 27 Jul → | ||
| 13–3 | 0.06 | 27% | 27 Jul → | ||
| 13–16 | -0.09 | 23% | 27 Jul → | ||
| 13–1 | 0.03 | 22% | 27 Jul → | ||
| 13–0 | 0.10 | 41% | 27 Jul → | ||
| 9–13 | -0.04 | 30% | 11 Jul → | ||
| 13–11 | 0.02 | 32% | 10 Jul → | ||
| 13–10 | 0.01 | 39% | 10 Jul → | ||
| 7–13 | -0.05 | 23% | 10 Jul → | ||
| 19–15 | 0.04 | 34% | 9 Jul → | ||
| 13–11 | 0.04 | 26% | 9 Jul → | ||
| 3–13 | -0.02 | 18% | 9 Jul → | ||
| 13–8 | 0.14 | 32% | 29 Jun → | ||
| 13–10 | 0.12 | 32% | 26 Jun → | ||
| 13–8 | 0.02 | 38% | 26 Jun → | ||
| 14–16 | -0.06 | 16% | 21 Jun → | ||
| 5–13 | -0.05 | 25% | 21 Jun → | ||
| 8–13 | 0.03 | 28% | 20 Jun → | ||
| 13–3 | 0.22 | 27% | 20 Jun → | ||
| 13–3 | 0.14 | 45% | 20 Jun → | ||
| 13–4 | 0.04 | 34% | 20 Jun → | ||
| 9–13 | 0.02 | 26% | 20 Jun → | ||
| 13–7 | -0.02 | 37% | 20 Jun → | ||
| 13–10 | 0.00 | 22% | 20 Jun → | ||
| 19–17 | 0.02 | 27% | 19 Jun → | ||
| 10–13 | -0.05 | 17% | 19 Jun → | ||
| 13–9 | -0.05 | 20% | 19 Jun → | ||
| 13–5 | 0.04 | 20% | 17 Jun → | ||
| 11–13 | -0.03 | 32% | 17 Jun → | ||
| 13–11 | 0.02 | 30% | 17 Jun → | ||
| 10–13 | 0.00 | 29% | 16 Jun → | ||
| 13–3 | 0.04 | 42% | 15 Jun → | ||
| 13–4 | -0.00 | 38% | 15 Jun → | ||
| 13–8 | 0.05 | 45% | 14 Jun → | ||
| 5–13 | -0.01 | 25% | 14 Jun → | ||
| 4–13 | -0.08 | 8% | 14 Jun → | ||
| 10–13 | -0.02 | 25% | 14 Jun → | ||
| 13–7 | 0.03 | 22% | 12 Jun → | ||
| 13–7 | -0.01 | 21% | 12 Jun → | ||
| 4–13 | -0.03 | 42% | 12 Jun → | ||
| 9–13 | 0.02 | 23% | 11 Jun → | ||
| 8–13 | -0.07 | 27% | 11 Jun → | ||
| 13–11 | -0.03 | 29% | 9 Jun → | ||
| 16–13 | -0.00 | 23% | 9 Jun → | ||
| 11–13 | -0.05 | 30% | 7 Jun → | ||
| 13–11 | -0.01 | 14% | 7 Jun → | ||
| 10–13 | -0.02 | 14% | 28 May → | ||
| 22–20 | -0.04 | 21% | 28 May → | ||
| 13–7 | 0.03 | 24% | 28 May → | ||
| 13–8 | -0.02 | 33% | 28 May → | ||
| 16–12 | -0.06 | 17% | 27 May → | ||
| 13–6 | 0.04 | 42% | 27 May → | ||
| 13–5 | 0.02 | 32% | 26 May → | ||
| 13–9 | 0.03 | 27% | 26 May → | ||
| 13–9 | 0.09 | 33% | 26 May → | ||
| 13–9 | 0.01 | 28% | 1 May → | ||
| 13–3 | 0.02 | 45% | 29 Apr → | ||
| 13–8 | 0.07 | 21% | 13 Apr → | ||
| 13–10 | 0.07 | 34% | 28 Mar → | ||
| 13–11 | 0.07 | 29% | 23 Mar → | ||
| 13–7 | 0.01 | 36% | 23 Mar → | ||
| 10–13 | -0.04 | 37% | 18 Mar → | ||
| 6–13 | -0.01 | 23% | 11 Mar → | ||
| 7–13 | -0.01 | 23% | 11 Mar → | ||
| 22–20 | -0.05 | 24% | 9 Mar → | ||
| 13–8 | -0.01 | 29% | 9 Mar → | ||
| 19–17 | -0.01 | 25% | 9 Mar → | ||
| 13–11 | -0.02 | 25% | 9 Mar → | ||
| 9–13 | -0.02 | 26% | 6 Mar → | ||
| 9–13 | -0.03 | 20% | 6 Mar → | ||
| 13–7 | 0.01 | 30% | 6 Mar → | ||
| 13–11 | -0.00 | 31% | 6 Mar → | ||
| 13–5 | 0.03 | 37% | 6 Mar → | ||
| 8–13 | -0.03 | 24% | 6 Mar → | ||
| 13–8 | 0.02 | 33% | 6 Mar → | ||
| 10–13 | 0.01 | 25% | 6 Mar → | ||
| 13–9 | -0.01 | 22% | 5 Mar → | ||
| 11–13 | -0.02 | 24% | 5 Mar → | ||
| 19–17 | -0.02 | 32% | 5 Mar → | ||
| 13–9 | 0.01 | 43% | 4 Mar → | ||
| 16–14 | 0.01 | 22% | 4 Mar → | ||
| 10–13 | 0.00 | 30% | 4 Mar → |
Match data via Leetify.