Abal0ney — CS2 Stats
76561198397451663[U:1:437185935]Steam profile ↗✓ No bans
Rating over time
Faceit ELO
- At peak — 1,756
- Next: Level 10 at 2,001 — 245 to go
- Reached: Level 9 · Level 8 · Level 7 · Level 6
- Level 9 first seen 2026-08-28
- Level 8 first seen 2026-08-28
Premier CS Rating
- At peak — 19,828
- Next: Pink band at 20,000 — 172 to go
- Reached: Purple band · Blue band · Light Blue band
- Purple band first seen 2026-08-28
- Blue band first seen 2026-08-28
CSDB's own observations — this history builds from the day a profile is first viewed and cannot be backfilled.
How this compares with the same rank
Median values for Purple band among CSDB-tracked players (n=2,789), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.
| Metric | This player | Purple band median | Pink band median | vs Pink band |
|---|---|---|---|---|
| Headshot rate | 45.9% | 44.1% | 47.2% | 1.3% short |
| Shot accuracy | 3.0% | 11.4% | 12.7% | 9.7% short |
| Kill/death ratio | 0.94 | 1.03 | 1.09 | 0.14 short |
| Match win rate | 50.7% | 45.2% | 46.6% | above |
This profile matches the typical Pink band player on 1 of 4 comparable metrics.
Widest gap: Shot accuracy. That is the metric furthest from the Pink band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +0pp win rate · -0.01 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 jL 93% playstyle similarity
Most alike: opening-duel success, utility contribution.
Where you differ: 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
Reaction time. 596ms 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 7.0/10 (Strong), 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 |
|---|---|---|---|---|---|
| A | 34 | 21–13 | 62% | 0.01 | |
| C | 21 | 9–12 | 43% | 0.01 | |
| C | 16 | 7–9 | 44% | 0.02 | |
| B | 14 | 7–7 | 50% | -0.01 | |
| D | 5 | 1–4 | 20% | -0.02 | |
| — | 4 | 2–2 | 50% | -0.01 | |
| — | 2 | 2–0 | 100% | -0.00 | |
| — | 2 | 1–1 | 50% | -0.00 | |
| shelter | — | 1 | 0–1 | 0% | -0.01 |
| — | 1 | 1–0 | 100% | 0.04 |
Across the last 100 tracked matches.
Lifetime stats
Most-used weapons
Lifetime map wins
Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsLWWWW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 53 | 55% | 1.12 | 14.9 |
| Dust2 | 36 | 64% | 1.17 | 15.1 |
| Ancient | 27 | 81% | 1.46 | 18.8 |
| Inferno | 25 | 56% | 1.39 | 18.1 |
| Anubis | 24 | 54% | 1.25 | 19.2 |
| Nuke | 11 | 73% | 1.36 | 18.6 |
| Vertigo | 4 | 50% | 2.60 | 18.5 |
| Train | 3 | 67% | 0.81 | 15.3 |
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
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 | |
|---|---|---|---|---|---|
| 12–12 | -0.01 | 9% | 27 Aug → | ||
| 6–13 | -0.06 | 25% | 27 Aug → | ||
| 16–14 | -0.03 | 13% | 26 Aug → | ||
| 13–10 | -0.00 | 19% | 25 Aug → | ||
| 15–15 | 0.01 | 20% | 22 Aug → | ||
| 6–13 | -0.04 | 15% | 22 Aug → | ||
| 13–4 | 0.08 | 15% | 22 Aug → | ||
| 13–3 | -0.00 | 27% | 21 Aug → | ||
| 13–3 | 0.12 | 21% | 21 Aug → | ||
| 8–13 | 0.03 | 13% | 21 Aug → | ||
| 16–13 | 0.02 | 18% | 20 Aug → | ||
| 13–7 | -0.00 | 12% | 19 Aug → | ||
| 12–16 | 0.02 | 29% | 19 Aug → | ||
| 15–15 | 0.10 | 17% | 19 Aug → | ||
| 13–9 | 0.03 | 15% | 18 Aug → | ||
| 10–13 | -0.00 | 25% | 16 Aug → | ||
| 13–6 | 0.01 | 24% | 15 Aug → | ||
| 2–13 | -0.08 | 19% | 15 Aug → | ||
| 13–1 | 0.09 | 15% | 15 Aug → | ||
| 2–13 | 0.00 | 21% | 14 Aug → | ||
| 13–6 | 0.05 | 20% | 13 Aug → | ||
| 13–5 | 0.05 | 12% | 13 Aug → | ||
| 13–8 | -0.02 | 16% | 11 Aug → | ||
| 13–7 | 0.07 | 12% | 11 Aug → | ||
| 13–6 | 0.03 | 16% | 10 Aug → | ||
| 13–6 | 0.07 | 9% | 10 Aug → | ||
| 13–11 | -0.02 | 21% | 10 Aug → | ||
| 11–13 | -0.06 | 16% | 9 Aug → | ||
| 7–13 | -0.02 | 11% | 9 Aug → | ||
| 4–13 | -0.05 | 11% | 9 Aug → | ||
| 15–15 | 0.06 | 12% | 9 Aug → | ||
| 13–5 | 0.00 | 19% | 9 Aug → | ||
| 10–13 | 0.01 | 22% | 9 Aug → | ||
| 13–11 | 0.00 | 12% | 9 Aug → | ||
| 9–13 | -0.02 | 18% | 8 Aug → | ||
| 3–13 | -0.07 | 13% | 8 Aug → | ||
| 13–6 | 0.06 | 9% | 8 Aug → | ||
| 10–13 | 0.01 | 11% | 8 Aug → | ||
| 15–15 | 0.01 | 11% | 8 Aug → | ||
| 8–13 | 0.05 | 17% | 8 Aug → | ||
| 13–5 | -0.02 | 13% | 8 Aug → | ||
| 5–13 | 0.03 | 10% | 8 Aug → | ||
| shelter | 9–13 | -0.01 | 16% | 7 Aug → | |
| 8–13 | -0.06 | 9% | 7 Aug → | ||
| 12–12 | 0.03 | 14% | 7 Aug → | ||
| 13–11 | -0.03 | 12% | 7 Aug → | ||
| 8–13 | -0.03 | 16% | 7 Aug → | ||
| 13–11 | 0.05 | 14% | 7 Aug → | ||
| 13–9 | 0.02 | 14% | 7 Aug → | ||
| 3–13 | -0.06 | 20% | 3 Aug → | ||
| 13–2 | -0.01 | 8% | 29 Jul → | ||
| 9–13 | 0.05 | 19% | 29 Jul → | ||
| 13–5 | 0.01 | 11% | 29 Jul → | ||
| 13–10 | -0.04 | 21% | 28 Jul → | ||
| 13–10 | 0.05 | 22% | 23 Jul → | ||
| 13–5 | -0.00 | 12% | 23 Jul → | ||
| 13–3 | 0.08 | 20% | 14 Jul → | ||
| 13–4 | 0.04 | 7% | 10 Jul → | ||
| 7–13 | -0.04 | 16% | 9 Jul → | ||
| 13–3 | 0.07 | 21% | 9 Jul → | ||
| 13–11 | -0.06 | 18% | 3 Jul → | ||
| 9–13 | -0.04 | 14% | 2 Jul → | ||
| 8–13 | -0.00 | 16% | 30 Jun → | ||
| 1–13 | -0.10 | 17% | 29 Jun → | ||
| 13–8 | 0.00 | 20% | 29 Jun → | ||
| 13–1 | -0.04 | 10% | 29 Jun → | ||
| 13–9 | 0.01 | 21% | 19 Jun → | ||
| 6–13 | -0.04 | 15% | 19 Jun → | ||
| 13–5 | 0.03 | 21% | 19 Jun → | ||
| 6–13 | -0.06 | 21% | 18 Jun → | ||
| 7–13 | -0.05 | 13% | 15 Jun → | ||
| 1–13 | -0.03 | 24% | 15 Jun → | ||
| 1–13 | 0.01 | 23% | 15 Jun → | ||
| 13–11 | -0.10 | 12% | 14 Jun → | ||
| 12–12 | 0.02 | 15% | 13 Jun → | ||
| 12–12 | -0.00 | 30% | 11 Jun → | ||
| 13–10 | 0.08 | 14% | 7 Jun → | ||
| 13–7 | 0.05 | 22% | 7 Jun → | ||
| 10–13 | 0.00 | 11% | 4 Jun → | ||
| 13–9 | -0.02 | 6% | 29 May → | ||
| 1–5 | 0.07 | 60% | 29 May → | ||
| 13–8 | 0.04 | 11% | 29 May → | ||
| 12–12 | -0.07 | 14% | 29 May → | ||
| 13–5 | 0.03 | 14% | 14 May → | ||
| 8–13 | -0.06 | 9% | 14 May → | ||
| 13–11 | -0.00 | 13% | 7 May → | ||
| 11–13 | 0.04 | 13% | 7 May → | ||
| 13–3 | 0.02 | 18% | 6 May → | ||
| 10–13 | 0.03 | 4% | 5 May → | ||
| 10–13 | 0.01 | 11% | 5 May → | ||
| 6–13 | -0.07 | 11% | 5 May → | ||
| 13–10 | 0.00 | 11% | 5 May → | ||
| 13–11 | 0.05 | 20% | 3 May → | ||
| 13–11 | -0.05 | 3% | 2 May → | ||
| 14–16 | -0.03 | 12% | 23 Apr → | ||
| 0–6 | -0.15 | 0% | 22 Apr → | ||
| 6–13 | 0.04 | 24% | 22 Apr → | ||
| 13–0 | 0.11 | 31% | 22 Apr → | ||
| 13–3 | 0.07 | 16% | 22 Apr → | ||
| 13–10 | 0.04 | 21% | 22 Apr → |
Match data via Leetify.