ad1ktionz — CS2 Stats
VN76561198325859548[U:1:365593820]Steam profile ↗✓ No bans
What changed since last observed
CSDB last observed this profile on 11 Nov 2026 (4 days ago). Ranks are recorded once per day this page is viewed.
No change since then. Play, then come back: the next observation lands here.
Rating over time
Faceit ELO
- At peak — 2,423
- Next: 2,500 ELO at 2,500 — 77 to go
- Reached: Level 10 · Level 9 · Level 8 · Level 7
Premier CS Rating
- 315 below peak (27,389)
- +209 over 30 days · steady
- Next: Gold band at 30,000 — 2,926 to go
- Reached: Red band · Pink band · Purple band · Blue band
Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.
How this compares with the same rank
Median values for Level 10 among CSDB-tracked players (n=31,884), 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 | Level 10 median |
|---|---|---|
| Headshot rate | 43.2% | 50.9% |
| Shot accuracy | 13.8% | 13.7% |
| Kill/death ratio | 1.20 | 1.09 |
| Match win rate | 47.6% | 48.4% |
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: −10pp win rate · −0.07 avg rating · −8.3pp headshot accuracy · −13ms reaction
Win rate −10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.
Last 5 · 10 · 20 matches
Last 5
- 3–2 · 60% win rate
- Avg rating 0.00
- Avg headshot accuracy 15%
- Avg reaction 459ms
Last 10
- 5–3–2 · 50% win rate
- Avg rating -0.01
- Avg headshot accuracy 16%
- Avg reaction 459ms
Last 20
- 11–5–4 · 55% win rate
- Avg rating 0.03
- Avg headshot accuracy 20%
- Avg reaction 465ms
Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.
Player DNA
Primary style: Opening Duellist — Winning opening duels is what stands out in this profile (+2.1 against its own average). How often you WIN the first duel — CSDB cannot yet see how often you take it.
Sharp aimerStrong positioning
Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.
What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.
Your pro match
Plays most like s1mple 85% playstyle similarity
Most alike: positioning profile, 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 91 — the mechanical foundation is a clear strength.
CT openings. 71% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
T openings. 67% 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.
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 8.4/10 (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.
Personal bests
Across the last 100 tracked matches.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
 dust2 | C | 30 | 13–17 | 43% | 0.05 |
 mirage | S | 30 | 23–7 | 77% | 0.03 |
 inferno | S | 14 | 10–4 | 71% | 0.05 |
 ancient | S | 13 | 10–3 | 77% | 0.04 |
 anubis | C | 5 | 2–3 | 40% | 0.00 |
 nuke | — | 4 | 4–0 | 100% | 0.06 |
 cache | — | 3 | 3–0 | 100% | 0.06 |
 train | — | 1 | 0–1 | 0% | -0.01 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (40% over 5). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.
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 resultsLLLWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 517 | 53% | 1.31 | 18.4 |
| Dust2 | 254 | 48% | 1.24 | 18.5 |
| Inferno | 172 | 57% | 1.33 | 17.8 |
| Ancient | 157 | 42% | 1.24 | 18.0 |
| Anubis | 79 | 53% | 1.15 | 17.1 |
| Nuke | 26 | 46% | 1.24 | 17.1 |
| Overpass | 22 | 64% | 1.36 | 17.1 |
| Cache | 16 | 50% | 1.19 | 17.9 |
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.
40% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| dust2 | 11–13 | -0.04 | 11% | 14 Nov → | |
| anubis | 13–6 | 0.07 | 11% | 13 Nov → | |
| inferno | 13–11 | -0.00 | 14% | 13 Nov → | |
| mirage | 6–13 | -0.04 | 17% | 11 Nov → | |
| dust2 | 11–1 | 0.02 | 21% | 11 Nov → | |
| mirage | 13–6 | -0.02 | 23% | 11 Nov → | |
| dust2 | 1–13 | -0.02 | 14% | 11 Nov → | |
| mirage | 13–5 | 0.02 | 21% | 8 Nov → | |
| anubis | 15–15 | 0.01 | 11% | 8 Nov → | |
| mirage | 12–12 | -0.06 | 16% | 8 Nov → | |
| dust2 | 4–10 | 0.05 | 28% | 8 Nov → | |
| dust2 | 4–13 | -0.01 | 20% | 7 Nov → | |
| mirage | 13–8 | 0.20 | 40% | 7 Nov → | |
| dust2 | 13–9 | 0.12 | 35% | 6 Nov → | |
| dust2 | 13–9 | 0.08 | 27% | 6 Nov → | |
| ancient | 13–4 | 0.07 | 15% | 6 Nov → | |
| inferno | 12–12 | 0.04 | 17% | 6 Nov → | |
| mirage | 13–6 | 0.03 | 21% | 6 Nov → | |
| mirage | 13–2 | -0.03 | 18% | 4 Nov → | |
| dust2 | 12–12 | 0.10 | 23% | 4 Nov → | |
| mirage | 2–13 | -0.06 | 17% | 4 Nov → | |
| ancient | 13–0 | 0.09 | 30% | 4 Nov → | |
| ancient | 16–13 | 0.02 | 18% | 4 Nov → | |
| cache | 13–6 | 0.07 | 20% | 4 Nov → | |
| dust2 | 13–9 | 0.11 | 25% | 3 Nov → | |
| inferno | 9–13 | 0.05 | 13% | 3 Nov → | |
| dust2 | 10–13 | 0.01 | 17% | 3 Nov → | |
| dust2 | 11–13 | 0.03 | 9% | 3 Nov → | |
| dust2 | 13–11 | 0.02 | 22% | 3 Nov → | |
| mirage | 2–7 | 0.00 | 18% | 2 Nov → | |
| dust2 | 5–13 | -0.04 | 12% | 30 Oct → | |
| inferno | 13–10 | -0.02 | 15% | 30 Oct → | |
| mirage | 13–8 | 0.07 | 19% | 30 Oct → | |
| ancient | 13–0 | 0.10 | 13% | 30 Oct → | |
| ancient | 13–8 | 0.01 | 10% | 28 Oct → | |
| mirage | 13–10 | 0.08 | 12% | 25 Oct → | |
| dust2 | 5–13 | 0.05 | 24% | 25 Oct → | |
| inferno | 11–13 | 0.04 | 19% | 25 Oct → | |
| ancient | 8–13 | -0.00 | 31% | 25 Oct → | |
| dust2 | 13–5 | 0.18 | 14% | 24 Oct → | |
| mirage | 3–13 | -0.01 | 20% | 24 Oct → | |
| inferno | 13–10 | 0.13 | 21% | 24 Oct → | |
| dust2 | 9–13 | 0.03 | 17% | 24 Oct → | |
| cache | 13–2 | 0.04 | 29% | 24 Oct → | |
| dust2 | 13–11 | 0.02 | 20% | 24 Oct → | |
| nuke | 13–9 | 0.00 | 11% | 24 Oct → | |
| inferno | 13–4 | 0.06 | 19% | 24 Oct → | |
| ancient | 13–0 | 0.10 | 17% | 24 Oct → | |
| nuke | 13–9 | 0.14 | 23% | 23 Oct → | |
| inferno | 13–8 | 0.06 | 21% | 23 Oct → | |
| dust2 | 13–4 | 0.22 | 16% | 23 Oct → | |
| dust2 | 12–12 | 0.05 | 13% | 22 Oct → | |
| inferno | 13–10 | 0.03 | 23% | 22 Oct → | |
| mirage | 13–4 | 0.05 | 36% | 22 Oct → | |
| inferno | 13–11 | 0.03 | 22% | 22 Oct → | |
| mirage | 13–8 | 0.04 | 19% | 21 Oct → | |
| ancient | 9–13 | 0.04 | 19% | 21 Oct → | |
| mirage | 13–10 | -0.02 | 16% | 19 Oct → | |
| anubis | 2–13 | -0.04 | 13% | 19 Oct → | |
| dust2 | 13–4 | 0.10 | 16% | 19 Oct → | |
| ancient | 16–14 | 0.05 | 16% | 19 Oct → | |
| dust2 | 8–13 | 0.09 | 6% | 18 Oct → | |
| mirage | 13–7 | 0.14 | 19% | 17 Oct → | |
| dust2 | 13–5 | 0.10 | 21% | 17 Oct → | |
| mirage | 13–4 | 0.11 | 32% | 17 Oct → | |
| mirage | 8–13 | 0.10 | 23% | 17 Oct → | |
| dust2 | 6–13 | 0.03 | 16% | 17 Oct → | |
| dust2 | 13–9 | 0.08 | 8% | 13 Oct → | |
| ancient | 13–2 | 0.14 | 19% | 13 Oct → | |
| ancient | 13–11 | 0.03 | 12% | 13 Oct → | |
| anubis | 13–9 | 0.06 | 12% | 13 Oct → | |
| nuke | 13–9 | -0.02 | 8% | 13 Oct → | |
| mirage | 7–13 | -0.02 | 23% | 13 Oct → | |
| dust2 | 14–16 | -0.08 | 9% | 27 Sept → | |
| anubis | 0–13 | -0.11 | 17% | 26 Sept → | |
| inferno | 13–8 | 0.10 | 29% | 11 Sept → | |
| inferno | 9–13 | 0.12 | 20% | 11 Sept → | |
| train | 2–13 | -0.01 | 17% | 11 Sept → | |
| cache | 13–11 | 0.05 | 18% | 31 Aug → | |
| mirage | 13–2 | -0.01 | 33% | 31 Aug → | |
| mirage | 13–8 | 0.11 | 21% | 30 Aug → | |
| dust2 | 12–16 | 0.02 | 14% | 30 Aug → | |
| mirage | 13–3 | 0.06 | 20% | 30 Aug → | |
| inferno | 13–11 | 0.05 | 19% | 19 Aug → | |
| dust2 | 13–7 | 0.07 | 21% | 12 Aug → | |
| mirage | 13–7 | 0.08 | 22% | 12 Aug → | |
| nuke | 13–7 | 0.11 | 23% | 2 Aug → | |
| mirage | 13–11 | 0.01 | 17% | 31 Jul → | |
| dust2 | 6–13 | -0.01 | 31% | 29 Jul → | |
| dust2 | 7–13 | -0.02 | 15% | 22 Jul → | |
| mirage | 13–4 | 0.11 | 26% | 16 Jul → | |
| mirage | 13–10 | 0.03 | 17% | 12 Jul → | |
| ancient | 13–4 | 0.01 | 10% | 12 Jul → | |
| inferno | 13–6 | 0.09 | 14% | 9 Jul → | |
| mirage | 13–8 | -0.00 | 13% | 9 Jul → | |
| mirage | 13–6 | 0.06 | 16% | 9 Jul → | |
| mirage | 13–7 | 0.03 | 9% | 5 Jul → | |
| ancient | 0–13 | -0.09 | 9% | 29 Jun → | |
| mirage | 13–6 | -0.04 | 20% | 29 Jun → | |
| dust2 | 13–9 | 0.01 | 21% | 28 Jun → |
Match data via Leetify.
Recent teammates
Milestones
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