iPlxel — CS2 Stats
76561198883349445[U:1:923083717]✓ No bans
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +30pp win rate · -0.01 avg rating
Player DNA
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 NiKo 72% playstyle similarity
Most alike: positioning profile, opening-duel success.
Where you differ: lower opening-fight frequency; 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. 604ms 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 4.7/10 (Developing), 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 |
|---|---|---|---|---|---|
| C | 20 | 7–13 | 35% | 0.01 | |
| A | 19 | 11–8 | 58% | -0.01 | |
| S | 16 | 12–4 | 75% | -0.01 | |
| A | 12 | 7–5 | 58% | -0.01 | |
| B | 11 | 5–6 | 45% | -0.01 | |
| S | 10 | 9–1 | 90% | 0.01 | |
| D | 9 | 3–6 | 33% | -0.04 | |
| — | 1 | 1–0 | 100% | 0.00 | |
| office | — | 1 | 0–1 | 0% | -0.04 |
| — | 1 | 1–0 | 100% | 0.06 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (33% over 9). 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 resultsWLWWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Inferno | 4 | 50% | 0.78 | 13.5 |
| Dust2 | 4 | 50% | 1.06 | 14.5 |
| Cache | 4 | 25% | 0.56 | 11.3 |
| Mirage | 4 | 50% | 1.01 | 13.3 |
| Vertigo | 2 | 100% | 1.48 | 17.5 |
| Anubis | 2 | 50% | 1.47 | 25.0 |
| Ancient | 2 | 0% | 0.62 | 9.5 |
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.
- Advanced MechanicsAim Training →
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 13.689° — above the 12° mark we flag
- 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 0.3844 — below the 0.5 mark we flag
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
33% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 15–15 | -0.06 | 27% | 28 Aug → | ||
| 13–7 | -0.03 | 25% | 28 Aug → | ||
| 13–8 | -0.04 | 25% | 28 Aug → | ||
| 13–7 | -0.02 | 28% | 28 Aug → | ||
| 13–9 | -0.05 | 23% | 28 Aug → | ||
| 13–10 | -0.06 | 15% | 28 Aug → | ||
| 10–13 | -0.03 | 23% | 27 Aug → | ||
| 13–9 | 0.01 | 17% | 25 Aug → | ||
| 13–4 | -0.05 | 41% | 25 Aug → | ||
| 5–13 | -0.06 | 24% | 25 Aug → | ||
| 13–7 | 0.04 | 22% | 25 Aug → | ||
| 1–13 | -0.03 | 19% | 25 Aug → | ||
| 16–13 | -0.02 | 18% | 24 Aug → | ||
| 9–13 | -0.01 | 24% | 24 Aug → | ||
| 9–13 | -0.04 | 12% | 24 Aug → | ||
| 13–7 | -0.01 | 19% | 23 Aug → | ||
| 8–13 | -0.06 | 17% | 23 Aug → | ||
| 9–13 | -0.02 | 28% | 23 Aug → | ||
| 5–13 | -0.05 | 11% | 23 Aug → | ||
| 13–4 | -0.07 | 18% | 22 Aug → | ||
| 13–6 | 0.01 | 23% | 22 Aug → | ||
| 13–8 | -0.05 | 21% | 21 Aug → | ||
| 13–3 | 0.05 | 32% | 21 Aug → | ||
| 13–9 | -0.04 | 20% | 21 Aug → | ||
| 15–15 | -0.05 | 19% | 21 Aug → | ||
| 10–13 | -0.00 | 20% | 20 Aug → | ||
| 4–13 | -0.05 | 21% | 20 Aug → | ||
| 13–11 | -0.05 | 27% | 20 Aug → | ||
| 2–13 | -0.02 | 24% | 20 Aug → | ||
| 13–5 | -0.00 | 39% | 19 Aug → | ||
| 9–13 | 0.03 | 33% | 19 Aug → | ||
| 8–13 | -0.12 | 19% | 19 Aug → | ||
| 13–10 | -0.05 | 24% | 19 Aug → | ||
| 7–13 | -0.02 | 26% | 19 Aug → | ||
| 13–11 | 0.01 | 29% | 19 Aug → | ||
| 10–13 | -0.11 | 16% | 12 Aug → | ||
| 12–5 | 0.08 | 33% | 12 Aug → | ||
| 13–11 | 0.02 | 21% | 12 Aug → | ||
| 8–13 | -0.06 | 15% | 9 Aug → | ||
| 15–15 | -0.08 | 12% | 8 Aug → | ||
| 13–4 | 0.00 | 12% | 6 Aug → | ||
| 6–13 | -0.10 | 12% | 6 Aug → | ||
| 13–11 | -0.05 | 21% | 6 Aug → | ||
| 13–2 | -0.03 | 30% | 5 Aug → | ||
| 3–13 | -0.06 | 10% | 5 Aug → | ||
| 13–5 | 0.02 | 27% | 5 Aug → | ||
| 9–13 | -0.04 | 14% | 5 Aug → | ||
| 14–16 | -0.07 | 19% | 5 Aug → | ||
| 0–13 | -0.04 | 43% | 3 Aug → | ||
| 13–2 | 0.05 | 15% | 2 Aug → | ||
| 13–3 | -0.02 | 20% | 2 Aug → | ||
| 13–9 | -0.04 | 26% | 1 Aug → | ||
| 6–13 | -0.04 | 28% | 1 Aug → | ||
| 13–6 | 0.00 | 27% | 29 Jul → | ||
| 0–13 | -0.04 | 9% | 29 Jul → | ||
| 13–5 | -0.00 | 21% | 29 Jul → | ||
| 4–13 | -0.08 | 16% | 29 Jul → | ||
| 13–9 | 0.01 | 18% | 28 Jul → | ||
| 13–11 | -0.01 | 22% | 21 Jul → | ||
| 15–15 | -0.02 | 15% | 21 Jul → | ||
| 4–13 | 0.03 | 20% | 17 Jul → | ||
| 13–16 | -0.06 | 24% | 17 Jul → | ||
| 1–13 | -0.09 | 32% | 16 Jul → | ||
| 13–8 | -0.01 | 30% | 16 Jul → | ||
| 3–13 | -0.09 | 23% | 15 Jul → | ||
| 7–13 | -0.02 | 33% | 15 Jul → | ||
| 14–16 | 0.05 | 14% | 15 Jul → | ||
| 13–4 | -0.00 | 24% | 15 Jul → | ||
| 13–2 | 0.03 | 23% | 14 Jul → | ||
| 13–4 | 0.07 | 19% | 14 Jul → | ||
| 9–13 | 0.08 | 27% | 14 Jul → | ||
| 13–8 | 0.03 | 28% | 14 Jul → | ||
| 13–10 | 0.03 | 29% | 13 Jul → | ||
| 13–5 | -0.00 | 24% | 12 Jul → | ||
| 15–15 | 0.04 | 26% | 11 Jul → | ||
| 15–15 | 0.03 | 22% | 11 Jul → | ||
| 13–10 | 0.06 | 20% | 11 Jul → | ||
| 13–7 | 0.04 | 26% | 10 Jul → | ||
| 13–9 | 0.01 | 30% | 10 Jul → | ||
| 13–6 | 0.00 | 21% | 10 Jul → | ||
| 13–11 | 0.01 | 19% | 10 Jul → | ||
| 13–8 | 0.04 | 27% | 10 Jul → | ||
| 13–10 | 0.10 | 34% | 9 Jul → | ||
| 13–7 | 0.04 | 21% | 9 Jul → | ||
| 13–4 | 0.17 | 15% | 9 Jul → | ||
| 13–3 | 0.06 | 24% | 8 Jul → | ||
| 12–12 | 0.04 | 21% | 8 Jul → | ||
| 13–2 | 0.05 | 20% | 8 Jul → | ||
| 7–13 | 0.07 | 26% | 8 Jul → | ||
| 13–2 | 0.14 | 27% | 7 Jul → | ||
| 3–13 | -0.07 | 36% | 7 Jul → | ||
| 5–13 | 0.05 | 33% | 7 Jul → | ||
| office | 12–12 | -0.04 | 24% | 7 Jul → | |
| 13–6 | 0.11 | 34% | 7 Jul → | ||
| 13–4 | 0.06 | 12% | 6 Jul → | ||
| 11–13 | 0.03 | 22% | 6 Jul → | ||
| 13–4 | 0.01 | 16% | 6 Jul → | ||
| 13–4 | 0.07 | 19% | 6 Jul → | ||
| 12–16 | 0.00 | 32% | 6 Jul → | ||
| 13–3 | -0.04 | 18% | 4 Jul → |
Match data via Leetify.