package_json — CS2 Stats
76561198818712114[U:1:858446386]✓ No bans
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -40pp win rate · -0.04 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 74% playstyle similarity
Most alike: opening-fight frequency, opening-duel success.
Where you differ: lower utility contribution; 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. 618ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.
Counter-strafing. Only 51% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.
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 2.3/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 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 | 12–11 | 52% | -0.03 | |
| C | 23 | 9–14 | 39% | -0.03 | |
| C | 20 | 8–12 | 40% | -0.03 | |
| C | 10 | 4–6 | 40% | -0.04 | |
| D | 9 | 3–6 | 33% | -0.05 | |
| D | 5 | 1–4 | 20% | -0.06 | |
| — | 4 | 2–2 | 50% | -0.03 | |
| — | 3 | 1–2 | 33% | -0.04 | |
| — | 3 | 1–2 | 33% | -0.05 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (20% 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 resultsWLWLW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Inferno | 18 | 33% | 0.88 | 11.1 |
| Dust2 | 14 | 50% | 0.68 | 11.2 |
| Mirage | 10 | 50% | 0.69 | 11.0 |
| Ancient | 8 | 50% | 0.67 | 12.6 |
| Nuke | 6 | 33% | 0.60 | 10.8 |
| Cache | 3 | 0% | 0.61 | 5.3 |
| Train | 1 | 0% | 0.39 | 11.0 |
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 14.1211° — above the 12° mark we flag
- Best CS2 CrosshairAim Training →
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 8.7263% — below the 15% 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 0.4198 — 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.
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 | |
|---|---|---|---|---|---|
| 8–13 | -0.01 | 12% | 26 Aug → | ||
| 1–13 | -0.04 | 0% | 23 Aug → | ||
| 6–13 | -0.10 | 2% | 23 Aug → | ||
| 16–13 | -0.04 | 10% | 23 Aug → | ||
| 11–13 | -0.08 | 5% | 23 Aug → | ||
| 2–13 | -0.07 | 28% | 22 Aug → | ||
| 13–9 | -0.02 | 14% | 22 Aug → | ||
| 5–13 | -0.14 | 0% | 22 Aug → | ||
| 4–13 | -0.06 | 13% | 22 Aug → | ||
| 11–13 | -0.06 | 13% | 22 Aug → | ||
| 7–13 | -0.08 | 2% | 22 Aug → | ||
| 15–15 | -0.02 | 4% | 22 Aug → | ||
| 4–13 | -0.09 | 0% | 21 Aug → | ||
| 16–14 | -0.04 | 11% | 18 Aug → | ||
| 10–13 | -0.02 | 5% | 18 Aug → | ||
| 13–0 | 0.05 | 8% | 18 Aug → | ||
| 13–8 | -0.05 | 8% | 18 Aug → | ||
| 13–1 | 0.01 | 4% | 18 Aug → | ||
| 13–6 | 0.02 | 6% | 18 Aug → | ||
| 13–11 | -0.00 | 8% | 18 Aug → | ||
| 13–2 | -0.01 | 11% | 17 Aug → | ||
| 13–4 | -0.01 | 8% | 17 Aug → | ||
| 15–15 | -0.03 | 11% | 16 Aug → | ||
| 9–13 | -0.02 | 16% | 16 Aug → | ||
| 9–13 | -0.02 | 11% | 16 Aug → | ||
| 13–11 | -0.06 | 11% | 16 Aug → | ||
| 7–13 | -0.04 | 11% | 16 Aug → | ||
| 6–13 | -0.01 | 10% | 15 Aug → | ||
| 13–11 | -0.09 | 10% | 14 Aug → | ||
| 13–6 | 0.00 | 10% | 14 Aug → | ||
| 13–5 | -0.01 | 23% | 13 Aug → | ||
| 13–8 | -0.01 | 15% | 12 Aug → | ||
| 15–15 | 0.04 | 16% | 12 Aug → | ||
| 7–13 | -0.03 | 7% | 12 Aug → | ||
| 3–13 | -0.04 | 4% | 11 Aug → | ||
| 13–8 | 0.06 | 10% | 11 Aug → | ||
| 8–13 | -0.06 | 8% | 9 Aug → | ||
| 9–13 | -0.07 | 7% | 9 Aug → | ||
| 11–13 | -0.06 | 7% | 8 Aug → | ||
| 9–13 | -0.05 | 7% | 8 Aug → | ||
| 1–13 | -0.11 | 5% | 8 Aug → | ||
| 13–10 | -0.06 | 9% | 7 Aug → | ||
| 8–13 | -0.03 | 6% | 7 Aug → | ||
| 13–10 | 0.03 | 7% | 7 Aug → | ||
| 13–5 | -0.04 | 15% | 7 Aug → | ||
| 8–13 | -0.05 | 15% | 7 Aug → | ||
| 13–6 | 0.05 | 8% | 7 Aug → | ||
| 13–11 | -0.00 | 9% | 6 Aug → | ||
| 6–13 | -0.04 | 7% | 6 Aug → | ||
| 5–13 | -0.01 | 8% | 6 Aug → | ||
| 10–13 | 0.01 | 4% | 5 Aug → | ||
| 13–8 | 0.06 | 13% | 5 Aug → | ||
| 8–13 | -0.03 | 7% | 5 Aug → | ||
| 13–10 | -0.05 | 0% | 5 Aug → | ||
| 13–6 | -0.02 | 23% | 5 Aug → | ||
| 13–4 | -0.01 | 3% | 5 Aug → | ||
| 13–5 | -0.01 | 6% | 5 Aug → | ||
| 7–13 | -0.05 | 14% | 5 Aug → | ||
| 13–11 | -0.01 | 4% | 4 Aug → | ||
| 6–13 | -0.12 | 0% | 3 Aug → | ||
| 10–13 | -0.04 | 6% | 3 Aug → | ||
| 10–6 | -0.07 | 3% | 3 Aug → | ||
| 0–13 | -0.10 | 4% | 3 Aug → | ||
| 0–13 | -0.14 | 13% | 3 Aug → | ||
| 10–13 | 0.00 | 14% | 3 Aug → | ||
| 12–12 | -0.06 | 8% | 2 Aug → | ||
| 13–6 | -0.06 | 10% | 2 Aug → | ||
| 5–13 | -0.06 | 11% | 2 Aug → | ||
| 4–13 | 0.03 | 7% | 1 Aug → | ||
| 13–4 | -0.01 | 5% | 1 Aug → | ||
| 13–3 | 0.02 | 5% | 1 Aug → | ||
| 10–13 | -0.07 | 7% | 1 Aug → | ||
| 12–12 | -0.02 | 15% | 1 Aug → | ||
| 11–13 | 0.00 | 6% | 1 Aug → | ||
| 13–4 | -0.05 | 5% | 31 Jul → | ||
| 13–7 | -0.04 | 7% | 30 Jul → | ||
| 13–7 | -0.02 | 4% | 30 Jul → | ||
| 12–16 | -0.09 | 6% | 30 Jul → | ||
| 13–11 | -0.02 | 11% | 30 Jul → | ||
| 9–13 | -0.03 | 18% | 29 Jul → | ||
| 11–13 | -0.07 | 6% | 27 Jul → | ||
| 13–10 | -0.09 | 7% | 27 Jul → | ||
| 13–4 | -0.04 | 3% | 27 Jul → | ||
| 5–13 | -0.03 | 5% | 27 Jul → | ||
| 11–13 | -0.03 | 13% | 26 Jul → | ||
| 1–13 | -0.08 | 13% | 26 Jul → | ||
| 5–13 | -0.06 | 13% | 26 Jul → | ||
| 8–13 | -0.03 | 8% | 25 Jul → | ||
| 11–13 | -0.03 | 2% | 25 Jul → | ||
| 12–12 | -0.04 | 23% | 25 Jul → | ||
| 13–5 | 0.06 | 3% | 24 Jul → | ||
| 13–8 | -0.08 | 11% | 24 Jul → | ||
| 10–13 | -0.05 | 18% | 24 Jul → | ||
| 13–7 | -0.03 | 16% | 24 Jul → | ||
| 15–15 | -0.03 | 10% | 24 Jul → | ||
| 10–13 | -0.03 | 5% | 24 Jul → | ||
| 9–13 | -0.06 | 9% | 24 Jul → | ||
| 5–13 | -0.09 | 3% | 24 Jul → | ||
| 13–8 | -0.06 | 9% | 24 Jul → | ||
| 15–15 | -0.06 | 16% | 23 Jul → |
Match data via Leetify.
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