monsterenergylover06 — CS2 Stats
76561198662079469[U:1:701813741]✓ No bans
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -40pp win rate · +0.00 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 54% playstyle similarity
Most alike: opening-duel success, utility contribution.
Where you differ: lower positioning profile; 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. 772ms 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 3.4/10 (Learning), 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 56 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 |
|---|---|---|---|---|---|
 ancient | C | 20 | 8–12 | 40% | -0.09 |
 cache | A | 18 | 10–8 | 56% | -0.10 |
 train | A | 11 | 6–5 | 55% | -0.09 |
 inferno | S | 7 | 6–1 | 86% | -0.06 |
Across the last 56 tracked matches.
Ancient is currently your weakest sufficiently-sampled map (40% over 20). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.
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.
- 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 6.2781% — below the 15% mark we flag
- Best CS2 SettingsAim Training →
Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.
Reaction time 771.7322ms — above the 700ms 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 0.2043 — 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.
40% win rate across 20 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| cache | 6–1 | -0.03 | 33% | 28 Aug → | |
| inferno | 13–1 | -0.10 | 0% | 28 Aug → | |
| train | 6–13 | -0.10 | 6% | 28 Aug → | |
| ancient | 8–13 | -0.09 | 7% | 28 Aug → | |
| cache | 11–13 | -0.11 | 15% | 28 Aug → | |
| train | 13–8 | -0.08 | 0% | 27 Aug → | |
| ancient | 8–13 | -0.09 | 9% | 27 Aug → | |
| cache | 10–13 | -0.15 | 0% | 27 Aug → | |
| inferno | 12–12 | -0.10 | 12% | 27 Aug → | |
| train | 13–6 | -0.04 | 4% | 27 Aug → | |
| ancient | 11–13 | -0.10 | 5% | 27 Aug → | |
| cache | 13–3 | -0.10 | 13% | 27 Aug → | |
| inferno | 13–6 | -0.09 | 7% | 26 Aug → | |
| train | 13–6 | -0.09 | 0% | 26 Aug → | |
| ancient | 13–5 | -0.07 | 5% | 26 Aug → | |
| cache | 9–13 | -0.10 | 3% | 26 Aug → | |
| ancient | 13–5 | -0.09 | 6% | 25 Aug → | |
| cache | 13–8 | -0.11 | 0% | 25 Aug → | |
| inferno | 13–8 | -0.06 | 0% | 25 Aug → | |
| train | 13–7 | -0.07 | 13% | 25 Aug → | |
| ancient | 12–12 | -0.08 | 6% | 25 Aug → | |
| cache | 13–2 | -0.08 | 0% | 25 Aug → | |
| cache | 13–4 | -0.08 | 6% | 25 Aug → | |
| ancient | 13–3 | -0.05 | 7% | 24 Aug → | |
| cache | 8–13 | -0.12 | 0% | 24 Aug → | |
| inferno | 13–5 | -0.07 | 0% | 24 Aug → | |
| train | 12–12 | -0.10 | 8% | 24 Aug → | |
| ancient | 12–12 | -0.09 | 10% | 24 Aug → | |
| cache | 13–9 | -0.10 | 13% | 24 Aug → | |
| train | 10–13 | -0.13 | 13% | 16 Aug → | |
| inferno | 13–3 | -0.10 | 14% | 16 Aug → | |
| cache | 13–11 | -0.09 | 4% | 16 Aug → | |
| ancient | 1–13 | -0.15 | 25% | 16 Aug → | |
| cache | 8–13 | -0.06 | 7% | 14 Aug → | |
| ancient | 13–9 | -0.11 | 11% | 14 Aug → | |
| ancient | 12–12 | -0.08 | 18% | 13 Aug → | |
| ancient | 6–1 | -0.07 | 20% | 13 Aug → | |
| inferno | 13–1 | 0.08 | 22% | 13 Aug → | |
| train | 13–8 | -0.11 | 15% | 13 Aug → | |
| train | 10–0 | 0.00 | 8% | 13 Aug → | |
| cache | 13–1 | -0.10 | 17% | 13 Aug → | |
| ancient | 11–13 | -0.10 | 9% | 13 Aug → | |
| cache | 13–6 | -0.15 | 0% | 12 Aug → | |
| ancient | 2–13 | -0.13 | 0% | 12 Aug → | |
| train | 6–13 | -0.11 | 0% | 10 Aug → | |
| cache | 8–13 | -0.13 | 18% | 10 Aug → | |
| ancient | 13–5 | -0.10 | 13% | 10 Aug → | |
| cache | 9–13 | -0.12 | 13% | 7 Aug → | |
| cache | 13–1 | -0.09 | 5% | 7 Aug → | |
| ancient | 3–13 | -0.09 | 17% | 7 Aug → | |
| ancient | 10–13 | -0.16 | 13% | 5 Aug → | |
| cache | 12–12 | -0.06 | 12% | 5 Aug → | |
| ancient | 13–11 | -0.08 | 22% | 5 Aug → | |
| train | 6–13 | -0.13 | 21% | 4 Aug → | |
| ancient | 13–8 | -0.09 | 29% | 4 Aug → | |
| ancient | 7–13 | -0.08 | 7% | 4 Aug → |
Match data via Leetify.
