stonedkdog — CS2 Stats
76561199125386335[U:1:1165120607]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Grey band among CSDB-tracked players (n=369), 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 | Grey band median | Light Blue band median | vs Light Blue band |
|---|---|---|---|---|
| Headshot rate | 36.5% | 37.5% | 39.7% | 3.2% short |
| Shot accuracy | 0.0% | 4.5% | 6.7% | 6.7% short |
| Kill/death ratio | 0.41 | 0.82 | 0.91 | 0.49 short |
| Match win rate | 28.9% | 39.1% | 42.1% | 13.3% short |
This profile sits below the typical Light Blue band player on every metric we can compare.
Widest gap: Shot accuracy. That is the metric furthest from the Light Blue 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: +10pp 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 59% playstyle similarity
Most alike: opening-duel success, utility contribution.
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. 809ms 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 2.7/10 (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 |
|---|---|---|---|---|---|
| D | 18 | 5–13 | 28% | -0.06 | |
| D | 17 | 3–14 | 18% | -0.07 | |
| C | 17 | 6–11 | 35% | -0.07 | |
| D | 16 | 5–11 | 31% | -0.07 | |
| D | 13 | 4–9 | 31% | -0.08 | |
| D | 10 | 2–8 | 20% | -0.07 | |
| — | 4 | 0–4 | 0% | -0.10 | |
| — | 3 | 1–2 | 33% | -0.03 | |
| — | 1 | 0–1 | 0% | -0.09 | |
| — | 1 | 0–1 | 0% | -0.07 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (18% over 17). Start with the 6 essential Inferno 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.
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 9.3107% — 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 808.7093ms — 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 0.4256 — 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.
18% win rate across 17 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–9 | -0.10 | 11% | 28 Aug → | ||
| 10–13 | -0.02 | 11% | 28 Aug → | ||
| 8–13 | -0.11 | 8% | 27 Aug → | ||
| 2–13 | -0.13 | 17% | 27 Aug → | ||
| 13–11 | -0.10 | 3% | 27 Aug → | ||
| 2–13 | -0.10 | 17% | 27 Aug → | ||
| 12–16 | -0.02 | 8% | 27 Aug → | ||
| 14–16 | -0.10 | 9% | 26 Aug → | ||
| 13–16 | -0.07 | 7% | 25 Aug → | ||
| 4–13 | -0.10 | 0% | 25 Aug → | ||
| 13–5 | -0.09 | 9% | 25 Aug → | ||
| 7–13 | 0.01 | 8% | 24 Aug → | ||
| 5–13 | -0.12 | 20% | 24 Aug → | ||
| 6–13 | -0.09 | 0% | 23 Aug → | ||
| 3–13 | -0.00 | 6% | 23 Aug → | ||
| 12–12 | -0.06 | 16% | 23 Aug → | ||
| 11–13 | -0.10 | 9% | 23 Aug → | ||
| 0–13 | -0.08 | 12% | 23 Aug → | ||
| 9–13 | -0.09 | 14% | 23 Aug → | ||
| 8–13 | -0.10 | 10% | 23 Aug → | ||
| 7–13 | -0.13 | 4% | 23 Aug → | ||
| 6–13 | -0.06 | 25% | 22 Aug → | ||
| 13–6 | -0.13 | 0% | 22 Aug → | ||
| 6–13 | -0.05 | 6% | 21 Aug → | ||
| 2–13 | -0.10 | 13% | 21 Aug → | ||
| 13–5 | -0.06 | 7% | 21 Aug → | ||
| 9–13 | -0.01 | 8% | 21 Aug → | ||
| 13–2 | -0.08 | 13% | 21 Aug → | ||
| 2–13 | -0.08 | 10% | 21 Aug → | ||
| 8–13 | -0.08 | 6% | 21 Aug → | ||
| 4–13 | -0.04 | 11% | 21 Aug → | ||
| 14–16 | -0.03 | 12% | 21 Aug → | ||
| 10–13 | -0.07 | 15% | 21 Aug → | ||
| 10–13 | -0.10 | 17% | 20 Aug → | ||
| 8–13 | -0.09 | 0% | 20 Aug → | ||
| 6–13 | -0.09 | 3% | 20 Aug → | ||
| 2–0 | -0.04 | 0% | 20 Aug → | ||
| 13–11 | -0.09 | 10% | 20 Aug → | ||
| 9–13 | -0.09 | 7% | 20 Aug → | ||
| 13–5 | -0.05 | 12% | 19 Aug → | ||
| 1–13 | -0.14 | 9% | 17 Aug → | ||
| 1–8 | -0.04 | 0% | 16 Aug → | ||
| 5–13 | -0.02 | 10% | 14 Aug → | ||
| 13–10 | -0.03 | 15% | 14 Aug → | ||
| 2–13 | -0.11 | 15% | 12 Aug → | ||
| 7–13 | -0.07 | 3% | 12 Aug → | ||
| 13–11 | -0.07 | 6% | 12 Aug → | ||
| 13–3 | 0.08 | 7% | 12 Aug → | ||
| 9–13 | -0.04 | 7% | 12 Aug → | ||
| 13–6 | 0.07 | 6% | 12 Aug → | ||
| 1–13 | -0.12 | 0% | 12 Aug → | ||
| 3–13 | -0.03 | 11% | 6 Aug → | ||
| 7–13 | -0.04 | 11% | 6 Aug → | ||
| 1–13 | -0.03 | 11% | 6 Aug → | ||
| 9–13 | -0.04 | 4% | 6 Aug → | ||
| 8–13 | -0.12 | 5% | 6 Aug → | ||
| 13–7 | -0.05 | 9% | 6 Aug → | ||
| 8–13 | -0.09 | 11% | 5 Aug → | ||
| 14–16 | -0.12 | 8% | 5 Aug → | ||
| 6–13 | -0.10 | 5% | 5 Aug → | ||
| 13–5 | -0.03 | 15% | 5 Aug → | ||
| 13–5 | -0.06 | 14% | 5 Aug → | ||
| 9–13 | -0.09 | 12% | 5 Aug → | ||
| 13–11 | -0.05 | 5% | 5 Aug → | ||
| 13–1 | 0.03 | 8% | 5 Aug → | ||
| 2–13 | -0.15 | 13% | 5 Aug → | ||
| 13–6 | -0.06 | 10% | 5 Aug → | ||
| 5–13 | -0.09 | 11% | 5 Aug → | ||
| 7–13 | -0.05 | 15% | 5 Aug → | ||
| 8–13 | -0.08 | 6% | 5 Aug → | ||
| 3–13 | -0.10 | 7% | 4 Aug → | ||
| 9–13 | -0.02 | 9% | 4 Aug → | ||
| 5–13 | -0.12 | 7% | 4 Aug → | ||
| 5–13 | -0.14 | 10% | 4 Aug → | ||
| 9–13 | -0.05 | 13% | 4 Aug → | ||
| 9–13 | -0.11 | 10% | 4 Aug → | ||
| 1–13 | -0.07 | 5% | 3 Aug → | ||
| 1–13 | -0.08 | 17% | 2 Aug → | ||
| 5–13 | -0.09 | 3% | 2 Aug → | ||
| 13–4 | -0.06 | 13% | 2 Aug → | ||
| 7–13 | -0.09 | 4% | 2 Aug → | ||
| 13–11 | -0.07 | 16% | 2 Aug → | ||
| 13–10 | -0.09 | 13% | 2 Aug → | ||
| 10–13 | -0.04 | 14% | 2 Aug → | ||
| 7–13 | -0.11 | 7% | 2 Aug → | ||
| 5–13 | -0.04 | 13% | 1 Aug → | ||
| 7–13 | -0.10 | 14% | 31 Jul → | ||
| 11–13 | -0.08 | 14% | 31 Jul → | ||
| 13–8 | -0.00 | 15% | 31 Jul → | ||
| 7–13 | -0.09 | 0% | 31 Jul → | ||
| 13–3 | -0.04 | 20% | 31 Jul → | ||
| 6–13 | -0.09 | 6% | 31 Jul → | ||
| 12–16 | -0.10 | 5% | 31 Jul → | ||
| 8–13 | -0.06 | 11% | 31 Jul → | ||
| 13–1 | -0.06 | 5% | 31 Jul → | ||
| 13–5 | -0.10 | 11% | 31 Jul → | ||
| 7–13 | -0.10 | 13% | 31 Jul → | ||
| 3–13 | -0.07 | 14% | 30 Jul → | ||
| 12–12 | -0.05 | 13% | 30 Jul → | ||
| 5–13 | -0.07 | 0% | 30 Jul → |
Match data via Leetify.