✪Peachy — CS2 Stats
76561198051096447[U:1:90830719]
How this compares with the same rank
Median values for Level 10 among CSDB-tracked players (n=218), 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 | vs Level 10 |
|---|---|---|---|
| Headshot rate | 46.6% | 52.8% | 6.2% short |
| Shot accuracy | 15.4% | 13.7% | above |
| Kill/death ratio | 1.06 | 1.08 | 0.02 short |
| Match win rate | 48.8% | 49.2% | meets |
This profile matches the typical Level 10 player on 2 of 4 comparable metrics.
Widest gap: Headshot rate. That is the metric furthest from the Level 10 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: -30pp win rate · +0.03 avg rating
Player DNA
Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.
Limited utility dependence
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 ropz 86% playstyle similarity
Most alike: opening-fight frequency, positioning profile.
Where you differ: lower opening-duel success; 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. 616ms 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 5.8/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.02 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 | 35 | 19–16 | 54% | 0.00 | |
| A | 22 | 14–8 | 64% | -0.00 | |
| S | 12 | 8–4 | 67% | -0.00 | |
| A | 9 | 5–4 | 56% | 0.00 | |
| C | 9 | 4–5 | 44% | -0.00 | |
| D | 8 | 1–7 | 13% | -0.01 | |
| — | 3 | 1–2 | 33% | 0.00 | |
| — | 2 | 1–1 | 50% | 0.04 |
Across the last 100 tracked matches.
Nuke is currently your weakest sufficiently-sampled map (13% over 8). Start with the 6 essential Nuke 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 resultsLWLWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 1 | 100% | 1.50 | 18.0 |
| Anubis | 1 | 0% | 0.72 | 13.0 |
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.
- Grenades & UtilityGrenade Lineups →
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 2.8653 — below the 4 mark we flag
- Advanced Mechanics
You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.
T opening duels 34.0962% — below the 40% mark we flag
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
13% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–9 | 0.07 | 35% | 3 Jun → | ||
| 0–11 | -0.04 | 14% | 9 May → | ||
| 12–12 | -0.00 | 22% | 5 May → | ||
| 10–13 | 0.05 | 41% | 5 May → | ||
| 0–12 | -0.11 | 43% | 4 May → | ||
| 13–11 | 0.13 | 29% | 3 May → | ||
| 10–13 | -0.00 | 22% | 23 Apr → | ||
| 4–13 | -0.00 | 38% | 6 Mar → | ||
| 8–13 | 0.01 | 16% | 6 Mar → | ||
| 6–13 | -0.04 | 29% | 25 Feb → | ||
| 13–10 | -0.03 | 18% | 25 Feb → | ||
| 13–5 | 0.04 | 43% | 24 Feb → | ||
| 9–13 | -0.04 | 13% | 23 Feb → | ||
| 10–13 | -0.03 | 16% | 22 Feb → | ||
| 16–14 | -0.03 | 15% | 22 Feb → | ||
| 10–13 | -0.04 | 20% | 21 Feb → | ||
| 15–15 | -0.06 | 27% | 21 Feb → | ||
| 13–8 | -0.03 | 13% | 19 Feb → | ||
| 13–7 | 0.05 | 28% | 19 Feb → | ||
| 11–13 | -0.05 | 30% | 19 Feb → | ||
| 7–13 | 0.01 | 14% | 18 Feb → | ||
| 13–9 | -0.01 | 19% | 18 Feb → | ||
| 13–6 | 0.01 | 21% | 18 Feb → | ||
| 13–9 | -0.02 | 23% | 18 Feb → | ||
| 13–8 | 0.01 | 14% | 18 Feb → | ||
| 13–7 | -0.03 | 10% | 18 Feb → | ||
| 13–5 | 0.01 | 24% | 18 Feb → | ||
| 5–13 | 0.04 | 29% | 18 Feb → | ||
| 13–2 | 0.01 | 18% | 18 Feb → | ||
| 13–10 | 0.00 | 20% | 18 Feb → | ||
| 5–13 | -0.03 | 21% | 17 Feb → | ||
| 15–15 | -0.04 | 21% | 17 Feb → | ||
| 6–13 | -0.03 | 25% | 17 Feb → | ||
| 10–13 | 0.02 | 27% | 16 Feb → | ||
| 13–4 | 0.03 | 33% | 16 Feb → | ||
| 2–13 | -0.08 | 19% | 16 Feb → | ||
| 13–9 | 0.02 | 27% | 16 Feb → | ||
| 16–12 | 0.01 | 19% | 15 Feb → | ||
| 8–13 | 0.09 | 36% | 15 Feb → | ||
| 9–13 | -0.13 | 14% | 15 Feb → | ||
| 13–6 | 0.04 | 24% | 15 Feb → | ||
| 13–8 | -0.03 | 24% | 15 Feb → | ||
| 16–14 | 0.10 | 14% | 14 Feb → | ||
| 8–13 | -0.01 | 20% | 14 Feb → | ||
| 11–13 | 0.04 | 16% | 14 Feb → | ||
| 13–8 | -0.01 | 22% | 14 Feb → | ||
| 13–9 | 0.01 | 28% | 14 Feb → | ||
| 9–13 | -0.05 | 28% | 14 Feb → | ||
| 8–13 | 0.00 | 53% | 14 Feb → | ||
| 13–4 | 0.01 | 31% | 14 Feb → | ||
| 13–7 | 0.03 | 38% | 13 Feb → | ||
| 7–0 | 0.06 | 24% | 13 Feb → | ||
| 13–8 | 0.02 | 13% | 13 Feb → | ||
| 13–7 | 0.08 | 14% | 13 Feb → | ||
| 13–10 | 0.01 | 16% | 13 Feb → | ||
| 9–13 | -0.02 | 24% | 12 Feb → | ||
| 13–10 | -0.02 | 30% | 12 Feb → | ||
| 13–11 | 0.05 | 37% | 12 Feb → | ||
| 13–9 | 0.09 | 24% | 12 Feb → | ||
| 2–13 | -0.13 | 57% | 11 Feb → | ||
| 13–11 | -0.00 | 26% | 11 Feb → | ||
| 7–13 | 0.01 | 21% | 10 Feb → | ||
| 12–16 | -0.03 | 24% | 8 Feb → | ||
| 3–13 | -0.05 | 27% | 7 Feb → | ||
| 0–11 | -0.03 | 27% | 7 Feb → | ||
| 13–11 | -0.01 | 38% | 6 Feb → | ||
| 13–7 | 0.02 | 26% | 6 Feb → | ||
| 13–6 | 0.02 | 22% | 6 Feb → | ||
| 13–16 | 0.00 | 17% | 6 Feb → | ||
| 8–13 | 0.05 | 23% | 5 Feb → | ||
| 13–8 | -0.06 | 19% | 5 Feb → | ||
| 15–15 | -0.00 | 30% | 5 Feb → | ||
| 5–13 | -0.07 | 10% | 5 Feb → | ||
| 13–6 | 0.01 | 20% | 5 Feb → | ||
| 13–10 | 0.01 | 29% | 5 Feb → | ||
| 8–13 | -0.03 | 22% | 4 Feb → | ||
| 13–7 | 0.01 | 17% | 4 Feb → | ||
| 13–3 | 0.03 | 23% | 4 Feb → | ||
| 13–6 | -0.06 | 23% | 4 Feb → | ||
| 7–13 | -0.00 | 25% | 4 Feb → | ||
| 7–13 | 0.01 | 25% | 4 Feb → | ||
| 16–12 | 0.10 | 27% | 4 Feb → | ||
| 8–13 | -0.04 | 42% | 4 Feb → | ||
| 13–1 | -0.00 | 29% | 4 Feb → | ||
| 13–8 | -0.01 | 26% | 3 Feb → | ||
| 10–13 | -0.03 | 31% | 3 Feb → | ||
| 6–13 | -0.02 | 28% | 3 Feb → | ||
| 13–10 | -0.02 | 46% | 3 Feb → | ||
| 13–6 | 0.04 | 29% | 3 Feb → | ||
| 8–13 | 0.05 | 23% | 1 Feb → | ||
| 13–3 | 0.08 | 36% | 1 Feb → | ||
| 13–10 | -0.04 | 25% | 1 Feb → | ||
| 4–13 | 0.00 | 28% | 31 Jan → | ||
| 13–3 | 0.02 | 21% | 31 Jan → | ||
| 6–1 | 0.01 | 13% | 31 Jan → | ||
| 5–13 | 0.02 | 24% | 30 Jan → | ||
| 13–6 | 0.08 | 21% | 30 Jan → | ||
| 13–9 | -0.05 | 17% | 29 Jan → | ||
| 7–13 | 0.07 | 19% | 29 Jan → | ||
| 4–7 | -0.01 | 36% | 29 Jan → |
Match data via Leetify.