Big Naturals — CS2 Stats
76561198170356675[U:1:210090947]✓ No bans
How this compares with the same rank
Median values for Pink band among CSDB-tracked players (n=201), 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 | Pink band median | vs Pink band |
|---|---|---|---|
| Headshot rate | 45.9% | 48.1% | 2.1% short |
| Shot accuracy | 21.4% | 12.9% | above |
| Kill/death ratio | 0.88 | 1.08 | 0.20 short |
| Match win rate | 72.8% | 46.5% | above |
This profile matches the typical Pink band player on 2 of 4 comparable metrics.
Widest gap: Kill/death ratio. That is the metric furthest from the Pink 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: -20pp win rate · +0.01 avg rating
Player DNA
Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.
Sharp aimerStrong CT-side opener
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 Twistzz 95% playstyle similarity
Most alike: opening-fight frequency, opening-duel success.
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
Strengths
Aim. Aim score of 85 — the mechanical foundation is a clear strength.
Areas to improve
Preaim. Mechanical aim is strong but the crosshair sits 10.6° off target when enemies appear — placement, not flicking, is the bigger win available.
T-side openings. Opening success drops from 48% on CT to 30% on T — the same duels are being taken with worse setups on the attacking side.
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 7.0/10 (Strong), 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 | 22 | 8–14 | 36% | 0.04 | |
| S | 22 | 16–6 | 73% | 0.05 | |
| office | A | 20 | 11–9 | 55% | 0.02 |
| agency | B | 8 | 4–4 | 50% | 0.04 |
| B | 6 | 3–3 | 50% | 0.11 | |
| D | 6 | 2–4 | 33% | 0.08 | |
| S | 5 | 5–0 | 100% | 0.06 | |
| C | 5 | 2–3 | 40% | 0.03 | |
| — | 3 | 2–1 | 67% | 0.07 | |
| — | 1 | 1–0 | 100% | -0.01 | |
| tuscan | — | 1 | 1–0 | 100% | 0.05 |
| breach | — | 1 | 1–0 | 100% | 0.05 |
Across the last 100 tracked matches.
Nuke is currently your weakest sufficiently-sampled map (33% over 6). 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.
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 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 30.1282% — 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.
33% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–7 | 0.10 | 24% | 1 Jul → | ||
| 13–4 | 0.20 | 22% | 1 Jul → | ||
| 13–8 | 0.07 | 24% | 1 Jul → | ||
| 8–13 | 0.03 | 33% | 1 Jul → | ||
| 13–4 | 0.05 | 35% | 29 Jun → | ||
| 8–13 | -0.01 | 21% | 20 Jun → | ||
| 5–13 | -0.01 | 20% | 20 Jun → | ||
| 9–13 | 0.07 | 23% | 19 Jun → | ||
| 13–8 | 0.10 | 23% | 19 Jun → | ||
| 15–15 | 0.10 | 30% | 19 Jun → | ||
| 13–3 | 0.12 | 23% | 19 Jun → | ||
| 13–10 | -0.01 | 34% | 12 Jun → | ||
| 11–13 | 0.01 | 29% | 12 Jun → | ||
| 13–8 | 0.10 | 40% | 12 Jun → | ||
| 13–11 | 0.07 | 28% | 12 Jun → | ||
| 13–2 | 0.16 | 34% | 12 Jun → | ||
| 5–13 | 0.06 | 18% | 7 Jun → | ||
| 13–11 | 0.02 | 20% | 30 May → | ||
| 13–11 | 0.07 | 25% | 30 May → | ||
| 15–15 | 0.03 | 35% | 30 May → | ||
| 13–11 | 0.04 | 11% | 30 May → | ||
| 13–8 | 0.09 | 38% | 30 May → | ||
| 13–8 | -0.02 | 75% | 30 May → | ||
| 4–13 | 0.02 | 30% | 30 May → | ||
| 13–5 | -0.01 | 53% | 30 May → | ||
| 6–13 | -0.05 | 29% | 30 May → | ||
| 13–2 | 0.12 | 26% | 29 May → | ||
| 13–11 | 0.05 | 22% | 29 May → | ||
| 13–1 | 0.19 | 40% | 29 May → | ||
| office | 12–12 | -0.06 | 26% | 29 Jun → | |
| 14–16 | 0.08 | 22% | 16 Aug → | ||
| 15–15 | -0.03 | 22% | 16 Aug → | ||
| office | 9–16 | -0.05 | 14% | 6 Aug → | |
| office | 16–11 | 0.09 | 22% | 6 Aug → | |
| 16–4 | 0.04 | 28% | 6 Aug → | ||
| 16–10 | 0.00 | 13% | 5 Aug → | ||
| agency | 14–16 | -0.02 | 25% | 5 Aug → | |
| agency | 16–12 | 0.07 | 19% | 5 Aug → | |
| 14–16 | 0.06 | 18% | 5 Aug → | ||
| 6–2 | 0.14 | 30% | 5 Aug → | ||
| office | 16–9 | -0.02 | 21% | 4 Aug → | |
| office | 16–8 | 0.03 | 19% | 4 Aug → | |
| office | 16–14 | 0.00 | 10% | 4 Aug → | |
| 11–16 | 0.10 | 20% | 2 Aug → | ||
| office | 16–6 | 0.10 | 27% | 30 Jul → | |
| office | 12–16 | 0.08 | 25% | 30 Jul → | |
| 14–16 | 0.11 | 22% | 30 Jul → | ||
| 16–6 | 0.12 | 29% | 30 Jul → | ||
| 9–16 | 0.08 | 21% | 26 Jul → | ||
| 13–16 | 0.05 | 8% | 25 Jul → | ||
| 16–13 | 0.06 | 28% | 23 Jul → | ||
| 11–16 | 0.07 | 22% | 23 Jul → | ||
| office | 16–8 | -0.02 | 11% | 22 Jul → | |
| agency | 16–11 | 0.05 | 38% | 22 Jul → | |
| 11–16 | 0.06 | 14% | 6 Jul → | ||
| 6–16 | -0.10 | 15% | 6 Jul → | ||
| 6–16 | 0.01 | 10% | 6 Jul → | ||
| 9–16 | -0.03 | 8% | 6 Jul → | ||
| 16–10 | 0.01 | 20% | 6 Jul → | ||
| 2–11 | -0.01 | 35% | 5 Jul → | ||
| 16–8 | 0.01 | 23% | 5 Jul → | ||
| office | 13–16 | 0.02 | 20% | 1 Jul → | |
| 4–16 | -0.06 | 28% | 1 Jul → | ||
| 2–0 | 0.18 | 100% | 1 Jul → | ||
| office | 14–16 | -0.04 | 38% | 25 Jun → | |
| office | 16–10 | 0.05 | 17% | 25 Jun → | |
| agency | 7–16 | -0.03 | 21% | 25 Jun → | |
| office | 10–16 | 0.00 | 12% | 23 Jun → | |
| 8–16 | 0.16 | 26% | 29 May → | ||
| agency | 16–14 | 0.14 | 17% | 28 May → | |
| agency | 11–16 | 0.06 | 22% | 21 May → | |
| office | 16–8 | 0.04 | 13% | 21 May → | |
| 16–9 | 0.12 | 26% | 21 May → | ||
| office | 11–16 | -0.04 | 2% | 19 May → | |
| office | 16–14 | -0.02 | 37% | 22 Apr → | |
| agency | 16–2 | 0.04 | 18% | 22 Apr → | |
| office | 16–13 | 0.14 | 40% | 21 Apr → | |
| agency | 11–16 | 0.04 | 10% | 21 Apr → | |
| 3–16 | 0.02 | 34% | 21 Apr → | ||
| office | 16–7 | 0.01 | 40% | 9 Apr → | |
| office | 7–16 | -0.01 | 22% | 9 Apr → | |
| office | 8–16 | 0.10 | 22% | 9 Apr → | |
| 15–15 | 0.11 | 16% | 13 Nov → | ||
| 10–1 | -0.01 | 38% | 22 Sept → | ||
| 9–16 | 0.07 | 16% | 22 Sept → | ||
| 14–16 | 0.02 | 21% | 22 Sept → | ||
| 16–14 | 0.01 | 13% | 22 Sept → | ||
| 16–10 | 0.03 | 22% | 22 Sept → | ||
| 16–11 | 0.02 | 23% | 22 Sept → | ||
| 14–16 | 0.08 | 18% | 17 Sept → | ||
| 16–14 | 0.06 | 16% | 17 Sept → | ||
| 16–13 | 0.04 | 35% | 17 Sept → | ||
| tuscan | 16–8 | 0.05 | 17% | 17 Sept → | |
| 16–6 | 0.11 | 22% | 17 Sept → | ||
| 16–9 | 0.12 | 19% | 17 Sept → | ||
| 16–1 | 0.11 | 16% | 17 Sept → | ||
| 16–11 | 0.02 | 24% | 16 Sept → | ||
| 13–16 | 0.05 | 23% | 16 Sept → | ||
| breach | 16–13 | 0.05 | 16% | 17 Aug → | |
| 16–10 | 0.05 | 24% | 14 Aug → |
Match data via Leetify.