S4ilingTurtle — CS2 Stats
76561198275620656[U:1:315354928]
How this compares with the same rank
Median values for Light Blue band among CSDB-tracked players (n=404), 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 | Light Blue band median | Blue band median | vs Blue band |
|---|---|---|---|---|
| Headshot rate | 42.1% | 40.1% | 41.7% | meets |
| Shot accuracy | 19.0% | 7.6% | 8.8% | above |
| Kill/death ratio | 1.06 | 0.92 | 0.97 | above |
| Match win rate | 40.8% | 42.2% | 43.8% | 3.0% short |
This profile matches the typical Blue band player on 3 of 4 comparable metrics.
Widest gap: Match win rate. That is the metric furthest from the 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: -30pp win rate · -0.03 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 b1t 84% playstyle similarity
Most alike: opening-duel success, utility contribution.
Where you differ: higher 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. 603ms 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 4.1/10 (Developing), 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 |
|---|---|---|---|---|---|
 mirage | B | 64 | 30–34 | 47% | -0.00 |
 dust2 | D | 15 | 4–11 | 27% | -0.00 |
 nuke | S | 8 | 6–2 | 75% | 0.02 |
 inferno | D | 5 | 1–4 | 20% | -0.02 |
 overpass | — | 4 | 1–3 | 25% | 0.01 |
 ancient | — | 3 | 2–1 | 67% | 0.05 |
 vertigo | — | 1 | 0–1 | 0% | -0.04 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (20% over 5). 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.
- Advanced Mechanics
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 35.394% — 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.
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 | |
|---|---|---|---|---|---|
| nuke | 13–1 | 0.04 | 0% | 14 Jul → | |
| inferno | 12–12 | 0.02 | 12% | 14 Jul → | |
| mirage | 13–5 | -0.05 | 11% | 1 Jul → | |
| mirage | 12–12 | -0.06 | 15% | 18 Jun → | |
| dust2 | 12–16 | -0.01 | 14% | 9 Apr → | |
| ancient | 6–13 | 0.02 | 18% | 8 Apr → | |
| mirage | 13–9 | 0.10 | 29% | 7 Apr → | |
| inferno | 11–13 | -0.03 | 18% | 1 Apr → | |
| mirage | 5–13 | -0.08 | 15% | 1 Apr → | |
| mirage | 9–13 | 0.10 | 21% | 29 Mar → | |
| nuke | 13–9 | 0.10 | 18% | 28 Mar → | |
| mirage | 13–3 | 0.13 | 20% | 27 Mar → | |
| mirage | 13–9 | 0.03 | 10% | 27 Mar → | |
| nuke | 9–13 | -0.00 | 11% | 25 Mar → | |
| mirage | 16–12 | -0.02 | 12% | 25 Mar → | |
| mirage | 13–8 | 0.08 | 24% | 25 Mar → | |
| nuke | 13–4 | -0.02 | 20% | 20 Mar → | |
| dust2 | 3–13 | -0.01 | 5% | 18 Mar → | |
| mirage | 12–12 | 0.03 | 34% | 18 Mar → | |
| mirage | 6–13 | 0.01 | 24% | 18 Mar → | |
| mirage | 0–6 | -0.01 | 14% | 18 Mar → | |
| mirage | 13–6 | 0.10 | 19% | 18 Mar → | |
| dust2 | 9–13 | -0.00 | 21% | 17 Mar → | |
| mirage | 10–13 | 0.02 | 28% | 17 Mar → | |
| mirage | 4–13 | -0.08 | 38% | 17 Mar → | |
| inferno | 12–16 | -0.06 | 17% | 13 Mar → | |
| mirage | 8–13 | 0.01 | 24% | 13 Mar → | |
| nuke | 13–10 | 0.04 | 22% | 6 Mar → | |
| overpass | 8–13 | 0.00 | 11% | 6 Mar → | |
| dust2 | 8–13 | -0.03 | 4% | 6 Mar → | |
| mirage | 13–9 | 0.03 | 18% | 5 Mar → | |
| dust2 | 12–16 | -0.03 | 28% | 5 Mar → | |
| mirage | 13–10 | -0.00 | 30% | 28 Feb → | |
| mirage | 13–7 | -0.03 | 29% | 10 Feb → | |
| dust2 | 13–16 | 0.05 | 29% | 10 Feb → | |
| dust2 | 13–5 | 0.04 | 25% | 10 Feb → | |
| mirage | 13–9 | 0.01 | 20% | 9 Feb → | |
| mirage | 1–13 | -0.10 | 13% | 8 Feb → | |
| mirage | 13–8 | -0.01 | 25% | 8 Feb → | |
| mirage | 8–13 | -0.01 | 24% | 5 Feb → | |
| mirage | 11–13 | 0.03 | 36% | 5 Feb → | |
| mirage | 13–5 | -0.01 | 29% | 5 Feb → | |
| mirage | 15–15 | -0.00 | 26% | 4 Feb → | |
| mirage | 13–8 | 0.09 | 23% | 4 Feb → | |
| dust2 | 13–7 | -0.02 | 41% | 4 Feb → | |
| mirage | 13–3 | -0.07 | 23% | 4 Feb → | |
| overpass | 9–13 | 0.05 | 16% | 4 Feb → | |
| mirage | 9–13 | -0.04 | 29% | 4 Feb → | |
| mirage | 13–4 | -0.01 | 11% | 4 Feb → | |
| mirage | 13–11 | -0.07 | 8% | 3 Feb → | |
| mirage | 5–13 | -0.04 | 20% | 2 Feb → | |
| mirage | 13–2 | 0.01 | 63% | 1 Feb → | |
| nuke | 13–6 | 0.03 | 17% | 31 Jan → | |
| mirage | 15–15 | 0.12 | 23% | 31 Jan → | |
| mirage | 10–13 | 0.13 | 29% | 31 Jan → | |
| mirage | 12–12 | 0.04 | 14% | 31 Jan → | |
| mirage | 9–13 | 0.02 | 17% | 31 Jan → | |
| mirage | 10–13 | 0.04 | 20% | 30 Jan → | |
| mirage | 13–6 | -0.05 | 17% | 30 Jan → | |
| mirage | 7–13 | -0.04 | 11% | 30 Jan → | |
| dust2 | 5–13 | 0.04 | 32% | 30 Jan → | |
| mirage | 13–10 | 0.03 | 15% | 30 Jan → | |
| dust2 | 9–13 | 0.02 | 38% | 26 Jan → | |
| mirage | 13–7 | -0.01 | 14% | 13 Jan → | |
| mirage | 8–13 | -0.02 | 20% | 12 Jan → | |
| dust2 | 10–13 | -0.06 | 16% | 20 Sept → | |
| inferno | 13–9 | -0.03 | 27% | 25 Aug → | |
| dust2 | 15–15 | 0.05 | 40% | 22 Aug → | |
| ancient | 13–9 | 0.05 | 16% | 22 Aug → | |
| overpass | 13–7 | 0.08 | 25% | 22 Aug → | |
| dust2 | 1–13 | -0.09 | 9% | 14 Aug → | |
| nuke | 13–8 | 0.03 | 10% | 7 Aug → | |
| mirage | 16–14 | -0.03 | 22% | 7 Aug → | |
| overpass | 8–13 | -0.10 | 15% | 6 Aug → | |
| ancient | 13–9 | 0.07 | 18% | 3 Aug → | |
| dust2 | 13–2 | -0.04 | 10% | 26 Jul → | |
| mirage | 13–8 | -0.02 | 23% | 24 Jul → | |
| inferno | 4–13 | -0.01 | 7% | 23 Jul → | |
| mirage | 3–13 | -0.04 | 41% | 11 Jul → | |
| mirage | 13–3 | 0.03 | 21% | 6 Jul → | |
| mirage | 0–13 | -0.08 | 31% | 6 Jul → | |
| mirage | 4–13 | -0.03 | 19% | 5 Jul → | |
| mirage | 6–13 | -0.08 | 16% | 26 Jun → | |
| mirage | 8–13 | -0.07 | 14% | 25 Jun → | |
| mirage | 13–5 | -0.05 | 17% | 19 Jun → | |
| mirage | 2–13 | 0.01 | 30% | 18 Jun → | |
| nuke | 9–13 | -0.04 | 3% | 14 Jun → | |
| dust2 | 13–3 | 0.06 | 22% | 1 Jun → | |
| mirage | 7–13 | -0.04 | 21% | 30 May → | |
| vertigo | 7–13 | -0.04 | 16% | 26 May → | |
| mirage | 13–9 | 0.05 | 17% | 19 May → | |
| mirage | 13–8 | -0.01 | 18% | 16 May → | |
| mirage | 11–13 | -0.04 | 26% | 20 Apr → | |
| mirage | 0–13 | -0.03 | 13% | 20 Apr → | |
| mirage | 2–13 | -0.05 | 24% | 20 Apr → | |
| mirage | 9–13 | -0.03 | 18% | 4 Apr → | |
| mirage | 13–7 | 0.02 | 24% | 4 Apr → | |
| mirage | 13–11 | -0.02 | 19% | 6 Feb → | |
| mirage | 3–13 | -0.02 | 9% | 5 Feb → | |
| mirage | 13–5 | 0.07 | 13% | 28 Jan → |
Match data via Leetify.
