✪ Tuty6900 — CS2 Stats
76561198274898051[U:1:314632323]
How this compares with the same rank
Median values for Pink band among CSDB-tracked players (n=3,917), 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 | Red band median | vs Red band |
|---|---|---|---|---|
| Headshot rate | 47.3% | 47.2% | 49.9% | 2.6% short |
| Shot accuracy | 17.6% | 12.7% | 13.4% | above |
| Kill/death ratio | 1.02 | 1.09 | 1.12 | 0.10 short |
| Match win rate | 44.2% | 46.6% | 48.4% | 4.2% short |
This profile matches the typical Red band player on 1 of 4 comparable metrics.
Widest gap: Kill/death ratio. That is the metric furthest from the Red 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 · +0.01 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
Sharp aimerEffective flashesLimited 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 sh1ro 92% playstyle similarity
Most alike: opening-fight frequency, utility contribution.
Where you differ: lower positioning 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
Strengths
Aim. Aim score of 86 — the mechanical foundation is a clear strength.
Flashes. 0.81 enemies blinded per flash — utility that consistently lands.
Areas to improve
Positioning. Positioning trails aim by 37 points — deaths here waste a strong aim profile.
Reaction time. 576ms 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 6.8/10 (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 | 37 | 17–20 | 46% | -0.00 | |
| B | 26 | 14–12 | 54% | 0.00 | |
| C | 15 | 6–9 | 40% | -0.00 | |
| B | 8 | 4–4 | 50% | 0.02 | |
| S | 7 | 5–2 | 71% | -0.01 | |
| — | 3 | 0–3 | 0% | -0.02 | |
| — | 2 | 1–1 | 50% | -0.04 | |
| warden | — | 1 | 1–0 | 100% | 0.06 |
| stronghold | — | 1 | 0–1 | 0% | -0.01 |
Across the last 100 tracked matches.
Nuke is currently your weakest sufficiently-sampled map (40% over 15). 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 resultsLLLLW
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 3.8995 — below the 4 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 15 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–7 | -0.09 | 23% | 10 Aug → | ||
| 13–6 | 0.03 | 24% | 4 Aug → | ||
| 6–13 | -0.05 | 41% | 2 Aug → | ||
| 9–13 | -0.06 | 8% | 1 Aug → | ||
| 13–11 | 0.03 | 21% | 1 Aug → | ||
| 13–6 | -0.02 | 23% | 22 Jul → | ||
| 13–3 | -0.01 | 14% | 19 Jul → | ||
| 13–6 | 0.06 | 17% | 19 Jul → | ||
| 13–7 | 0.01 | 13% | 19 Jul → | ||
| 13–6 | 0.03 | 24% | 19 Jul → | ||
| 9–13 | -0.06 | 19% | 17 Jul → | ||
| 9–13 | -0.07 | 11% | 16 Jul → | ||
| 13–10 | -0.06 | 26% | 16 Jul → | ||
| 8–13 | 0.06 | 31% | 15 Jul → | ||
| 13–11 | -0.01 | 30% | 15 Jul → | ||
| 10–13 | 0.03 | 19% | 15 Jul → | ||
| 5–13 | -0.09 | 14% | 14 Jul → | ||
| 13–8 | -0.05 | 35% | 13 Jul → | ||
| 13–1 | 0.11 | 17% | 13 Jul → | ||
| 13–6 | 0.02 | 4% | 13 Jul → | ||
| 13–3 | 0.03 | 21% | 13 Jul → | ||
| 0–13 | -0.03 | 11% | 11 Jul → | ||
| 14–16 | 0.05 | 23% | 11 Jul → | ||
| 13–9 | -0.00 | 16% | 11 Jul → | ||
| 13–6 | -0.04 | 48% | 11 Jul → | ||
| 13–9 | -0.02 | 19% | 21 Jun → | ||
| 7–13 | -0.04 | 40% | 21 Jun → | ||
| 7–13 | 0.03 | 31% | 18 Jun → | ||
| 9–13 | 0.00 | 28% | 18 Jun → | ||
| 13–16 | 0.06 | 26% | 2 Jun → | ||
| 13–7 | 0.03 | 21% | 30 May → | ||
| 9–13 | -0.04 | 21% | 6 May → | ||
| 6–13 | -0.05 | 28% | 3 May → | ||
| 13–11 | -0.03 | 31% | 15 Apr → | ||
| 10–13 | -0.02 | 24% | 12 Apr → | ||
| 9–13 | 0.00 | 12% | 6 Apr → | ||
| 13–4 | 0.05 | 18% | 5 Apr → | ||
| 13–9 | 0.08 | 22% | 3 Apr → | ||
| 10–13 | -0.07 | 15% | 2 Apr → | ||
| 16–13 | -0.02 | 17% | 30 Mar → | ||
| 15–15 | -0.02 | 20% | 29 Mar → | ||
| 13–9 | 0.02 | 50% | 29 Mar → | ||
| 13–10 | 0.02 | 22% | 29 Mar → | ||
| 13–7 | 0.05 | 30% | 29 Mar → | ||
| 8–13 | -0.06 | 15% | 29 Mar → | ||
| 13–8 | 0.08 | 19% | 28 Mar → | ||
| 11–13 | 0.02 | 33% | 27 Mar → | ||
| 9–13 | 0.00 | 36% | 26 Mar → | ||
| 9–13 | -0.01 | 34% | 26 Mar → | ||
| 16–13 | -0.02 | 30% | 25 Mar → | ||
| 4–13 | -0.07 | 14% | 25 Mar → | ||
| 13–11 | -0.03 | 14% | 24 Mar → | ||
| 12–16 | -0.04 | 32% | 24 Mar → | ||
| 10–13 | 0.06 | 35% | 24 Mar → | ||
| 13–6 | 0.05 | 20% | 23 Mar → | ||
| 9–13 | 0.01 | 20% | 23 Mar → | ||
| 5–13 | -0.01 | 41% | 22 Mar → | ||
| 13–10 | 0.02 | 40% | 22 Mar → | ||
| 6–13 | -0.05 | 47% | 22 Mar → | ||
| 10–13 | -0.03 | 21% | 14 Mar → | ||
| 8–13 | -0.03 | 28% | 14 Mar → | ||
| 6–13 | -0.04 | 12% | 13 Mar → | ||
| 16–12 | 0.03 | 19% | 12 Mar → | ||
| 9–13 | -0.04 | 17% | 11 Mar → | ||
| 13–9 | 0.10 | 18% | 11 Mar → | ||
| 13–10 | -0.03 | 39% | 11 Mar → | ||
| 13–9 | 0.06 | 26% | 10 Mar → | ||
| 7–13 | -0.05 | 47% | 9 Mar → | ||
| 8–13 | -0.02 | 20% | 9 Mar → | ||
| 13–2 | 0.04 | 38% | 9 Mar → | ||
| 10–13 | -0.00 | 23% | 7 Mar → | ||
| 10–3 | 0.09 | 21% | 7 Mar → | ||
| 4–13 | -0.07 | 21% | 6 Mar → | ||
| 13–11 | 0.05 | 23% | 6 Mar → | ||
| 13–10 | 0.03 | 21% | 24 Feb → | ||
| 6–13 | 0.04 | 30% | 23 Feb → | ||
| 7–13 | -0.04 | 12% | 22 Feb → | ||
| 12–12 | 0.05 | 24% | 22 Feb → | ||
| 10–13 | -0.01 | 22% | 21 Feb → | ||
| 9–13 | -0.00 | 17% | 19 Feb → | ||
| 6–13 | -0.05 | 22% | 18 Feb → | ||
| 6–13 | -0.07 | 18% | 15 Feb → | ||
| 13–11 | -0.01 | 15% | 14 Feb → | ||
| 13–8 | -0.01 | 16% | 14 Feb → | ||
| 13–6 | 0.02 | 11% | 14 Feb → | ||
| 13–9 | 0.08 | 17% | 13 Feb → | ||
| 9–13 | -0.03 | 21% | 13 Feb → | ||
| 10–13 | 0.02 | 22% | 12 Feb → | ||
| 13–3 | 0.03 | 19% | 12 Feb → | ||
| 13–10 | -0.00 | 33% | 7 Feb → | ||
| 15–15 | 0.02 | 22% | 7 Feb → | ||
| 13–4 | 0.04 | 12% | 6 Feb → | ||
| 8–13 | -0.03 | 28% | 4 Feb → | ||
| 11–13 | -0.04 | 14% | 2 Feb → | ||
| warden | 13–7 | 0.06 | 31% | 1 Feb → | |
| 7–3 | -0.00 | 47% | 1 Feb → | ||
| stronghold | 8–13 | -0.01 | 19% | 1 Feb → | |
| 13–11 | -0.03 | 27% | 30 Jan → | ||
| 6–13 | -0.02 | 27% | 29 Jan → | ||
| 7–13 | 0.03 | 19% | 29 Jan → |
Match data via Leetify.