BANKAI — CS2 Stats
76561199523098741[U:1:1562833013]
How this compares with the same rank
Median values for Blue band among CSDB-tracked players (n=1,240), 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 | Blue band median | Purple band median | vs Purple band |
|---|---|---|---|---|
| Headshot rate | 46.7% | 41.7% | 44.1% | above |
| Shot accuracy | 2.7% | 8.8% | 11.4% | 8.7% short |
| Kill/death ratio | 1.35 | 0.97 | 1.03 | above |
| Match win rate | 46.6% | 43.8% | 45.2% | above |
This profile matches the typical Purple band player on 3 of 4 comparable metrics.
Widest gap: Shot accuracy. That is the metric furthest from the Purple 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 · -0.02 avg rating
Player DNA
Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.
Strong CT-side openerLimited 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 s1mple 85% playstyle similarity
Most alike: opening-fight frequency, positioning profile.
Where you differ: lower aim profile; lower utility contribution.
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
CT openings. 73% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
T-side openings. Opening success drops from 73% on CT to 49% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 569ms 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 6.0/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 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 |
|---|---|---|---|---|---|
| S | 32 | 21–11 | 66% | 0.10 | |
| D | 20 | 6–14 | 30% | 0.05 | |
| S | 11 | 8–3 | 73% | 0.11 | |
| D | 9 | 3–6 | 33% | 0.06 | |
| A | 9 | 5–4 | 56% | 0.07 | |
| C | 5 | 2–3 | 40% | 0.06 | |
| C | 5 | 2–3 | 40% | 0.05 | |
| — | 3 | 0–3 | 0% | 0.02 | |
| — | 2 | 2–0 | 100% | 0.06 | |
| warden | — | 2 | 0–2 | 0% | 0.06 |
| alpine | — | 1 | 0–1 | 0% | -0.03 |
| italy | — | 1 | 0–1 | 0% | 0.10 |
Across the last 100 tracked matches.
Mirage is currently your weakest sufficiently-sampled map (30% over 20). Start with the 6 essential Mirage 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.
- 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 0.4158 — 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.
30% win rate across 20 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 1–13 | -0.05 | 5% | 28 Aug → | ||
| 7–13 | 0.02 | 12% | 28 Aug → | ||
| 13–8 | 0.08 | 33% | 23 Aug → | ||
| 9–13 | 0.02 | 12% | 23 Aug → | ||
| 13–6 | 0.17 | 19% | 23 Aug → | ||
| 13–11 | 0.14 | 18% | 23 Aug → | ||
| 15–15 | 0.00 | 18% | 14 Aug → | ||
| 13–9 | 0.09 | 30% | 14 Aug → | ||
| 13–8 | 0.15 | 21% | 10 Aug → | ||
| 4–13 | -0.00 | 18% | 10 Aug → | ||
| 13–9 | 0.10 | 21% | 9 Aug → | ||
| 13–6 | 0.04 | 12% | 9 Aug → | ||
| 10–13 | 0.03 | 12% | 9 Aug → | ||
| 13–3 | 0.10 | 33% | 9 Aug → | ||
| 13–5 | 0.15 | 26% | 9 Aug → | ||
| 11–13 | 0.14 | 18% | 8 Aug → | ||
| 5–13 | 0.05 | 22% | 8 Aug → | ||
| 13–7 | 0.14 | 20% | 8 Aug → | ||
| 13–9 | 0.05 | 19% | 7 Aug → | ||
| 11–13 | 0.06 | 24% | 7 Aug → | ||
| 11–13 | 0.03 | 29% | 2 Aug → | ||
| 13–11 | 0.05 | 15% | 2 Aug → | ||
| 9–13 | -0.01 | 30% | 18 Jul → | ||
| 13–16 | 0.14 | 21% | 10 Jul → | ||
| 4–13 | -0.03 | 32% | 10 Jul → | ||
| 13–9 | 0.09 | 25% | 10 Jul → | ||
| 13–2 | 0.20 | 24% | 6 Jul → | ||
| 11–13 | -0.02 | 19% | 4 Jul → | ||
| 13–6 | 0.00 | 21% | 1 Jul → | ||
| 6–13 | 0.04 | 20% | 27 Jun → | ||
| 5–13 | 0.06 | 16% | 22 Jun → | ||
| 13–3 | 0.23 | 15% | 22 Jun → | ||
| 13–2 | 0.09 | 17% | 13 Jun → | ||
| 8–13 | 0.00 | 14% | 13 Jun → | ||
| 11–13 | 0.02 | 18% | 10 Jun → | ||
| 13–1 | 0.18 | 13% | 7 Jun → | ||
| 14–16 | 0.04 | 21% | 7 Jun → | ||
| 13–7 | 0.07 | 25% | 7 Jun → | ||
| 13–7 | 0.10 | 20% | 7 Jun → | ||
| 10–13 | 0.04 | 16% | 6 Jun → | ||
| 13–7 | 0.25 | 30% | 6 Jun → | ||
| 4–13 | 0.06 | 22% | 31 May → | ||
| 13–16 | 0.12 | 16% | 31 May → | ||
| 15–15 | 0.06 | 23% | 30 May → | ||
| 13–4 | -0.01 | 35% | 2 May → | ||
| 12–12 | 0.17 | 24% | 2 May → | ||
| 11–13 | 0.09 | 18% | 25 Apr → | ||
| 13–7 | 0.10 | 18% | 25 Apr → | ||
| 3–13 | 0.01 | 17% | 25 Apr → | ||
| 6–13 | 0.02 | 22% | 5 Apr → | ||
| 6–13 | 0.17 | 25% | 5 Apr → | ||
| 2–13 | 0.08 | 20% | 5 Apr → | ||
| 13–3 | 0.08 | 29% | 4 Apr → | ||
| 6–13 | -0.00 | 18% | 3 Apr → | ||
| 16–14 | 0.02 | 7% | 28 Mar → | ||
| 13–3 | 0.09 | 24% | 28 Mar → | ||
| 10–13 | 0.04 | 18% | 28 Mar → | ||
| 15–15 | 0.15 | 18% | 18 Mar → | ||
| 13–11 | 0.12 | 19% | 18 Mar → | ||
| 13–11 | 0.07 | 18% | 16 Mar → | ||
| 13–8 | 0.03 | 25% | 16 Mar → | ||
| warden | 6–13 | 0.08 | 23% | 14 Mar → | |
| 4–13 | 0.05 | 16% | 9 Mar → | ||
| 7–13 | 0.05 | 21% | 9 Mar → | ||
| 13–11 | 0.05 | 20% | 8 Mar → | ||
| 16–13 | 0.13 | 27% | 7 Mar → | ||
| 8–13 | 0.16 | 11% | 6 Mar → | ||
| 13–11 | 0.10 | 12% | 6 Mar → | ||
| 8–13 | 0.08 | 13% | 6 Mar → | ||
| 4–13 | 0.02 | 19% | 6 Mar → | ||
| 8–13 | 0.00 | 16% | 1 Mar → | ||
| 13–8 | 0.01 | 22% | 1 Mar → | ||
| 13–10 | 0.07 | 15% | 1 Mar → | ||
| 13–10 | 0.10 | 27% | 1 Mar → | ||
| 5–13 | 0.15 | 25% | 28 Feb → | ||
| 13–6 | 0.09 | 21% | 26 Feb → | ||
| 13–8 | 0.10 | 17% | 26 Feb → | ||
| 13–4 | 0.09 | 15% | 21 Feb → | ||
| 13–7 | 0.12 | 17% | 20 Feb → | ||
| 15–15 | 0.01 | 15% | 20 Feb → | ||
| 13–11 | 0.08 | 12% | 14 Feb → | ||
| 13–7 | 0.08 | 22% | 14 Feb → | ||
| 13–6 | 0.10 | 28% | 7 Feb → | ||
| 10–3 | 0.05 | 13% | 7 Feb → | ||
| alpine | 4–13 | -0.03 | 12% | 2 Feb → | |
| 9–13 | 0.00 | 21% | 2 Feb → | ||
| italy | 9–13 | 0.10 | 17% | 2 Feb → | |
| warden | 9–13 | 0.04 | 26% | 2 Feb → | |
| 13–10 | 0.13 | 29% | 13 Jan → | ||
| 13–1 | 0.05 | 10% | 13 Jan → | ||
| 13–2 | 0.14 | 18% | 13 Jan → | ||
| 2–13 | -0.00 | 20% | 13 Jan → | ||
| 16–13 | 0.04 | 18% | 12 Jan → | ||
| 8–13 | 0.16 | 14% | 9 Jan → | ||
| 8–13 | 0.09 | 27% | 9 Jan → | ||
| 5–13 | 0.06 | 21% | 9 Jan → | ||
| 11–13 | 0.12 | 26% | 9 Jan → | ||
| 8–13 | -0.00 | 14% | 3 Jan → | ||
| 13–0 | 0.04 | 83% | 3 Jan → | ||
| 13–0 | 0.12 | 90% | 3 Jan → |
Match data via Leetify.