Digita — CS2 Stats
DK76561198183273927[U:1:223008199]Steam profile ↗
How this compares with the same rank
Median values for Blue band among CSDB-tracked players (n=2,468), 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 | 57.2% | 41.4% | 44.2% | above |
| Shot accuracy | 22.0% | 9.0% | 11.6% | above |
| Kill/death ratio | 0.95 | 0.97 | 1.03 | 0.08 short |
| Match win rate | 43.7% | 43.7% | 45.2% | 1.5% short |
This profile matches the typical Purple band player on 2 of 4 comparable metrics.
Widest gap: Kill/death ratio. 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: +60pp win rate · +0.06 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
Strong 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 iM 94% playstyle similarity
Most alike: utility contribution, opening-duel success.
Where you differ: higher opening-fight frequency.
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. 61% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
Areas to improve
T-side openings. Opening success drops from 61% on CT to 36% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 588ms 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 6.4/10 (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 |
|---|---|---|---|---|---|
| A | 22 | 12–10 | 55% | 0.01 | |
| B | 19 | 9–10 | 47% | 0.01 | |
| D | 19 | 6–13 | 32% | 0.01 | |
| B | 11 | 5–6 | 45% | -0.00 | |
| D | 10 | 3–7 | 30% | -0.02 | |
| B | 6 | 3–3 | 50% | 0.02 | |
| S | 6 | 4–2 | 67% | 0.02 | |
| C | 5 | 2–3 | 40% | -0.01 | |
| — | 2 | 1–1 | 50% | 0.13 |
Across the last 100 tracked matches.
Ancient is currently your weakest sufficiently-sampled map (30% over 10). Start with the 6 essential Ancient 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 36.1264% — 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.
30% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–5 | 0.04 | 14% | 29 Aug → | ||
| 8–13 | -0.04 | 24% | 29 Aug → | ||
| 13–11 | 0.05 | 18% | 28 Aug → | ||
| 13–8 | 0.06 | 14% | 28 Aug → | ||
| 13–4 | 0.08 | 9% | 16 Aug → | ||
| 13–2 | 0.14 | 21% | 16 Aug → | ||
| 13–1 | 0.01 | 12% | 15 Aug → | ||
| 10–13 | 0.03 | 20% | 15 Aug → | ||
| 7–13 | 0.07 | 26% | 15 Aug → | ||
| 13–5 | 0.04 | 19% | 15 Aug → | ||
| 6–13 | 0.06 | 9% | 14 Aug → | ||
| 5–13 | -0.01 | 12% | 13 Aug → | ||
| 6–13 | -0.03 | 17% | 11 Aug → | ||
| 13–16 | -0.02 | 19% | 11 Aug → | ||
| 7–13 | -0.02 | 31% | 11 Aug → | ||
| 7–13 | -0.06 | 15% | 8 Aug → | ||
| 4–13 | 0.00 | 30% | 29 Jun → | ||
| 13–4 | 0.03 | 14% | 29 Jun → | ||
| 8–8 | -0.04 | 8% | 29 Jun → | ||
| 10–13 | -0.00 | 21% | 29 Jun → | ||
| 7–13 | -0.03 | 12% | 29 Jun → | ||
| 13–8 | 0.02 | 17% | 28 Jun → | ||
| 9–13 | 0.00 | 19% | 28 Jun → | ||
| 7–13 | 0.10 | 20% | 27 Jun → | ||
| 7–0 | 0.01 | 18% | 27 Jun → | ||
| 13–10 | 0.10 | 36% | 27 Jun → | ||
| 11–13 | 0.06 | 16% | 27 Jun → | ||
| 13–5 | 0.03 | 11% | 27 Jun → | ||
| 13–11 | 0.00 | 13% | 26 Jun → | ||
| 13–10 | -0.03 | 25% | 26 Jun → | ||
| 13–11 | 0.06 | 14% | 25 Jun → | ||
| 11–13 | 0.08 | 14% | 25 Jun → | ||
| 13–5 | 0.09 | 26% | 25 Jun → | ||
| 13–7 | -0.00 | 14% | 25 Jun → | ||
| 16–13 | 0.00 | 13% | 25 Jun → | ||
| 13–3 | -0.07 | 17% | 25 Jun → | ||
| 5–13 | 0.06 | 15% | 25 Jun → | ||
| 7–13 | -0.06 | 4% | 24 Jun → | ||
| 12–16 | -0.00 | 14% | 24 Jun → | ||
| 13–7 | 0.08 | 22% | 24 Jun → | ||
| 10–13 | -0.01 | 11% | 24 Jun → | ||
| 13–9 | 0.07 | 13% | 24 Jun → | ||
| 11–3 | 0.07 | 16% | 23 Jun → | ||
| 8–13 | -0.03 | 17% | 23 Jun → | ||
| 8–13 | -0.08 | 22% | 23 Jun → | ||
| 13–8 | -0.01 | 11% | 22 Jun → | ||
| 2–13 | -0.10 | 17% | 22 Jun → | ||
| 9–13 | 0.10 | 20% | 22 Jun → | ||
| 4–13 | -0.05 | 14% | 22 Jun → | ||
| 10–13 | 0.02 | 11% | 22 Jun → | ||
| 13–10 | -0.02 | 8% | 22 Jun → | ||
| 1–13 | -0.05 | 14% | 22 Jun → | ||
| 7–13 | -0.09 | 10% | 22 Jun → | ||
| 13–9 | 0.03 | 35% | 22 Jun → | ||
| 13–6 | 0.00 | 10% | 22 Jun → | ||
| 8–13 | 0.02 | 13% | 21 Jun → | ||
| 9–13 | -0.05 | 28% | 21 Jun → | ||
| 13–10 | -0.03 | 15% | 21 Jun → | ||
| 10–13 | 0.01 | 18% | 19 Jun → | ||
| 6–13 | 0.00 | 22% | 19 Jun → | ||
| 13–7 | 0.02 | 16% | 19 Jun → | ||
| 11–13 | -0.03 | 19% | 19 Jun → | ||
| 10–13 | -0.03 | 17% | 19 Jun → | ||
| 13–11 | 0.03 | 19% | 19 Jun → | ||
| 13–5 | -0.01 | 12% | 17 Jun → | ||
| 4–13 | -0.01 | 13% | 16 Jun → | ||
| 9–13 | -0.04 | 20% | 16 Jun → | ||
| 13–4 | 0.02 | 5% | 14 Jun → | ||
| 10–13 | 0.01 | 20% | 14 Jun → | ||
| 13–7 | 0.03 | 20% | 13 Jun → | ||
| 6–13 | -0.05 | 8% | 13 Jun → | ||
| 10–13 | 0.03 | 31% | 12 Jun → | ||
| 13–10 | 0.00 | 9% | 12 Jun → | ||
| 13–11 | -0.10 | 9% | 12 Jun → | ||
| 13–11 | -0.01 | 14% | 12 Jun → | ||
| 10–13 | -0.07 | 11% | 12 Jun → | ||
| 6–13 | 0.02 | 18% | 12 Jun → | ||
| 13–10 | 0.00 | 21% | 11 Jun → | ||
| 13–9 | -0.07 | 10% | 11 Jun → | ||
| 10–13 | -0.03 | 13% | 11 Jun → | ||
| 13–3 | 0.04 | 24% | 11 Jun → | ||
| 4–0 | 0.03 | 19% | 30 May → | ||
| 5–13 | 0.04 | 17% | 30 May → | ||
| 10–13 | -0.07 | 11% | 11 May → | ||
| 2–13 | -0.08 | 12% | 11 May → | ||
| 9–6 | 0.10 | 32% | 11 May → | ||
| 6–13 | 0.05 | 15% | 10 May → | ||
| 13–5 | -0.01 | 20% | 9 May → | ||
| 15–15 | -0.01 | 11% | 9 May → | ||
| 9–13 | 0.04 | 14% | 9 May → | ||
| 9–13 | -0.01 | 22% | 9 May → | ||
| 14–16 | -0.02 | 15% | 9 May → | ||
| 12–12 | 0.17 | 11% | 8 May → | ||
| 16–14 | 0.01 | 8% | 8 May → | ||
| 13–2 | 0.07 | 11% | 6 May → | ||
| 8–13 | 0.01 | 10% | 6 May → | ||
| 13–16 | 0.02 | 15% | 6 May → | ||
| 8–13 | 0.01 | 32% | 6 May → | ||
| 13–4 | 0.10 | 17% | 4 May → | ||
| 16–14 | 0.01 | 15% | 4 May → |
Match data via Leetify.