Donkeykong — CS2 Stats
76561197994297406[U:1:34031678]
How this compares with the same rank
Median values for Level 8 among CSDB-tracked players (n=1,146), 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 | Level 8 median | Level 9 median | vs Level 9 |
|---|---|---|---|---|
| Headshot rate | 46.7% | 47.2% | 49.0% | 2.3% short |
| Shot accuracy | 15.7% | 12.3% | 13.1% | above |
| Kill/death ratio | 0.96 | 1.07 | 1.08 | 0.12 short |
| Match win rate | 46.9% | 46.3% | 46.9% | meets |
This profile matches the typical Level 9 player on 2 of 4 comparable metrics.
Widest gap: Kill/death ratio. That is the metric furthest from the Level 9 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: -40pp win rate · -0.04 avg rating
Player DNA
Primary style: Passive Rifler — Aim-led profile without a single dominant tendency.
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 NiKo 84% playstyle similarity
Most alike: utility contribution, opening-fight frequency.
Where you differ: lower aim profile; 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
Areas to improve
Positioning. Positioning trails aim by 35 points — deaths here waste a strong aim profile.
Reaction time. 602ms 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 5.3/10 (Developing), 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 |
|---|---|---|---|---|---|
| D | 24 | 6–18 | 25% | -0.03 | |
| C | 16 | 7–9 | 44% | -0.00 | |
| D | 15 | 5–10 | 33% | -0.02 | |
| S | 12 | 9–3 | 75% | 0.00 | |
| S | 11 | 10–1 | 91% | 0.01 | |
| S | 10 | 7–3 | 70% | -0.02 | |
| C | 9 | 4–5 | 44% | -0.03 | |
| — | 3 | 3–0 | 100% | 0.00 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (25% over 24). 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.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWLLLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Inferno | 157 | 55% | 1.04 | 14.4 |
| Nuke | 122 | 59% | 0.94 | 13.7 |
| Vertigo | 113 | 50% | 0.91 | 14.0 |
| Mirage | 101 | 42% | 0.79 | 13.0 |
| Ancient | 93 | 44% | 0.92 | 13.6 |
| Anubis | 34 | 50% | 0.86 | 12.5 |
| Dust2 | 26 | 38% | 0.78 | 12.7 |
| Overpass | 13 | 62% | 1.06 | 17.5 |
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.
- 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 37.0907% — 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.
25% win rate across 24 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 10–13 | -0.06 | 6% | 22 Aug → | ||
| 11–13 | -0.06 | 17% | 22 Aug → | ||
| 13–10 | 0.01 | 22% | 22 Aug → | ||
| 13–6 | 0.03 | 21% | 22 Aug → | ||
| 13–16 | -0.03 | 14% | 22 Aug → | ||
| 12–16 | 0.02 | 15% | 22 Aug → | ||
| 6–13 | -0.01 | 14% | 19 Aug → | ||
| 13–11 | 0.01 | 29% | 19 Aug → | ||
| 13–6 | -0.01 | 22% | 19 Aug → | ||
| 12–16 | -0.01 | 31% | 17 Aug → | ||
| 3–13 | -0.06 | 17% | 17 Aug → | ||
| 13–3 | -0.03 | 4% | 17 Aug → | ||
| 13–8 | 0.08 | 33% | 17 Aug → | ||
| 8–13 | 0.03 | 33% | 15 Aug → | ||
| 13–8 | 0.01 | 43% | 15 Aug → | ||
| 13–7 | 0.12 | 35% | 15 Aug → | ||
| 13–8 | -0.03 | 32% | 15 Aug → | ||
| 13–6 | -0.00 | 30% | 15 Aug → | ||
| 13–8 | 0.05 | 17% | 14 Aug → | ||
| 13–1 | 0.12 | 16% | 14 Aug → | ||
| 8–13 | -0.05 | 14% | 14 Aug → | ||
| 11–13 | -0.03 | 24% | 14 Aug → | ||
| 13–2 | 0.04 | 24% | 14 Aug → | ||
| 13–10 | -0.03 | 24% | 14 Aug → | ||
| 13–16 | -0.00 | 20% | 14 Aug → | ||
| 13–1 | 0.03 | 24% | 13 Aug → | ||
| 13–10 | 0.00 | 17% | 13 Aug → | ||
| 13–1 | 0.02 | 35% | 13 Aug → | ||
| 8–13 | -0.03 | 10% | 13 Aug → | ||
| 10–13 | -0.06 | 28% | 13 Aug → | ||
| 11–13 | -0.01 | 31% | 10 Aug → | ||
| 6–13 | -0.11 | 35% | 10 Aug → | ||
| 13–10 | -0.09 | 21% | 10 Aug → | ||
| 13–11 | -0.05 | 18% | 10 Aug → | ||
| 2–13 | -0.06 | 19% | 10 Aug → | ||
| 13–10 | -0.00 | 15% | 9 Aug → | ||
| 13–5 | -0.05 | 14% | 9 Aug → | ||
| 8–13 | 0.01 | 9% | 9 Aug → | ||
| 13–10 | -0.03 | 21% | 9 Aug → | ||
| 15–15 | -0.04 | 21% | 8 Aug → | ||
| 13–11 | 0.02 | 26% | 8 Aug → | ||
| 13–3 | -0.07 | 35% | 8 Aug → | ||
| 13–8 | 0.08 | 17% | 8 Aug → | ||
| 13–6 | 0.02 | 30% | 8 Aug → | ||
| 15–15 | -0.03 | 21% | 7 Aug → | ||
| 9–13 | -0.05 | 19% | 7 Aug → | ||
| 5–13 | -0.07 | 23% | 7 Aug → | ||
| 13–5 | 0.02 | 31% | 7 Aug → | ||
| 13–8 | 0.01 | 17% | 7 Aug → | ||
| 6–13 | -0.03 | 27% | 7 Aug → | ||
| 8–13 | -0.04 | 18% | 1 Aug → | ||
| 13–16 | -0.09 | 10% | 1 Aug → | ||
| 3–13 | -0.05 | 11% | 1 Aug → | ||
| 13–9 | 0.03 | 34% | 1 Aug → | ||
| 13–7 | 0.04 | 43% | 1 Aug → | ||
| 13–3 | 0.07 | 23% | 1 Aug → | ||
| 8–13 | -0.11 | 22% | 1 Aug → | ||
| 16–13 | -0.02 | 28% | 1 Aug → | ||
| 2–7 | -0.02 | 14% | 1 Aug → | ||
| 5–13 | -0.01 | 10% | 31 Jul → | ||
| 13–9 | 0.02 | 23% | 31 Jul → | ||
| 3–13 | -0.08 | 20% | 31 Jul → | ||
| 13–11 | -0.01 | 13% | 31 Jul → | ||
| 10–13 | 0.03 | 18% | 31 Jul → | ||
| 13–7 | -0.00 | 23% | 31 Jul → | ||
| 13–2 | 0.03 | 12% | 31 Jul → | ||
| 9–13 | -0.03 | 15% | 31 Jul → | ||
| 7–13 | -0.03 | 41% | 31 Jul → | ||
| 13–11 | -0.03 | 23% | 18 Jul → | ||
| 13–4 | 0.10 | 17% | 18 Jul → | ||
| 8–13 | -0.10 | 16% | 18 Jul → | ||
| 13–16 | -0.07 | 25% | 18 Jul → | ||
| 4–13 | -0.05 | 28% | 18 Jul → | ||
| 16–13 | -0.02 | 22% | 18 Jul → | ||
| 13–7 | 0.01 | 22% | 18 Jul → | ||
| 12–16 | -0.04 | 25% | 11 Jul → | ||
| 2–13 | -0.02 | 23% | 11 Jul → | ||
| 11–13 | -0.02 | 23% | 10 Jul → | ||
| 13–9 | -0.01 | 25% | 10 Jul → | ||
| 13–11 | -0.04 | 17% | 10 Jul → | ||
| 13–4 | 0.03 | 24% | 10 Jul → | ||
| 13–4 | 0.03 | 21% | 10 Jul → | ||
| 7–13 | 0.01 | 10% | 4 Jul → | ||
| 11–13 | -0.03 | 17% | 4 Jul → | ||
| 2–13 | -0.03 | 10% | 4 Jul → | ||
| 11–13 | -0.10 | 13% | 4 Jul → | ||
| 0–13 | -0.06 | 32% | 4 Jul → | ||
| 10–13 | 0.01 | 33% | 4 Jul → | ||
| 13–6 | -0.05 | 10% | 4 Jul → | ||
| 13–8 | -0.04 | 24% | 4 Jul → | ||
| 11–13 | -0.09 | 14% | 4 Jul → | ||
| 9–13 | -0.04 | 19% | 3 Jul → | ||
| 13–9 | -0.06 | 12% | 3 Jul → | ||
| 13–5 | 0.02 | 18% | 3 Jul → | ||
| 10–13 | -0.01 | 23% | 3 Jul → | ||
| 13–11 | -0.04 | 19% | 3 Jul → | ||
| 11–13 | -0.02 | 19% | 3 Jul → | ||
| 13–2 | 0.09 | 16% | 3 Jul → | ||
| 10–13 | -0.00 | 24% | 3 Jul → | ||
| 13–11 | -0.02 | 21% | 3 Jul → |
Match data via Leetify.