kachigga — CS2 Stats
CK76561198407348831[U:1:447083103]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Level 4 among CSDB-tracked players (n=928), 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 4 median | Level 5 median | vs Level 5 |
|---|---|---|---|---|
| Headshot rate | 38.9% | 42.5% | 44.2% | 5.3% short |
| Shot accuracy | 22.0% | 10.9% | 11.2% | above |
| Kill/death ratio | 1.07 | 0.99 | 1.04 | above |
| Match win rate | 44.9% | 44.2% | 45.3% | meets |
This profile matches the typical Level 5 player on 3 of 4 comparable metrics.
Widest gap: Headshot rate. That is the metric furthest from the Level 5 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 · +0.00 avg rating
Player DNA
Primary style: Hybrid 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 Twistzz 87% playstyle similarity
Most alike: opening-fight frequency, positioning profile.
Where you differ: lower utility contribution; 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. 582ms 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 5.1/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×1.00 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 | 28 | 20–8 | 71% | 0.01 | |
| C | 26 | 9–17 | 35% | -0.01 | |
| A | 18 | 10–8 | 56% | 0.01 | |
| C | 12 | 5–7 | 42% | 0.00 | |
| D | 8 | 2–6 | 25% | -0.00 | |
| B | 6 | 3–3 | 50% | 0.00 | |
| — | 1 | 0–1 | 0% | -0.06 | |
| — | 1 | 0–1 | 0% | 0.00 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (25% over 8). 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.
- Best CS2 CrosshairAim Training →
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 14.5097% — below the 15% mark we flag
- 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 37.5694% — 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 8 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 4–13 | -0.06 | 15% | 13 May → | ||
| 13–11 | -0.00 | 10% | 13 May → | ||
| 12–16 | -0.01 | 20% | 5 May → | ||
| 9–13 | 0.08 | 10% | 1 May → | ||
| 9–13 | -0.02 | 12% | 1 May → | ||
| 12–12 | 0.00 | 15% | 29 Apr → | ||
| 5–13 | -0.03 | 17% | 28 Apr → | ||
| 8–13 | -0.01 | 13% | 28 Apr → | ||
| 10–13 | -0.02 | 20% | 27 Apr → | ||
| 6–13 | 0.08 | 14% | 26 Apr → | ||
| 13–10 | 0.02 | 8% | 26 Apr → | ||
| 6–13 | 0.05 | 7% | 24 Apr → | ||
| 13–10 | 0.02 | 9% | 24 Apr → | ||
| 5–13 | -0.10 | 22% | 22 Apr → | ||
| 13–7 | 0.11 | 20% | 21 Apr → | ||
| 13–11 | -0.03 | 16% | 21 Apr → | ||
| 13–5 | 0.07 | 11% | 20 Apr → | ||
| 7–13 | -0.02 | 20% | 20 Apr → | ||
| 8–13 | -0.10 | 8% | 20 Apr → | ||
| 7–13 | -0.01 | 21% | 19 Apr → | ||
| 2–13 | 0.00 | 15% | 17 Apr → | ||
| 13–10 | 0.00 | 16% | 17 Apr → | ||
| 7–13 | 0.03 | 12% | 17 Apr → | ||
| 10–13 | -0.02 | 12% | 16 Apr → | ||
| 4–13 | -0.05 | 17% | 16 Apr → | ||
| 13–7 | -0.02 | 13% | 15 Apr → | ||
| 13–9 | 0.07 | 20% | 14 Apr → | ||
| 13–11 | -0.04 | 5% | 13 Apr → | ||
| 2–13 | -0.10 | 27% | 13 Apr → | ||
| 13–8 | 0.05 | 17% | 11 Apr → | ||
| 13–6 | 0.00 | 12% | 10 Apr → | ||
| 13–4 | 0.05 | 15% | 10 Apr → | ||
| 4–13 | -0.02 | 34% | 9 Apr → | ||
| 13–11 | -0.02 | 13% | 9 Apr → | ||
| 12–16 | -0.05 | 16% | 9 Apr → | ||
| 16–12 | -0.03 | 11% | 8 Apr → | ||
| 13–11 | -0.04 | 21% | 8 Apr → | ||
| 13–6 | 0.05 | 13% | 8 Apr → | ||
| 4–13 | 0.05 | 26% | 7 Apr → | ||
| 13–11 | 0.02 | 22% | 7 Apr → | ||
| 5–13 | -0.00 | 24% | 6 Apr → | ||
| 6–13 | -0.02 | 18% | 6 Apr → | ||
| 11–13 | 0.02 | 12% | 3 Apr → | ||
| 16–12 | -0.00 | 14% | 2 Apr → | ||
| 13–9 | -0.01 | 19% | 2 Apr → | ||
| 12–2 | -0.01 | 11% | 1 Apr → | ||
| 7–13 | -0.01 | 20% | 1 Apr → | ||
| 13–10 | -0.03 | 11% | 1 Apr → | ||
| 6–13 | 0.01 | 18% | 1 Apr → | ||
| 13–9 | -0.01 | 8% | 31 Mar → | ||
| 7–0 | 0.03 | 12% | 31 Mar → | ||
| 13–6 | 0.10 | 21% | 30 Mar → | ||
| 7–13 | -0.01 | 19% | 30 Mar → | ||
| 16–14 | -0.02 | 15% | 29 Mar → | ||
| 13–4 | 0.02 | 9% | 29 Mar → | ||
| 4–13 | -0.09 | 11% | 27 Mar → | ||
| 13–8 | 0.04 | 15% | 27 Mar → | ||
| 13–9 | 0.09 | 13% | 27 Mar → | ||
| 13–7 | 0.02 | 12% | 25 Mar → | ||
| 7–13 | -0.03 | 25% | 25 Mar → | ||
| 13–5 | 0.06 | 17% | 25 Mar → | ||
| 14–16 | 0.05 | 15% | 24 Mar → | ||
| 9–13 | -0.01 | 7% | 24 Mar → | ||
| 13–8 | 0.05 | 11% | 24 Mar → | ||
| 10–13 | -0.03 | 11% | 23 Mar → | ||
| 16–13 | -0.01 | 16% | 23 Mar → | ||
| 9–13 | 0.01 | 16% | 20 Mar → | ||
| 14–16 | -0.01 | 13% | 20 Mar → | ||
| 11–13 | -0.08 | 21% | 20 Mar → | ||
| 7–13 | -0.04 | 12% | 19 Mar → | ||
| 16–14 | 0.13 | 15% | 19 Mar → | ||
| 13–3 | 0.04 | 16% | 18 Mar → | ||
| 8–13 | 0.03 | 20% | 17 Mar → | ||
| 13–8 | -0.05 | 13% | 17 Mar → | ||
| 13–10 | -0.01 | 10% | 17 Mar → | ||
| 13–10 | 0.03 | 20% | 17 Mar → | ||
| 10–13 | -0.01 | 17% | 16 Mar → | ||
| 13–1 | 0.04 | 8% | 16 Mar → | ||
| 13–7 | 0.04 | 13% | 14 Mar → | ||
| 5–13 | -0.05 | 16% | 14 Mar → | ||
| 13–6 | -0.01 | 18% | 13 Mar → | ||
| 15–15 | 0.01 | 9% | 13 Mar → | ||
| 13–4 | 0.05 | 11% | 13 Mar → | ||
| 1–13 | -0.06 | 17% | 12 Mar → | ||
| 13–9 | 0.06 | 20% | 12 Mar → | ||
| 5–13 | 0.05 | 9% | 11 Mar → | ||
| 16–14 | -0.03 | 13% | 11 Mar → | ||
| 5–13 | -0.03 | 16% | 11 Mar → | ||
| 8–13 | -0.00 | 19% | 10 Mar → | ||
| 13–5 | -0.01 | 10% | 10 Mar → | ||
| 13–16 | 0.02 | 10% | 10 Mar → | ||
| 7–13 | -0.05 | 14% | 9 Mar → | ||
| 16–13 | -0.02 | 16% | 9 Mar → | ||
| 15–15 | 0.02 | 15% | 8 Mar → | ||
| 13–11 | 0.05 | 11% | 8 Mar → | ||
| 13–7 | 0.11 | 25% | 8 Mar → | ||
| 9–13 | 0.01 | 26% | 7 Mar → | ||
| 9–13 | -0.02 | 13% | 6 Mar → | ||
| 11–13 | -0.03 | 11% | 6 Mar → | ||
| 13–10 | -0.06 | 13% | 6 Mar → |
Match data via Leetify.