Cardamomo Enemenergumenono — CS2 Stats
MX76561198090456449[U:1:130190721]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Purple band among CSDB-tracked players (n=5,002), 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 | Purple band median | Pink band median | vs Pink band |
|---|---|---|---|---|
| Headshot rate | 39.9% | 44.2% | 47.1% | 7.2% short |
| Shot accuracy | 11.9% | 11.6% | 12.8% | 0.9% short |
| Kill/death ratio | 0.71 | 1.03 | 1.08 | 0.37 short |
| Match win rate | 33.5% | 45.2% | 46.6% | 13.1% short |
This profile sits below the typical Pink band player on every metric we can compare.
Widest gap: Kill/death ratio. That is the metric furthest from the Pink 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: -20pp win rate · -0.02 avg rating
Player DNA
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 64% playstyle similarity
Most alike: utility contribution, opening-duel success.
Where you differ: lower aim profile; lower 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
Areas to improve
Reaction time. 640ms 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 4.3/10 (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 |
|---|---|---|---|---|---|
| A | 37 | 22–15 | 59% | -0.04 | |
| C | 23 | 10–13 | 43% | -0.04 | |
| A | 10 | 6–4 | 60% | -0.02 | |
| B | 10 | 5–5 | 50% | -0.03 | |
| A | 5 | 3–2 | 60% | -0.05 | |
| — | 4 | 2–2 | 50% | -0.03 | |
| — | 3 | 1–2 | 33% | -0.01 | |
| office | — | 3 | 0–3 | 0% | -0.07 |
| — | 2 | 0–2 | 0% | -0.07 | |
| debris | — | 1 | 0–1 | 0% | -0.17 |
| — | 1 | 1–0 | 100% | 0.07 | |
| italy | — | 1 | 1–0 | 100% | 0.07 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (43% over 23). 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 resultsLLLLL
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 →
Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.
Enemies flashed per flash 0.3871 — below the 0.5 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 20.6574% — 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.
43% win rate across 23 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 9–7 | 0.03 | 13% | 12 Aug → | ||
| 2–9 | -0.19 | 18% | 12 Aug → | ||
| debris | 4–9 | -0.17 | 0% | 12 Aug → | |
| 13–6 | -0.02 | 8% | 12 Aug → | ||
| 4–13 | -0.07 | 13% | 12 Aug → | ||
| 13–3 | -0.02 | 16% | 8 Aug → | ||
| 8–13 | -0.02 | 22% | 8 Aug → | ||
| 10–13 | -0.04 | 19% | 8 Aug → | ||
| 13–6 | -0.02 | 19% | 8 Aug → | ||
| 7–13 | -0.07 | 22% | 7 Aug → | ||
| 13–6 | -0.04 | 11% | 7 Aug → | ||
| 13–11 | -0.04 | 17% | 7 Aug → | ||
| 7–13 | -0.06 | 17% | 31 Jul → | ||
| 2–13 | -0.07 | 26% | 31 Jul → | ||
| 10–13 | -0.05 | 16% | 30 Jul → | ||
| 13–11 | -0.04 | 5% | 30 Jul → | ||
| 12–3 | -0.06 | 11% | 30 Jul → | ||
| 16–13 | -0.05 | 16% | 30 Jul → | ||
| 13–8 | -0.02 | 19% | 25 Jul → | ||
| 15–15 | -0.03 | 24% | 25 Jul → | ||
| 13–3 | -0.05 | 12% | 25 Jul → | ||
| 13–5 | 0.01 | 13% | 25 Jul → | ||
| 10–13 | 0.05 | 16% | 25 Jul → | ||
| 8–13 | -0.01 | 20% | 25 Jul → | ||
| 8–13 | -0.03 | 10% | 25 Jul → | ||
| 13–1 | -0.03 | 17% | 24 Jul → | ||
| 13–6 | 0.02 | 10% | 24 Jul → | ||
| 7–13 | -0.05 | 16% | 24 Jul → | ||
| 13–10 | 0.02 | 16% | 23 Jul → | ||
| 16–14 | -0.01 | 21% | 23 Jul → | ||
| 13–3 | 0.07 | 9% | 23 Jul → | ||
| 6–13 | -0.08 | 13% | 21 Jul → | ||
| 13–9 | -0.05 | 7% | 21 Jul → | ||
| 7–13 | -0.06 | 18% | 21 Jul → | ||
| 13–7 | -0.04 | 22% | 21 Jul → | ||
| 13–11 | -0.08 | 20% | 21 Jul → | ||
| 13–10 | -0.02 | 15% | 20 Jul → | ||
| 16–13 | -0.02 | 25% | 20 Jul → | ||
| 9–3 | -0.01 | 21% | 20 Jul → | ||
| 12–16 | -0.06 | 13% | 5 Jul → | ||
| 13–6 | -0.04 | 4% | 5 Jul → | ||
| 6–13 | -0.00 | 25% | 5 Jul → | ||
| 9–3 | 0.07 | 15% | 5 Jul → | ||
| 3–9 | -0.02 | 23% | 5 Jul → | ||
| 13–10 | -0.02 | 41% | 26 Jun → | ||
| 13–5 | 0.02 | 13% | 26 Jun → | ||
| 13–11 | -0.01 | 4% | 26 Jun → | ||
| 8–13 | -0.04 | 21% | 25 Jun → | ||
| 16–14 | -0.04 | 14% | 25 Jun → | ||
| 4–13 | -0.07 | 23% | 8 Jun → | ||
| 4–13 | -0.07 | 3% | 8 Jun → | ||
| 13–7 | -0.03 | 15% | 8 Jun → | ||
| 11–13 | -0.15 | 10% | 8 Jun → | ||
| 13–9 | -0.07 | 21% | 2 Jun → | ||
| 8–13 | -0.10 | 21% | 1 Jun → | ||
| 13–6 | -0.03 | 19% | 1 Jun → | ||
| 3–13 | -0.09 | 18% | 30 Apr → | ||
| 16–14 | -0.06 | 17% | 10 Apr → | ||
| 8–2 | -0.08 | 33% | 10 Apr → | ||
| 3–13 | -0.06 | 6% | 10 Apr → | ||
| 9–13 | -0.02 | 10% | 10 Apr → | ||
| 15–15 | -0.03 | 12% | 10 Apr → | ||
| 3–13 | -0.09 | 11% | 9 Apr → | ||
| 13–10 | -0.02 | 19% | 1 Apr → | ||
| 11–13 | -0.07 | 24% | 1 Apr → | ||
| 8–13 | -0.09 | 21% | 1 Apr → | ||
| 15–15 | -0.06 | 14% | 31 Mar → | ||
| 13–11 | -0.04 | 16% | 31 Mar → | ||
| 7–13 | -0.06 | 15% | 31 Mar → | ||
| 13–11 | -0.03 | 13% | 31 Mar → | ||
| 13–7 | -0.07 | 19% | 31 Mar → | ||
| 13–4 | -0.01 | 6% | 30 Mar → | ||
| office | 4–13 | -0.07 | 45% | 30 Mar → | |
| 7–13 | 0.02 | 14% | 19 Mar → | ||
| 2–13 | -0.08 | 18% | 19 Mar → | ||
| 13–11 | -0.03 | 9% | 19 Mar → | ||
| office | 5–13 | -0.07 | 25% | 18 Mar → | |
| italy | 13–6 | 0.07 | 22% | 18 Mar → | |
| 13–8 | -0.03 | 11% | 13 Mar → | ||
| 13–6 | 0.04 | 15% | 13 Mar → | ||
| 13–16 | -0.01 | 13% | 13 Mar → | ||
| 7–13 | -0.05 | 22% | 13 Mar → | ||
| 16–14 | -0.01 | 16% | 12 Mar → | ||
| 7–2 | -0.04 | 30% | 12 Mar → | ||
| 10–13 | -0.04 | 22% | 7 Mar → | ||
| 10–13 | -0.03 | 10% | 4 Mar → | ||
| 13–11 | -0.04 | 18% | 4 Mar → | ||
| 14–16 | -0.00 | 17% | 4 Mar → | ||
| 13–7 | 0.06 | 15% | 4 Mar → | ||
| 16–13 | -0.02 | 14% | 3 Mar → | ||
| 14–16 | -0.09 | 12% | 3 Mar → | ||
| 13–11 | 0.03 | 26% | 3 Mar → | ||
| 3–13 | -0.10 | 0% | 2 Mar → | ||
| office | 9–13 | -0.07 | 17% | 2 Mar → | |
| 4–13 | -0.06 | 33% | 22 Feb → | ||
| 13–16 | -0.05 | 17% | 12 Feb → | ||
| 6–13 | -0.01 | 27% | 12 Feb → | ||
| 7–13 | -0.02 | 25% | 9 Feb → | ||
| 13–7 | 0.00 | 8% | 9 Feb → | ||
| 13–7 | -0.02 | 36% | 9 Feb → |
Match data via Leetify.
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