KONGG — CS2 Stats
76561197982480387[U:1:22214659]
How this compares with the same rank
Median values for Pink band among CSDB-tracked players (n=201), 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 | Pink band median | vs Pink band |
|---|---|---|---|
| Headshot rate | 44.5% | 48.1% | 3.6% short |
| Shot accuracy | 16.0% | 12.9% | above |
| Kill/death ratio | 1.22 | 1.08 | above |
| Match win rate | 48.7% | 46.5% | above |
This profile matches the typical Pink band player on 3 of 4 comparable metrics.
Widest gap: Headshot rate. 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: -10pp win rate · -0.00 avg rating
Player DNA
Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.
Strong CT-side openerHigh utility contribution
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 91% playstyle similarity
Most alike: opening-fight frequency, utility contribution.
Where you differ: 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
Strengths
Utility. Utility score of 79 — grenade impact well above the norm.
Areas to improve
T-side openings. Opening success drops from 45% on CT to 24% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 626ms 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 6.1/10 (Solid), 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 |
|---|---|---|---|---|---|
| C | 25 | 11–14 | 44% | 0.04 | |
| D | 22 | 5–17 | 23% | 0.01 | |
| B | 17 | 9–8 | 53% | 0.03 | |
| C | 15 | 6–9 | 40% | 0.01 | |
| B | 10 | 5–5 | 50% | 0.01 | |
| S | 5 | 4–1 | 80% | 0.02 | |
| C | 5 | 2–3 | 40% | 0.08 | |
| — | 1 | 1–0 | 100% | 0.06 |
Across the last 100 tracked matches.
Ancient is currently your weakest sufficiently-sampled map (23% over 22). 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.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsLWLLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Ancient | 175 | 55% | 1.17 | 17.9 |
| Inferno | 171 | 54% | 1.30 | 18.4 |
| Anubis | 158 | 52% | 1.29 | 19.5 |
| Dust2 | 82 | 41% | 1.19 | 18.3 |
| Overpass | 55 | 58% | 1.41 | 20.6 |
| Train | 24 | 33% | 1.17 | 18.5 |
| Mirage | 22 | 32% | 1.09 | 13.6 |
| Nuke | 5 | 40% | 1.26 | 18.2 |
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 23.7675% — 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.
23% win rate across 22 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 1–13 | -0.05 | 58% | 14 Aug → | ||
| 11–13 | -0.01 | 33% | 14 Aug → | ||
| 8–1 | 0.02 | 22% | 14 Aug → | ||
| 13–9 | 0.01 | 27% | 12 Aug → | ||
| 13–9 | 0.07 | 47% | 12 Aug → | ||
| 9–13 | 0.07 | 24% | 12 Aug → | ||
| 13–6 | 0.01 | 16% | 12 Aug → | ||
| 10–13 | 0.01 | 16% | 8 Aug → | ||
| 13–5 | 0.07 | 16% | 8 Aug → | ||
| 10–13 | -0.00 | 18% | 8 Aug → | ||
| 13–11 | 0.03 | 29% | 8 Aug → | ||
| 9–13 | 0.07 | 26% | 8 Aug → | ||
| 13–10 | 0.02 | 29% | 8 Aug → | ||
| 16–12 | 0.08 | 26% | 8 Aug → | ||
| 13–9 | -0.05 | 10% | 7 Aug → | ||
| 16–13 | 0.04 | 20% | 7 Aug → | ||
| 9–13 | -0.01 | 11% | 6 Aug → | ||
| 13–10 | 0.06 | 21% | 1 Aug → | ||
| 4–13 | -0.02 | 28% | 1 Aug → | ||
| 5–13 | 0.00 | 44% | 31 Jul → | ||
| 1–13 | -0.07 | 9% | 25 Jul → | ||
| 6–13 | -0.04 | 11% | 25 Jul → | ||
| 6–13 | 0.14 | 24% | 24 Jul → | ||
| 12–16 | -0.01 | 24% | 24 Jul → | ||
| 9–13 | -0.03 | 20% | 24 Jul → | ||
| 11–13 | -0.03 | 11% | 24 Jul → | ||
| 13–3 | 0.04 | 16% | 24 Jul → | ||
| 9–13 | 0.01 | 26% | 23 Jul → | ||
| 8–13 | -0.01 | 20% | 23 Jul → | ||
| 13–11 | 0.03 | 23% | 23 Jul → | ||
| 9–13 | -0.04 | 19% | 23 Jul → | ||
| 13–16 | 0.00 | 16% | 22 Jul → | ||
| 2–13 | -0.05 | 22% | 22 Jul → | ||
| 10–13 | -0.02 | 14% | 22 Jul → | ||
| 13–4 | -0.02 | 25% | 22 Jul → | ||
| 13–6 | 0.04 | 6% | 21 Jul → | ||
| 13–7 | 0.02 | 24% | 21 Jul → | ||
| 16–12 | 0.11 | 24% | 21 Jul → | ||
| 7–13 | 0.02 | 32% | 20 Jul → | ||
| 5–13 | 0.06 | 27% | 20 Jul → | ||
| 13–8 | 0.06 | 29% | 20 Jul → | ||
| 13–11 | 0.03 | 12% | 20 Jul → | ||
| 13–10 | 0.00 | 26% | 20 Jul → | ||
| 10–13 | 0.02 | 15% | 20 Jul → | ||
| 11–13 | -0.01 | 18% | 18 Jul → | ||
| 13–11 | 0.06 | 16% | 18 Jul → | ||
| 13–9 | 0.02 | 23% | 18 Jul → | ||
| 13–5 | 0.04 | 16% | 18 Jul → | ||
| 13–6 | 0.03 | 18% | 18 Jul → | ||
| 13–5 | 0.08 | 27% | 16 Jul → | ||
| 5–13 | 0.02 | 28% | 16 Jul → | ||
| 16–14 | -0.03 | 13% | 16 Jul → | ||
| 11–13 | 0.03 | 14% | 16 Jul → | ||
| 5–13 | 0.03 | 29% | 16 Jul → | ||
| 13–10 | 0.04 | 26% | 11 Jul → | ||
| 15–15 | 0.06 | 17% | 11 Jul → | ||
| 11–13 | 0.03 | 27% | 11 Jul → | ||
| 13–3 | 0.05 | 14% | 11 Jul → | ||
| 9–13 | 0.03 | 20% | 11 Jul → | ||
| 10–13 | 0.00 | 24% | 10 Jul → | ||
| 13–6 | 0.08 | 41% | 10 Jul → | ||
| 5–13 | -0.01 | 26% | 9 Jul → | ||
| 13–9 | 0.08 | 16% | 9 Jul → | ||
| 5–13 | -0.06 | 10% | 9 Jul → | ||
| 15–15 | 0.05 | 24% | 9 Jul → | ||
| 15–15 | -0.01 | 17% | 4 Jul → | ||
| 11–13 | 0.06 | 20% | 4 Jul → | ||
| 11–13 | 0.01 | 11% | 3 Jul → | ||
| 13–9 | 0.03 | 21% | 3 Jul → | ||
| 13–6 | 0.03 | 24% | 2 Jul → | ||
| 11–13 | -0.01 | 19% | 30 Jun → | ||
| 16–14 | 0.11 | 20% | 29 Jun → | ||
| 7–13 | 0.01 | 15% | 28 Jun → | ||
| 10–13 | 0.04 | 22% | 28 Jun → | ||
| 13–11 | 0.01 | 23% | 27 Jun → | ||
| 10–13 | 0.08 | 12% | 27 Jun → | ||
| 13–11 | 0.01 | 21% | 27 Jun → | ||
| 11–13 | 0.09 | 20% | 27 Jun → | ||
| 13–9 | 0.06 | 34% | 27 Jun → | ||
| 21–25 | 0.00 | 29% | 26 Jun → | ||
| 16–14 | 0.03 | 24% | 26 Jun → | ||
| 2–13 | -0.00 | 23% | 26 Jun → | ||
| 7–13 | 0.09 | 36% | 25 Jun → | ||
| 11–13 | 0.04 | 34% | 25 Jun → | ||
| 9–13 | 0.03 | 32% | 25 Jun → | ||
| 13–11 | 0.03 | 25% | 25 Jun → | ||
| 13–5 | 0.21 | 40% | 25 Jun → | ||
| 8–13 | -0.05 | 20% | 25 Jun → | ||
| 13–7 | 0.11 | 28% | 17 Jun → | ||
| 8–13 | 0.00 | 20% | 17 Jun → | ||
| 11–13 | 0.08 | 25% | 17 Jun → | ||
| 9–13 | 0.09 | 23% | 17 Jun → | ||
| 5–13 | 0.02 | 27% | 17 Jun → | ||
| 15–15 | 0.05 | 10% | 17 Jun → | ||
| 11–13 | 0.06 | 31% | 17 Jun → | ||
| 9–13 | -0.03 | 26% | 16 Jun → | ||
| 8–13 | -0.01 | 21% | 16 Jun → | ||
| 13–9 | 0.00 | 14% | 15 Jun → | ||
| 13–9 | 0.05 | 29% | 15 Jun → | ||
| 13–6 | 0.03 | 21% | 15 Jun → |
Match data via Leetify.
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