Hotdog — CS2 Stats
76561198084355760[U:1:124090032]
How this compares with the same rank
Median values for Level 3 among CSDB-tracked players (n=607), 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 3 median | Level 4 median | vs Level 4 |
|---|---|---|---|---|
| Headshot rate | 36.9% | 42.1% | 42.5% | 5.5% short |
| Shot accuracy | 13.9% | 12.1% | 10.9% | above |
| Kill/death ratio | 1.20 | 0.99 | 0.99 | above |
| Match win rate | 55.8% | 43.9% | 44.2% | above |
This profile matches the typical Level 4 player on 3 of 4 comparable metrics.
Widest gap: Headshot rate. That is the metric furthest from the Level 4 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: -50pp win rate · -0.03 avg rating
Player DNA
Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.
Limited utility dependence
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 b1t 85% playstyle similarity
Most alike: opening-fight frequency, opening-duel success.
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. 579ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.
Counter-strafing. Only 68% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.
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 (×1.00 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 | 28 | 12–16 | 43% | -0.02 | |
| S | 20 | 14–6 | 70% | 0.00 | |
| S | 17 | 12–5 | 71% | 0.02 | |
| S | 11 | 8–3 | 73% | 0.02 | |
| B | 10 | 5–5 | 50% | 0.03 | |
| A | 7 | 4–3 | 57% | 0.00 | |
| — | 4 | 3–1 | 75% | 0.04 | |
| — | 2 | 2–0 | 100% | 0.01 | |
| basalt | — | 1 | 1–0 | 100% | -0.01 |
Across the last 100 tracked matches.
Dust 2 is currently your weakest sufficiently-sampled map (43% over 28). Start with the 6 essential Dust 2 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 resultsLLWLW
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 →
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 1.5273 — below the 4 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 39.5309% — 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 28 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 12–12 | -0.09 | 13% | 27 Aug → | ||
| 1–13 | -0.08 | 12% | 27 Aug → | ||
| 13–5 | -0.00 | 18% | 5 Aug → | ||
| 11–13 | -0.01 | 17% | 5 Aug → | ||
| 8–13 | -0.08 | 5% | 31 Jul → | ||
| 13–6 | 0.09 | 10% | 31 Jul → | ||
| 12–12 | 0.12 | 16% | 30 Jul → | ||
| 4–13 | -0.09 | 9% | 30 Jul → | ||
| 9–13 | 0.06 | 22% | 29 Jul → | ||
| 11–13 | -0.01 | 12% | 24 Jul → | ||
| 10–13 | 0.04 | 12% | 24 Jul → | ||
| 13–7 | 0.04 | 21% | 24 Jul → | ||
| 13–3 | -0.04 | 12% | 22 Jul → | ||
| 13–5 | 0.03 | 23% | 20 Jul → | ||
| 5–13 | -0.05 | 16% | 19 Jul → | ||
| 9–13 | -0.00 | 13% | 19 Jul → | ||
| 13–3 | 0.08 | 25% | 18 Jul → | ||
| 13–8 | 0.04 | 14% | 18 Jul → | ||
| 8–0 | 0.07 | 21% | 18 Jul → | ||
| 13–8 | 0.03 | 29% | 18 Jul → | ||
| 12–12 | -0.05 | 14% | 18 Jul → | ||
| 13–7 | -0.01 | 17% | 14 Jul → | ||
| 13–10 | 0.02 | 17% | 14 Jul → | ||
| 13–7 | 0.08 | 11% | 14 Jul → | ||
| 13–6 | 0.07 | 20% | 14 Jul → | ||
| 13–9 | 0.03 | 23% | 13 Jul → | ||
| 13–5 | 0.01 | 12% | 13 Jul → | ||
| 4–13 | -0.11 | 13% | 13 Jul → | ||
| 7–6 | -0.01 | 12% | 13 Jul → | ||
| 13–7 | 0.05 | 18% | 9 Jul → | ||
| 13–3 | 0.03 | 14% | 9 Jul → | ||
| 9–13 | -0.03 | 20% | 9 Jul → | ||
| 13–10 | 0.02 | 17% | 7 Jul → | ||
| 13–6 | 0.06 | 16% | 7 Jul → | ||
| 13–6 | 0.08 | 11% | 7 Jul → | ||
| 12–12 | 0.09 | 14% | 1 Jul → | ||
| 13–9 | 0.01 | 13% | 30 Jun → | ||
| 13–5 | 0.03 | 16% | 29 Jun → | ||
| 13–8 | 0.07 | 12% | 28 Jun → | ||
| 13–9 | -0.04 | 16% | 28 Jun → | ||
| 13–3 | 0.06 | 18% | 28 Jun → | ||
| 13–2 | 0.03 | 14% | 21 Jun → | ||
| 13–4 | 0.15 | 12% | 21 Jun → | ||
| 13–8 | 0.09 | 20% | 20 Jun → | ||
| 4–13 | -0.00 | 11% | 20 Jun → | ||
| 13–3 | 0.01 | 13% | 19 Jun → | ||
| 13–6 | 0.08 | 20% | 15 Jun → | ||
| 13–4 | 0.03 | 21% | 15 Jun → | ||
| 13–6 | 0.03 | 22% | 15 Jun → | ||
| 13–9 | 0.03 | 15% | 12 Jun → | ||
| 13–3 | 0.14 | 14% | 12 Jun → | ||
| 13–11 | 0.08 | 21% | 11 Jun → | ||
| 13–10 | 0.06 | 22% | 11 Jun → | ||
| 9–13 | -0.07 | 22% | 8 Jun → | ||
| 13–11 | -0.00 | 12% | 7 Jun → | ||
| 13–10 | 0.05 | 14% | 7 Jun → | ||
| 13–4 | 0.07 | 11% | 7 Jun → | ||
| 13–4 | 0.10 | 11% | 6 Jun → | ||
| 13–7 | 0.05 | 16% | 2 Jun → | ||
| 13–11 | 0.07 | 15% | 30 May → | ||
| 13–6 | 0.12 | 11% | 27 May → | ||
| 13–4 | -0.01 | 23% | 27 May → | ||
| 13–5 | 0.13 | 23% | 25 May → | ||
| 9–13 | -0.04 | 11% | 1 Sept → | ||
| 8–8 | -0.07 | 13% | 9 Aug → | ||
| 8–8 | -0.01 | 21% | 1 Aug → | ||
| 7–9 | -0.01 | 13% | 26 Jul → | ||
| 8–8 | -0.01 | 12% | 22 Jul → | ||
| 6–9 | -0.11 | 11% | 22 Jul → | ||
| 3–9 | -0.03 | 14% | 21 Jul → | ||
| 9–6 | 0.10 | 16% | 21 Jul → | ||
| 16–11 | -0.08 | 10% | 7 Jul → | ||
| 7–16 | -0.05 | 9% | 25 Jun → | ||
| 9–2 | -0.03 | 11% | 17 Jun → | ||
| 16–8 | 0.04 | 22% | 2 May → | ||
| 11–16 | -0.07 | 10% | 28 Apr → | ||
| 9–4 | 0.00 | 22% | 20 Apr → | ||
| 7–16 | -0.10 | 15% | 4 Apr → | ||
| 4–16 | -0.08 | 7% | 23 Mar → | ||
| 7–9 | -0.07 | 10% | 23 Mar → | ||
| 7–9 | 0.03 | 18% | 25 Oct → | ||
| 9–7 | 0.04 | 17% | 1 Nov → | ||
| 4–9 | -0.17 | 5% | 16 Oct → | ||
| 0–5 | -0.19 | 0% | 10 Oct → | ||
| 4–9 | -0.08 | 21% | 10 Oct → | ||
| basalt | 9–7 | -0.01 | 3% | 9 Oct → | |
| 2–9 | -0.03 | 15% | 5 Oct → | ||
| 9–5 | 0.00 | 38% | 5 Oct → | ||
| 9–6 | -0.01 | 16% | 5 Oct → | ||
| 2–16 | 0.00 | 15% | 29 Mar → | ||
| 16–14 | 0.00 | 20% | 6 Mar → | ||
| 12–16 | 0.00 | 7% | 27 Feb → | ||
| 9–16 | 0.00 | 16% | 25 Feb → | ||
| 16–9 | 0.00 | 8% | 21 Feb → | ||
| 16–12 | 0.00 | 9% | 15 Feb → | ||
| 16–10 | 0.00 | 18% | 5 Feb → | ||
| 14–16 | 0.00 | 5% | 5 Feb → | ||
| 15–15 | 0.00 | 14% | 31 Jan → | ||
| 16–11 | 0.00 | 9% | 30 Jan → | ||
| 13–5 | 0.00 | 11% | 29 Jan → |
Match data via Leetify.