Jug2g — CS2 Stats
76561199100720244[U:1:1140454516]
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -40pp win rate · -0.03 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
Sharp aimerExcellent counter-strafingStrong CT-side openerLimited 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 ropz 92% playstyle similarity
Most alike: positioning profile, opening-fight frequency.
Where you differ: lower utility contribution.
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
Aim. Aim score of 88 — the mechanical foundation is a clear strength.
Counter-strafing. 90% of shots taken properly stopped — movement discipline most players never reach.
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
T-side openings. Opening success drops from 59% on CT to 32% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 624ms 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 6.7/10 (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 |
|---|---|---|---|---|---|
| A | 27 | 15–12 | 56% | 0.03 | |
| B | 21 | 10–11 | 48% | 0.01 | |
| S | 16 | 11–5 | 69% | 0.01 | |
| B | 13 | 7–6 | 54% | 0.03 | |
| B | 8 | 4–4 | 50% | 0.03 | |
| D | 6 | 2–4 | 33% | 0.03 | |
| C | 5 | 2–3 | 40% | 0.02 | |
| — | 4 | 2–2 | 50% | 0.02 |
Across the last 100 tracked matches.
Anubis is currently your weakest sufficiently-sampled map (33% over 6). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWLWLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 177 | 50% | 1.15 | 16.6 |
| Dust2 | 92 | 54% | 1.14 | 17.3 |
| Inferno | 80 | 54% | 1.21 | 16.9 |
| Anubis | 79 | 48% | 1.13 | 16.6 |
| Ancient | 68 | 53% | 1.07 | 15.9 |
| Nuke | 36 | 69% | 1.24 | 17.9 |
| Vertigo | 30 | 37% | 1.06 | 16.6 |
| Train | 8 | 25% | 0.88 | 13.8 |
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 0.3164 — 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 31.6906% — 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.
33% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 9–13 | 0.01 | 29% | 29 Aug → | ||
| 11–13 | 0.03 | 25% | 27 Aug → | ||
| 4–13 | -0.01 | 23% | 26 Aug → | ||
| 7–13 | -0.01 | 23% | 25 Aug → | ||
| 13–7 | -0.01 | 29% | 19 Aug → | ||
| 13–9 | -0.06 | 38% | 16 Aug → | ||
| 7–13 | -0.02 | 15% | 15 Aug → | ||
| 10–13 | 0.01 | 29% | 11 Aug → | ||
| 13–6 | -0.00 | 30% | 9 Aug → | ||
| 0–10 | -0.04 | 21% | 4 Aug → | ||
| 13–5 | 0.02 | 28% | 4 Aug → | ||
| 15–15 | -0.01 | 32% | 4 Aug → | ||
| 16–14 | 0.01 | 24% | 3 Aug → | ||
| 13–8 | 0.03 | 24% | 3 Aug → | ||
| 13–5 | 0.05 | 18% | 2 Aug → | ||
| 13–7 | 0.04 | 12% | 24 Jun → | ||
| 16–14 | 0.11 | 38% | 24 Jun → | ||
| 1–13 | -0.08 | 20% | 23 Jun → | ||
| 5–13 | 0.02 | 12% | 22 Jun → | ||
| 13–8 | 0.06 | 31% | 21 Jun → | ||
| 11–13 | -0.06 | 40% | 20 Jun → | ||
| 3–13 | -0.08 | 16% | 20 Jun → | ||
| 13–7 | 0.11 | 30% | 8 May → | ||
| 13–7 | 0.04 | 29% | 21 Apr → | ||
| 13–11 | 0.01 | 31% | 26 Mar → | ||
| 13–6 | 0.03 | 31% | 24 Mar → | ||
| 4–13 | -0.04 | 17% | 22 Mar → | ||
| 13–11 | -0.02 | 27% | 22 Mar → | ||
| 8–13 | -0.02 | 16% | 7 Mar → | ||
| 7–2 | -0.01 | 56% | 6 Mar → | ||
| 4–13 | 0.02 | 23% | 4 Mar → | ||
| 13–11 | 0.08 | 27% | 27 Feb → | ||
| 9–13 | 0.02 | 20% | 7 Jan → | ||
| 5–13 | -0.06 | 26% | 31 Dec → | ||
| 13–3 | 0.08 | 33% | 29 Dec → | ||
| 8–13 | 0.00 | 31% | 29 Dec → | ||
| 13–7 | 0.05 | 31% | 28 Dec → | ||
| 13–9 | 0.02 | 21% | 28 Dec → | ||
| 6–13 | 0.03 | 53% | 23 Dec → | ||
| 5–13 | 0.00 | 34% | 20 Dec → | ||
| 13–7 | 0.09 | 42% | 19 Dec → | ||
| 7–13 | -0.01 | 37% | 19 Dec → | ||
| 13–4 | 0.02 | 22% | 19 Dec → | ||
| 7–13 | -0.05 | 33% | 18 Dec → | ||
| 13–4 | 0.05 | 24% | 18 Dec → | ||
| 3–13 | -0.06 | 43% | 15 Dec → | ||
| 13–10 | 0.00 | 34% | 9 Dec → | ||
| 13–9 | 0.07 | 25% | 26 Nov → | ||
| 13–9 | 0.08 | 44% | 22 Nov → | ||
| 13–3 | 0.03 | 33% | 11 Nov → | ||
| 13–10 | -0.00 | 33% | 7 Nov → | ||
| 13–7 | -0.02 | 26% | 6 Nov → | ||
| 8–13 | -0.00 | 54% | 4 Nov → | ||
| 8–13 | -0.00 | 28% | 2 Nov → | ||
| 6–13 | -0.01 | 29% | 23 Oct → | ||
| 13–10 | 0.02 | 43% | 17 Oct → | ||
| 5–13 | -0.03 | 43% | 4 Oct → | ||
| 13–11 | 0.05 | 34% | 13 Aug → | ||
| 9–13 | -0.04 | 36% | 5 Aug → | ||
| 13–6 | 0.06 | 38% | 3 Aug → | ||
| 13–6 | 0.05 | 33% | 31 Jul → | ||
| 13–8 | 0.04 | 47% | 30 Jul → | ||
| 13–4 | 0.06 | 39% | 28 Jul → | ||
| 10–13 | -0.00 | 29% | 10 Jul → | ||
| 11–13 | 0.06 | 43% | 5 Jul → | ||
| 11–13 | -0.02 | 35% | 26 Jun → | ||
| 3–13 | -0.03 | 16% | 16 Jun → | ||
| 13–9 | -0.05 | 27% | 14 Jun → | ||
| 11–13 | -0.07 | 28% | 13 Jun → | ||
| 10–13 | -0.02 | 16% | 12 Jun → | ||
| 13–11 | 0.03 | 34% | 11 Jun → | ||
| 13–8 | 0.00 | 29% | 11 Jun → | ||
| 12–16 | 0.00 | 27% | 3 Jun → | ||
| 13–5 | 0.08 | 52% | 2 Jun → | ||
| 8–13 | 0.08 | 50% | 2 Jun → | ||
| 3–13 | 0.09 | 27% | 2 Jun → | ||
| 13–9 | -0.04 | 21% | 2 Jun → | ||
| 13–4 | 0.11 | 24% | 2 Jun → | ||
| 3–13 | -0.01 | 36% | 2 Jun → | ||
| 9–5 | 0.09 | 39% | 29 May → | ||
| 9–2 | 0.21 | 55% | 29 May → | ||
| 13–5 | 0.19 | 56% | 26 May → | ||
| 5–8 | -0.03 | 17% | 25 May → | ||
| 13–4 | 0.07 | 20% | 24 May → | ||
| 9–13 | -0.01 | 33% | 23 May → | ||
| 13–9 | -0.03 | 42% | 23 May → | ||
| 9–13 | 0.02 | 33% | 22 May → | ||
| 13–8 | 0.08 | 41% | 22 May → | ||
| 13–7 | 0.04 | 46% | 22 May → | ||
| 15–15 | 0.08 | 33% | 22 May → | ||
| 13–4 | 0.07 | 30% | 21 May → | ||
| 6–13 | 0.02 | 25% | 21 May → | ||
| 8–13 | 0.03 | 44% | 21 May → | ||
| 13–1 | 0.13 | 43% | 20 May → | ||
| 13–4 | 0.12 | 37% | 19 May → | ||
| 7–13 | -0.03 | 36% | 19 May → | ||
| 4–13 | 0.00 | 33% | 18 May → | ||
| 13–5 | 0.09 | 47% | 18 May → | ||
| 13–4 | -0.05 | 22% | 17 May → | ||
| 9–13 | 0.04 | 23% | 16 May → |
Match data via Leetify.