mynamejeff — CS2 Stats
76561198237743752[U:1:277478024]
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +0pp win rate · -0.01 avg rating
Player DNA
Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.
Sharp aimerExcellent counter-strafingEffective flashes
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 m0NESY 97% playstyle similarity
Most alike: aim profile, 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
Strengths
Aim. Aim score of 99 — the mechanical foundation is a clear strength.
Counter-strafing. 91% of shots taken properly stopped — movement discipline most players never reach.
CT openings. 69% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
T openings. 71% T opening-duel success — entries that actually open the round.
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
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 8.1/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×0.90 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 |
|---|---|---|---|---|---|
| B | 23 | 11–12 | 48% | 0.04 | |
| A | 22 | 13–9 | 59% | 0.04 | |
| A | 18 | 10–8 | 56% | 0.05 | |
| A | 11 | 6–5 | 55% | 0.00 | |
| S | 8 | 7–1 | 88% | 0.09 | |
| A | 7 | 4–3 | 57% | 0.06 | |
| — | 4 | 4–0 | 100% | 0.10 | |
| — | 4 | 3–1 | 75% | 0.06 | |
| debris | — | 1 | 0–1 | 0% | 0.07 |
| eldorado | — | 1 | 1–0 | 100% | 0.07 |
| poseidon | — | 1 | 1–0 | 100% | 0.03 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (48% 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 resultsWLWWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Ancient | 8 | 62% | 1.33 | 16.4 |
| Inferno | 6 | 50% | 1.34 | 16.0 |
| Dust2 | 5 | 80% | 1.37 | 27.0 |
| Mirage | 4 | 75% | 1.42 | 18.5 |
| Train | 3 | 100% | 1.01 | 13.7 |
| Anubis | 2 | 50% | 0.94 | 16.5 |
| Overpass | 2 | 50% | 1.29 | 21.5 |
| Nuke | 2 | 0% | 1.14 | 20.0 |
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
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
48% win rate across 23 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 13–3 | 0.04 | 16% | 11 Aug → | ||
| 13–10 | 0.13 | 39% | 11 Aug → | ||
| 11–13 | 0.05 | 48% | 10 Aug → | ||
| 13–10 | 0.06 | 52% | 10 Aug → | ||
| 10–13 | 0.07 | 54% | 10 Aug → | ||
| 13–8 | 0.05 | 33% | 9 Aug → | ||
| debris | 8–8 | 0.07 | 36% | 9 Aug → | |
| 9–5 | 0.09 | 48% | 9 Aug → | ||
| eldorado | 9–6 | 0.07 | 39% | 9 Aug → | |
| 13–3 | 0.23 | 38% | 3 Aug → | ||
| 13–2 | 0.12 | 28% | 3 Aug → | ||
| 13–4 | 0.08 | 35% | 3 Aug → | ||
| 11–13 | -0.02 | 10% | 31 Jul → | ||
| 12–12 | 0.19 | 37% | 27 Jun → | ||
| 13–3 | 0.07 | 38% | 27 Jun → | ||
| 13–10 | 0.06 | 51% | 26 Jun → | ||
| 13–2 | 0.11 | 38% | 26 Jun → | ||
| 13–6 | 0.17 | 31% | 13 Jun → | ||
| 11–13 | 0.04 | 45% | 12 Jun → | ||
| 16–14 | 0.17 | 44% | 12 Jun → | ||
| 8–0 | 0.18 | 74% | 12 Jun → | ||
| 13–3 | 0.23 | 48% | 11 Jun → | ||
| 11–13 | 0.09 | 29% | 10 Jun → | ||
| 13–7 | 0.14 | 30% | 10 Jun → | ||
| 13–2 | 0.25 | 62% | 10 Jun → | ||
| 13–1 | 0.19 | 65% | 10 Jun → | ||
| 13–3 | 0.21 | 44% | 10 Jun → | ||
| 13–9 | 0.24 | 56% | 10 Jun → | ||
| 13–7 | 0.07 | 9% | 9 Jun → | ||
| 13–5 | 0.18 | 24% | 9 Jun → | ||
| 13–9 | 0.12 | 14% | 9 Jun → | ||
| 6–13 | -0.06 | 17% | 9 Jun → | ||
| 3–13 | -0.06 | 21% | 8 Jun → | ||
| 15–15 | 0.07 | 25% | 8 Jun → | ||
| 13–5 | 0.04 | 13% | 8 Jun → | ||
| 13–10 | 0.10 | 18% | 6 Jun → | ||
| 0–13 | -0.10 | 0% | 5 Jun → | ||
| 11–13 | 0.02 | 28% | 5 Jun → | ||
| 6–11 | 0.06 | 28% | 2 Jun → | ||
| 13–11 | 0.10 | 23% | 2 Jun → | ||
| 13–7 | -0.06 | 12% | 1 Jun → | ||
| 13–7 | 0.01 | 24% | 1 Jun → | ||
| 7–8 | 0.00 | 24% | 1 Jun → | ||
| 13–10 | 0.06 | 18% | 1 Jun → | ||
| 13–1 | 0.02 | 33% | 1 Jun → | ||
| 13–8 | 0.05 | 27% | 31 May → | ||
| 13–6 | 0.15 | 30% | 31 May → | ||
| 13–8 | 0.10 | 19% | 31 May → | ||
| 2–9 | -0.04 | 32% | 30 May → | ||
| 12–12 | 0.07 | 27% | 30 May → | ||
| 13–6 | 0.02 | 11% | 30 May → | ||
| 10–13 | 0.09 | 26% | 30 May → | ||
| 13–5 | 0.05 | 17% | 29 May → | ||
| 13–4 | -0.02 | 23% | 29 May → | ||
| 6–13 | 0.06 | 26% | 29 May → | ||
| 13–5 | 0.09 | 33% | 29 May → | ||
| 13–8 | 0.07 | 29% | 27 May → | ||
| 14–16 | 0.05 | 18% | 27 May → | ||
| 8–8 | 0.04 | 19% | 27 May → | ||
| poseidon | 9–3 | 0.03 | 24% | 27 May → | |
| 9–2 | 0.15 | 19% | 27 May → | ||
| 10–13 | -0.01 | 10% | 27 May → | ||
| 16–14 | -0.02 | 19% | 26 May → | ||
| 7–13 | -0.02 | 10% | 26 May → | ||
| 13–4 | 0.06 | 15% | 26 May → | ||
| 5–13 | -0.01 | 16% | 25 May → | ||
| 15–15 | 0.03 | 22% | 25 May → | ||
| 6–13 | -0.02 | 16% | 25 May → | ||
| 5–13 | -0.02 | 23% | 24 May → | ||
| 7–13 | 0.03 | 14% | 24 May → | ||
| 4–13 | -0.01 | 23% | 24 May → | ||
| 13–2 | 0.08 | 17% | 24 May → | ||
| 11–13 | -0.06 | 15% | 24 May → | ||
| 16–13 | -0.06 | 13% | 23 May → | ||
| 13–10 | 0.04 | 16% | 23 May → | ||
| 1–13 | -0.05 | 37% | 23 May → | ||
| 8–13 | -0.14 | 33% | 22 May → | ||
| 11–13 | -0.05 | 11% | 18 May → | ||
| 13–8 | -0.00 | 17% | 15 May → | ||
| 13–7 | 0.01 | 21% | 15 May → | ||
| 13–6 | -0.01 | 20% | 7 May → | ||
| 13–6 | -0.03 | 19% | 7 May → | ||
| 15–15 | -0.05 | 16% | 7 May → | ||
| 13–9 | 0.03 | 21% | 1 May → | ||
| 13–4 | 0.09 | 31% | 1 May → | ||
| 13–9 | 0.07 | 19% | 1 May → | ||
| 8–13 | -0.06 | 43% | 29 Apr → | ||
| 12–12 | -0.01 | 18% | 29 Apr → | ||
| 9–13 | -0.05 | 24% | 28 Apr → | ||
| 13–9 | 0.03 | 14% | 20 Apr → | ||
| 13–0 | 0.07 | 45% | 16 Apr → | ||
| 1–9 | -0.06 | 13% | 14 Apr → | ||
| 8–8 | -0.04 | 17% | 11 Apr → | ||
| 7–13 | -0.06 | 22% | 7 Apr → | ||
| 13–7 | 0.05 | 19% | 2 Apr → | ||
| 9–1 | 0.03 | 28% | 2 Apr → | ||
| 2–13 | 0.00 | 39% | 26 Mar → | ||
| 13–10 | -0.02 | 22% | 26 Mar → | ||
| 13–11 | -0.00 | 18% | 6 Mar → | ||
| 13–2 | 0.05 | 15% | 6 Mar → |
Match data via Leetify.