Fajita — CS2 Stats
76561198250787884[U:1:290522156]Steam profile ↗✓ No bans
How this compares with the same rank
Median values for Level 10 among CSDB-tracked players (n=218), 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 10 median | vs Level 10 |
|---|---|---|---|
| Headshot rate | 47.6% | 52.8% | 5.2% short |
| Shot accuracy | 12.1% | 13.7% | 1.6% short |
| Kill/death ratio | 1.19 | 1.08 | above |
| Match win rate | 42.5% | 49.2% | 6.6% short |
This profile matches the typical Level 10 player on 1 of 4 comparable metrics.
Widest gap: Match win rate. That is the metric furthest from the Level 10 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: +40pp win rate · +0.01 avg rating
Player DNA
Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.
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 device 94% playstyle similarity
Most alike: opening-duel success, positioning profile.
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
Areas to improve
Reaction time. 588ms 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 5.8/10 (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 | 38 | 16–22 | 42% | 0.02 | |
| D | 18 | 6–12 | 33% | 0.05 | |
| D | 8 | 0–8 | 0% | 0.00 | |
| A | 7 | 4–3 | 57% | 0.08 | |
| D | 7 | 2–5 | 29% | 0.03 | |
| D | 6 | 0–6 | 0% | 0.03 | |
| D | 6 | 2–4 | 33% | 0.08 | |
| office | A | 5 | 3–2 | 60% | 0.04 |
| — | 3 | 1–2 | 33% | 0.06 | |
| shelter | — | 1 | 0–1 | 0% | 0.05 |
| — | 1 | 0–1 | 0% | -0.03 |
Across the last 100 tracked matches.
Mirage is currently your weakest sufficiently-sampled map (0% over 8). Start with the 6 essential Mirage 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 resultsWLLWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 67 | 61% | 1.16 | 14.8 |
| Inferno | 54 | 61% | 1.27 | 15.5 |
| Dust2 | 46 | 65% | 1.25 | 15.5 |
| Ancient | 44 | 48% | 1.02 | 14.5 |
| Anubis | 43 | 53% | 1.16 | 14.5 |
| Vertigo | 4 | 25% | 1.21 | 19.8 |
| Train | 4 | 50% | 0.77 | 11.5 |
| Nuke | 4 | 50% | 1.43 | 14.8 |
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
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
0% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 16–12 | 0.09 | 22% | 23 Aug → | ||
| 6–13 | -0.03 | 15% | 16 Aug → | ||
| 6–13 | 0.07 | 22% | 15 Aug → | ||
| 9–13 | 0.06 | 26% | 9 Aug → | ||
| 1–13 | -0.03 | 22% | 9 Aug → | ||
| 8–8 | 0.13 | 25% | 26 Jul → | ||
| 13–5 | 0.04 | 15% | 26 Jul → | ||
| 13–4 | 0.01 | 26% | 26 Jul → | ||
| 6–13 | 0.00 | 17% | 19 Jul → | ||
| 13–8 | 0.07 | 19% | 18 Jul → | ||
| 8–13 | -0.01 | 22% | 18 Jul → | ||
| 3–13 | 0.03 | 26% | 18 Jul → | ||
| 12–12 | 0.07 | 25% | 18 Jul → | ||
| 6–13 | -0.02 | 15% | 14 Jul → | ||
| shelter | 12–12 | 0.05 | 23% | 11 Jul → | |
| office | 7–13 | 0.09 | 19% | 11 Jul → | |
| 0–13 | -0.05 | 8% | 11 Jul → | ||
| 2–13 | -0.02 | 20% | 11 Jul → | ||
| 10–13 | 0.05 | 29% | 7 Jul → | ||
| 4–13 | 0.08 | 32% | 7 Jul → | ||
| 3–13 | 0.05 | 23% | 5 Jul → | ||
| 13–8 | 0.21 | 18% | 4 Jul → | ||
| 13–4 | 0.35 | 30% | 4 Jul → | ||
| 13–5 | 0.17 | 22% | 4 Jul → | ||
| 5–13 | 0.03 | 16% | 4 Jul → | ||
| 13–8 | -0.04 | 32% | 4 Jul → | ||
| 13–3 | 0.08 | 16% | 4 Jul → | ||
| 4–13 | 0.01 | 21% | 4 Jul → | ||
| 9–13 | 0.01 | 11% | 30 Jun → | ||
| 7–13 | 0.03 | 29% | 30 Jun → | ||
| 13–11 | 0.06 | 21% | 28 Jun → | ||
| 10–13 | 0.04 | 15% | 28 Jun → | ||
| 11–13 | 0.06 | 17% | 27 Jun → | ||
| 9–13 | 0.07 | 15% | 27 Jun → | ||
| 7–13 | 0.03 | 18% | 27 Jun → | ||
| 12–12 | 0.09 | 21% | 27 Jun → | ||
| 13–6 | 0.01 | 17% | 23 Jun → | ||
| 13–11 | 0.09 | 28% | 22 Jun → | ||
| 10–1 | 0.08 | 17% | 19 Jun → | ||
| 4–13 | -0.04 | 17% | 16 Jun → | ||
| 12–12 | 0.01 | 22% | 14 Jun → | ||
| 7–13 | -0.01 | 24% | 14 Jun → | ||
| 10–13 | -0.03 | 18% | 14 Jun → | ||
| 3–13 | 0.00 | 26% | 14 Jun → | ||
| 2–13 | -0.00 | 39% | 14 Jun → | ||
| 13–3 | 0.04 | 13% | 6 Jun → | ||
| 12–12 | 0.05 | 21% | 6 Jun → | ||
| 5–13 | -0.01 | 45% | 2 Jun → | ||
| 13–8 | 0.02 | 7% | 30 May → | ||
| 8–13 | 0.00 | 16% | 27 May → | ||
| 2–13 | -0.03 | 19% | 26 May → | ||
| 7–1 | 0.06 | 22% | 26 May → | ||
| 9–13 | 0.07 | 31% | 25 May → | ||
| 13–6 | 0.02 | 8% | 25 May → | ||
| 5–13 | 0.01 | 21% | 25 May → | ||
| 13–4 | 0.02 | 23% | 25 May → | ||
| 4–13 | -0.11 | 17% | 24 May → | ||
| 12–12 | 0.03 | 31% | 23 May → | ||
| 4–13 | -0.06 | 14% | 23 May → | ||
| 9–7 | 0.02 | 31% | 23 May → | ||
| 13–8 | -0.01 | 25% | 20 May → | ||
| 3–13 | 0.04 | 21% | 20 May → | ||
| office | 13–8 | 0.08 | 33% | 20 May → | |
| office | 13–9 | -0.01 | 19% | 16 May → | |
| 13–10 | 0.03 | 10% | 9 May → | ||
| 9–13 | 0.02 | 24% | 6 May → | ||
| 12–12 | 0.08 | 24% | 6 May → | ||
| 13–6 | 0.04 | 19% | 4 May → | ||
| 13–2 | 0.02 | 21% | 4 May → | ||
| 13–5 | 0.02 | 21% | 3 May → | ||
| 5–13 | 0.11 | 19% | 3 May → | ||
| 12–12 | 0.01 | 14% | 3 May → | ||
| 12–12 | 0.07 | 19% | 2 May → | ||
| 13–6 | 0.06 | 28% | 2 May → | ||
| 13–10 | 0.05 | 12% | 2 May → | ||
| 6–13 | -0.04 | 23% | 1 May → | ||
| 13–2 | -0.06 | 21% | 30 Apr → | ||
| 13–9 | 0.05 | 24% | 29 Apr → | ||
| 6–13 | 0.14 | 24% | 29 Apr → | ||
| 1–13 | -0.04 | 33% | 29 Apr → | ||
| 11–13 | 0.05 | 32% | 25 Apr → | ||
| 7–13 | 0.07 | 12% | 18 Apr → | ||
| 10–13 | 0.03 | 15% | 18 Apr → | ||
| 8–13 | 0.04 | 11% | 18 Apr → | ||
| 12–12 | 0.00 | 17% | 18 Apr → | ||
| 13–11 | 0.10 | 13% | 18 Apr → | ||
| office | 8–13 | 0.07 | 29% | 12 Apr → | |
| 13–9 | 0.05 | 15% | 12 Apr → | ||
| 3–9 | -0.12 | 29% | 12 Apr → | ||
| 12–12 | 0.05 | 18% | 12 Apr → | ||
| 7–13 | -0.03 | 13% | 12 Apr → | ||
| 8–13 | 0.02 | 19% | 11 Apr → | ||
| 9–13 | 0.04 | 19% | 11 Apr → | ||
| 7–13 | 0.04 | 19% | 11 Apr → | ||
| 11–13 | 0.01 | 25% | 8 Apr → | ||
| office | 13–6 | -0.01 | 27% | 7 Apr → | |
| 9–13 | 0.09 | 19% | 7 Apr → | ||
| 7–9 | -0.03 | 30% | 5 Apr → | ||
| 9–6 | 0.17 | 19% | 5 Apr → | ||
| 8–13 | 0.00 | 18% | 5 Apr → |
Match data via Leetify.