taiwolfgod — CS2 Stats
76561198123567442[U:1:163301714]
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 |
|---|---|---|
| Headshot rate | 57.1% | 52.8% |
| Shot accuracy | 8.8% | 13.7% |
| Kill/death ratio | 0.93 | 1.08 |
| Match win rate | 48.5% | 49.2% |
Share this profile
The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.
Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: +40pp win rate · +0.02 avg rating
Player DNA
Primary style: Entry Fragger — High opening-fight frequency with above-par success in them.
Strong CT-side openerEffective 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 s1mple 93% playstyle similarity
Most alike: opening-fight frequency, 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
Strengths
CT openings. 62% CT opening-duel success — winning the first fight on the defending side is rare and valuable.
Flashes. 0.79 enemies blinded per flash — utility that consistently lands.
Areas to improve
T-side openings. Opening success drops from 62% on CT to 45% on T — the same duels are being taken with worse setups on the attacking side.
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 7.6/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.05 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 | 17–10 | 63% | 0.05 | |
| B | 23 | 12–11 | 52% | 0.01 | |
| S | 21 | 14–7 | 67% | 0.03 | |
| C | 14 | 6–8 | 43% | 0.02 | |
| B | 10 | 5–5 | 50% | 0.02 | |
| — | 4 | 1–3 | 25% | 0.06 | |
| — | 1 | 0–1 | 0% | 0.16 |
Across the last 100 tracked matches.
Nuke is currently your weakest sufficiently-sampled map (43% over 14). Start with the 6 essential Nuke 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 resultsLWLLW
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 509 | 50% | 1.12 | 15.4 |
| Ancient | 361 | 53% | 1.19 | 16.6 |
| Anubis | 361 | 56% | 1.20 | 16.4 |
| Dust2 | 345 | 58% | 1.13 | 15.0 |
| Nuke | 139 | 48% | 1.06 | 15.0 |
| Vertigo | 72 | 54% | 1.31 | 18.7 |
| Inferno | 30 | 57% | 1.24 | 16.7 |
| Overpass | 27 | 56% | 1.30 | 16.1 |
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.
43% win rate across 14 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 5–13 | 0.09 | 26% | 13 Aug → | ||
| 13–10 | 0.14 | 24% | 13 Aug → | ||
| 13–7 | 0.01 | 26% | 30 Jul → | ||
| 5–13 | -0.04 | 21% | 30 Jul → | ||
| 13–11 | 0.04 | 15% | 30 Jul → | ||
| 13–6 | -0.00 | 32% | 30 Jul → | ||
| 13–6 | 0.04 | 17% | 26 Jul → | ||
| 13–3 | 0.10 | 31% | 25 Jul → | ||
| 13–11 | 0.00 | 26% | 21 Jul → | ||
| 2–13 | -0.11 | 13% | 12 Jul → | ||
| 9–13 | 0.01 | 18% | 8 Jul → | ||
| 7–13 | -0.07 | 31% | 30 Jun → | ||
| 8–13 | -0.03 | 21% | 30 Jun → | ||
| 11–13 | 0.01 | 12% | 1 Jun → | ||
| 10–13 | 0.07 | 34% | 1 Jun → | ||
| 13–10 | 0.00 | 18% | 31 May → | ||
| 9–13 | 0.04 | 27% | 31 May → | ||
| 12–16 | 0.05 | 24% | 18 Apr → | ||
| 13–6 | 0.03 | 11% | 18 Apr → | ||
| 13–8 | 0.02 | 18% | 12 Apr → | ||
| 16–13 | 0.09 | 24% | 12 Apr → | ||
| 1–13 | -0.06 | 42% | 28 Mar → | ||
| 13–5 | 0.01 | 27% | 17 Mar → | ||
| 13–6 | 0.15 | 22% | 17 Mar → | ||
| 14–16 | 0.16 | 24% | 17 Mar → | ||
| 8–13 | -0.02 | 37% | 14 Mar → | ||
| 13–10 | 0.03 | 7% | 13 Mar → | ||
| 13–5 | 0.13 | 34% | 2 Mar → | ||
| 13–5 | 0.16 | 23% | 2 Mar → | ||
| 13–11 | 0.06 | 28% | 22 Feb → | ||
| 7–13 | 0.02 | 22% | 21 Feb → | ||
| 13–4 | 0.05 | 9% | 20 Feb → | ||
| 13–6 | 0.02 | 29% | 13 Feb → | ||
| 13–8 | 0.16 | 25% | 13 Feb → | ||
| 3–13 | -0.06 | 20% | 21 Jan → | ||
| 13–5 | 0.07 | 25% | 21 Jan → | ||
| 5–13 | -0.02 | 20% | 10 Jan → | ||
| 7–13 | 0.03 | 30% | 7 Jan → | ||
| 13–4 | 0.02 | 23% | 4 Jan → | ||
| 9–13 | 0.01 | 20% | 7 Dec → | ||
| 10–13 | 0.00 | 34% | 4 Dec → | ||
| 13–6 | 0.12 | 18% | 2 Dec → | ||
| 9–13 | 0.11 | 21% | 29 Nov → | ||
| 13–6 | 0.06 | 15% | 22 Nov → | ||
| 11–13 | -0.03 | 12% | 1 Nov → | ||
| 10–13 | -0.01 | 14% | 30 Oct → | ||
| 13–2 | 0.03 | 21% | 29 Oct → | ||
| 13–7 | 0.05 | 27% | 25 Oct → | ||
| 4–13 | -0.03 | 19% | 12 Oct → | ||
| 13–9 | 0.16 | 25% | 11 Oct → | ||
| 9–13 | -0.02 | 20% | 6 Oct → | ||
| 13–8 | 0.07 | 27% | 26 Sept → | ||
| 9–13 | -0.01 | 27% | 26 Sept → | ||
| 13–7 | -0.00 | 23% | 25 Sept → | ||
| 13–10 | 0.04 | 33% | 25 Aug → | ||
| 13–7 | 0.05 | 17% | 24 Aug → | ||
| 13–5 | 0.08 | 30% | 23 Aug → | ||
| 16–13 | -0.01 | 31% | 23 Aug → | ||
| 4–13 | -0.07 | 18% | 21 Aug → | ||
| 13–7 | 0.05 | 43% | 16 Aug → | ||
| 7–13 | -0.07 | 17% | 9 Aug → | ||
| 13–6 | -0.08 | 32% | 6 Aug → | ||
| 13–5 | 0.10 | 29% | 28 May → | ||
| 14–16 | -0.02 | 9% | 1 May → | ||
| 11–13 | -0.01 | 25% | 28 Apr → | ||
| 16–12 | -0.01 | 22% | 28 Apr → | ||
| 4–13 | -0.01 | 30% | 26 Feb → | ||
| 9–13 | 0.14 | 18% | 24 Feb → | ||
| 11–13 | 0.09 | 22% | 12 Feb → | ||
| 13–10 | 0.00 | 18% | 6 Feb → | ||
| 13–11 | 0.03 | 15% | 27 Jan → | ||
| 13–8 | 0.01 | 17% | 26 Jan → | ||
| 9–13 | -0.01 | 21% | 16 Jan → | ||
| 13–7 | 0.15 | 24% | 13 Jan → | ||
| 13–6 | 0.20 | 27% | 7 Jan → | ||
| 13–10 | -0.03 | 27% | 14 Dec → | ||
| 13–11 | 0.03 | 18% | 13 Dec → | ||
| 13–8 | 0.03 | 19% | 13 Dec → | ||
| 10–13 | 0.02 | 18% | 10 Dec → | ||
| 13–6 | 0.06 | 20% | 10 Dec → | ||
| 11–13 | -0.00 | 29% | 8 Dec → | ||
| 13–10 | -0.03 | 24% | 8 Dec → | ||
| 13–7 | 0.09 | 33% | 6 Dec → | ||
| 13–8 | 0.07 | 26% | 28 Nov → | ||
| 5–13 | -0.02 | 32% | 28 Nov → | ||
| 16–19 | 0.08 | 28% | 24 Nov → | ||
| 11–13 | 0.07 | 14% | 24 Nov → | ||
| 13–7 | 0.08 | 33% | 24 Nov → | ||
| 10–13 | -0.01 | 28% | 24 Nov → | ||
| 13–5 | 0.05 | 29% | 23 Nov → | ||
| 10–13 | -0.04 | 24% | 23 Nov → | ||
| 8–13 | 0.04 | 28% | 23 Nov → | ||
| 7–13 | -0.02 | 12% | 23 Nov → | ||
| 6–13 | -0.06 | 19% | 22 Nov → | ||
| 13–2 | 0.17 | 27% | 22 Nov → | ||
| 13–2 | 0.04 | 13% | 22 Nov → | ||
| 13–7 | -0.03 | 14% | 22 Nov → | ||
| 8–13 | -0.01 | 21% | 21 Nov → | ||
| 13–6 | 0.08 | 22% | 21 Nov → | ||
| 6–13 | 0.02 | 19% | 16 Nov → |
Match data via Leetify.