Gizmy — CS2 Stats
PRO100 ThievesUnited KingdomIGLSettings & gear profile →
76561198344226986[U:1:383961258]
Rating over time
Faceit ELO
- At peak — 3,603
- Next: 4,000 ELO at 4,000 — 397 to go
- Reached: 3,500 ELO · 3,000 ELO · 2,500 ELO · Level 10
- 3,500 ELO first seen 2026-08-28
- 3,000 ELO first seen 2026-08-28
CSDB's own observations — this history builds from the day a profile is first viewed and cannot be backfilled.
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: -40pp win rate · -0.05 avg rating
Player DNA
Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.
Sharp aimerExcellent counter-strafingStrong CT-side openerEffective flashesHigh utility contribution
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 NiKo 95% playstyle similarity
Most alike: aim profile, opening-duel success.
Where you differ: higher 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 93 — the mechanical foundation is a clear strength.
Utility. Utility score of 79 — grenade impact well above the norm.
Areas to improve
Positioning. Positioning trails aim by 35 points — deaths here waste a strong aim profile.
T-side openings. Opening success drops from 46% on CT to 29% 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 7.9/10 (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% | 0.00 | |
| B | 20 | 10–10 | 50% | -0.00 | |
| B | 14 | 7–7 | 50% | -0.02 | |
| A | 14 | 8–6 | 57% | -0.00 | |
| B | 12 | 6–6 | 50% | -0.02 | |
| C | 9 | 4–5 | 44% | -0.01 | |
| — | 4 | 1–3 | 25% | -0.05 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (44% over 9). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsWWLWL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Ancient | 306 | 59% | 1.24 | 16.4 |
| Anubis | 224 | 66% | 1.29 | 16.4 |
| Mirage | 171 | 58% | 1.27 | 15.8 |
| Nuke | 109 | 65% | 1.21 | 16.2 |
| Dust2 | 98 | 53% | 1.17 | 15.5 |
| Vertigo | 64 | 62% | 1.22 | 16.3 |
| Inferno | 42 | 52% | 1.37 | 16.6 |
| Overpass | 31 | 58% | 1.60 | 16.6 |
Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.
Inventory
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.
- 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 28.9573% — 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.
44% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| 9–13 | 0.01 | 45% | 24 Aug → | ||
| 13–7 | 0.00 | 34% | 24 Aug → | ||
| 10–13 | -0.03 | 17% | 24 Aug → | ||
| 13–6 | -0.01 | 23% | 24 Aug → | ||
| 13–6 | 0.02 | 18% | 23 Aug → | ||
| 13–11 | 0.01 | 14% | 21 Aug → | ||
| 5–13 | -0.03 | 16% | 14 Aug → | ||
| 5–13 | -0.02 | 23% | 14 Aug → | ||
| 4–13 | -0.06 | 16% | 12 Aug → | ||
| 13–6 | 0.08 | 32% | 9 Aug → | ||
| 16–14 | -0.01 | 19% | 9 Aug → | ||
| 16–12 | 0.03 | 16% | 9 Aug → | ||
| 7–13 | -0.01 | 14% | 9 Aug → | ||
| 13–11 | 0.04 | 28% | 9 Aug → | ||
| 13–8 | 0.07 | 19% | 9 Aug → | ||
| 13–5 | 0.04 | 16% | 9 Aug → | ||
| 13–6 | 0.04 | 13% | 8 Aug → | ||
| 13–2 | -0.01 | 13% | 8 Aug → | ||
| 13–3 | 0.07 | 28% | 7 Aug → | ||
| 13–2 | 0.20 | 29% | 7 Aug → | ||
| 11–13 | -0.04 | 28% | 26 Jul → | ||
| 0–13 | -0.10 | 35% | 26 Jul → | ||
| 13–4 | 0.01 | 24% | 26 Jul → | ||
| 15–19 | -0.05 | 23% | 23 Jul → | ||
| 13–8 | 0.01 | 20% | 23 Jul → | ||
| 7–13 | -0.01 | 22% | 23 Jul → | ||
| 4–13 | -0.02 | 25% | 22 Jul → | ||
| 13–11 | 0.03 | 26% | 22 Jul → | ||
| 13–7 | -0.04 | 16% | 22 Jul → | ||
| 10–13 | -0.02 | 34% | 22 Jul → | ||
| 13–10 | -0.02 | 32% | 22 Jul → | ||
| 9–13 | -0.06 | 26% | 22 Jul → | ||
| 7–13 | -0.05 | 27% | 14 Jun → | ||
| 11–13 | -0.01 | 16% | 14 Jun → | ||
| 13–11 | -0.02 | 15% | 13 Jun → | ||
| 10–13 | -0.06 | 22% | 13 Jun → | ||
| 9–13 | 0.02 | 33% | 13 Jun → | ||
| 13–9 | 0.01 | 18% | 12 Jun → | ||
| 7–13 | -0.05 | 28% | 12 Jun → | ||
| 13–5 | 0.03 | 32% | 12 Jun → | ||
| 10–13 | 0.01 | 24% | 11 Jun → | ||
| 7–13 | -0.03 | 14% | 11 Jun → | ||
| 13–11 | -0.03 | 26% | 9 Jun → | ||
| 13–5 | -0.00 | 42% | 9 Jun → | ||
| 7–13 | 0.02 | 20% | 8 Jun → | ||
| 13–6 | 0.04 | 26% | 8 Jun → | ||
| 8–13 | -0.04 | 20% | 8 Jun → | ||
| 12–9 | -0.02 | 31% | 7 Jun → | ||
| 0–2 | -0.10 | 0% | 7 Jun → | ||
| 19–22 | 0.01 | 18% | 6 Jun → | ||
| 13–8 | -0.03 | 27% | 6 Jun → | ||
| 2–13 | -0.09 | 16% | 13 May → | ||
| 4–13 | -0.03 | 27% | 13 May → | ||
| 10–13 | -0.02 | 10% | 12 May → | ||
| 13–2 | 0.02 | 27% | 12 May → | ||
| 16–12 | 0.02 | 19% | 12 May → | ||
| 11–13 | -0.01 | 30% | 11 May → | ||
| 10–13 | 0.02 | 30% | 11 May → | ||
| 13–11 | -0.04 | 35% | 10 May → | ||
| 13–7 | 0.03 | 28% | 10 May → | ||
| 3–13 | -0.03 | 29% | 9 May → | ||
| 3–13 | -0.07 | 24% | 9 May → | ||
| 13–9 | 0.04 | 39% | 26 Apr → | ||
| 5–13 | -0.06 | 21% | 26 Apr → | ||
| 13–10 | -0.00 | 10% | 26 Apr → | ||
| 13–0 | 0.07 | 23% | 26 Apr → | ||
| 13–6 | 0.03 | 37% | 26 Apr → | ||
| 14–16 | 0.00 | 13% | 26 Apr → | ||
| 13–2 | -0.03 | 30% | 26 Apr → | ||
| 9–13 | -0.02 | 31% | 25 Apr → | ||
| 16–14 | -0.03 | 25% | 25 Apr → | ||
| 8–13 | -0.07 | 18% | 25 Apr → | ||
| 16–14 | -0.03 | 15% | 24 Apr → | ||
| 13–7 | -0.02 | 14% | 24 Apr → | ||
| 10–13 | -0.00 | 27% | 24 Apr → | ||
| 13–8 | 0.01 | 22% | 23 Apr → | ||
| 13–4 | 0.03 | 24% | 23 Apr → | ||
| 13–8 | 0.03 | 31% | 2 Apr → | ||
| 10–13 | -0.03 | 22% | 2 Apr → | ||
| 3–13 | -0.02 | 29% | 2 Apr → | ||
| 13–8 | -0.03 | 18% | 31 Mar → | ||
| 16–12 | -0.04 | 23% | 31 Mar → | ||
| 13–11 | -0.03 | 13% | 31 Mar → | ||
| 13–8 | 0.04 | 20% | 31 Mar → | ||
| 13–6 | -0.07 | 20% | 30 Mar → | ||
| 13–8 | 0.07 | 30% | 30 Mar → | ||
| 10–13 | 0.02 | 28% | 25 Mar → | ||
| 9–13 | -0.04 | 26% | 25 Mar → | ||
| 13–8 | 0.02 | 23% | 25 Mar → | ||
| 13–11 | -0.03 | 27% | 25 Mar → | ||
| 3–13 | -0.03 | 22% | 25 Mar → | ||
| 13–9 | -0.01 | 30% | 11 Mar → | ||
| 13–3 | 0.03 | 27% | 11 Mar → | ||
| 7–11 | -0.01 | 10% | 8 Mar → | ||
| 4–2 | -0.12 | 6% | 8 Mar → | ||
| 11–13 | -0.00 | 22% | 8 Mar → | ||
| 10–13 | -0.01 | 36% | 7 Mar → | ||
| 6–13 | -0.03 | 17% | 7 Mar → | ||
| 10–13 | -0.03 | 24% | 7 Mar → | ||
| 11–13 | -0.02 | 16% | 6 Mar → |
Match data via Leetify.
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