Ninjini — CS2 Stats
76561198941329001[U:1:981063273]Steam profile ↗✓ No bans
What changed since last observed
CSDB last observed this profile on 28 Aug 2026 (26 days ago). Ranks are recorded once per day this page is viewed.
No change since then — still 249 tracked matches. Play, then come back: the next observation lands here.
CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 43 days played since 7 Dec 2025. Come back after the next session and the change shows above.
Is this you? Sign in with Steam to claim it and connect match tracking →
Rating over time
Premier CS Rating
- 1,286 below peak (14,982)
- Next: Purple band at 15,000 — 1,304 to go
- Reached: Blue band · Light Blue band
- Blue band first seen 2026-08-28
- Light Blue band first seen 2026-08-28
Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.
Compare periods
Last 30 days vs previous 30
No matches recorded between 28 Aug 2026 and 23 Sep 2026.
Measured 28 Aug 2026 → 23 Sep 2026; no observation near 60 days ago, so there is no previous window yet.
Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.
How this compares with the same rank
Median values for Blue band among CSDB-tracked players (n=20,829), 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 | Blue band median | Purple band median | vs Purple band |
|---|---|---|---|---|
| Headshot rate | 37.5% | 41.9% | 44.3% | 6.8% short |
| Shot accuracy | 0.1% | 9.6% | 11.8% | 11.7% short |
| Kill/death ratio | 0.99 | 0.98 | 1.03 | 0.04 short |
| Match win rate | 44.2% | 43.8% | 45.2% | 1.1% short |
This profile sits below the typical Purple band player on every metric we can compare.
Widest gap: Shot accuracy. That is the metric furthest from the Purple band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.
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: −60pp win rate · −0.08 avg rating · −18.5pp headshot accuracy · +177ms reaction
Win rate down 60pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).
Last 5 · 10 · 20 matches
Last 5
- 0–4–1 · 0% win rate
- Avg rating -0.06
- Avg headshot accuracy 12%
- Avg reaction 719ms
Last 10
- 3–5–2 · 30% win rate
- Avg rating -0.02
- Avg headshot accuracy 18%
- Avg reaction 654ms
Last 20
- 12–6–2 · 60% win rate
- Avg rating 0.02
- Avg headshot accuracy 27%
- Avg reaction 565ms
Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.
Player DNA
Primary style: Positional Player — Positioning stands above the rest of this profile (+1.5 against its own average).
Sharp aimerStrong T-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.
What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.
Your pro match
Plays most like ropz 87% playstyle similarity
Most alike: aim profile, utility contribution.
Where you differ: lower positioning profile; lower opening-duel success.
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 86 — the mechanical foundation is a clear strength.
Areas to improve
Positioning. Positioning trails aim by 33 points — deaths here waste a strong aim profile.
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
CT openings. Opening success drops from 49% on T to 30% on CT — first contacts on the defending side are being lost.
Reaction time. 583ms 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 5.5/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 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.
Personal bests
Across the last 100 tracked matches.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
 inferno | S | 25 | 22–3 | 88% | 0.06 |
 dust2 | S | 15 | 11–4 | 73% | 0.05 |
 nuke | S | 13 | 12–1 | 92% | 0.06 |
 mirage | B | 12 | 6–6 | 50% | 0.02 |
 overpass | S | 9 | 7–2 | 78% | 0.04 |
 anubis | S | 7 | 5–2 | 71% | 0.06 |
| office | S | 5 | 4–1 | 80% | 0.07 |
 train | — | 4 | 3–1 | 75% | 0.01 |
 ancient | — | 3 | 2–1 | 67% | 0.02 |
| rooftop | — | 3 | 3–0 | 100% | 0.19 |
 vertigo | — | 2 | 2–0 | 100% | 0.14 |
| warden | — | 1 | 0–1 | 0% | -0.12 |
| poseidon | — | 1 | 1–0 | 100% | 0.05 |
Across the last 100 tracked matches.
Mirage is currently your weakest sufficiently-sampled map (50% over 12). 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.
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 0.484 — below the 0.5 mark we flag
- Advanced Mechanics
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 30.2816% — below the 40% mark we flag
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| anubis | 6–13 | -0.05 | 0% | 2 Jun → | |
| dust2 | 12–12 | 0.00 | 23% | 1 Jun → | |
| mirage | 7–13 | -0.03 | 27% | 24 May → | |
| overpass | 5–13 | -0.09 | 10% | 11 May → | |
| warden | 2–9 | -0.12 | 0% | 8 May → | |
| nuke | 13–11 | 0.04 | 22% | 7 May → | |
| mirage | 13–4 | -0.01 | 39% | 30 Apr → | |
| dust2 | 15–15 | -0.04 | 23% | 27 Apr → | |
| mirage | 9–13 | 0.03 | 11% | 27 Apr → | |
| dust2 | 13–11 | 0.03 | 20% | 25 Apr → | |
| dust2 | 13–5 | 0.05 | 28% | 7 Apr → | |
| ancient | 13–3 | 0.06 | 39% | 7 Apr → | |
| dust2 | 10–13 | 0.17 | 31% | 7 Apr → | |
| anubis | 13–0 | 0.03 | 55% | 7 Apr → | |
| office | 13–2 | 0.12 | 38% | 2 Apr → | |
| dust2 | 13–6 | 0.03 | 50% | 2 Apr → | |
| office | 13–2 | 0.07 | 42% | 2 Apr → | |
| inferno | 11–3 | -0.04 | 11% | 1 Apr → | |
| dust2 | 8–0 | 0.03 | 25% | 1 Apr → | |
| anubis | 13–1 | 0.02 | 42% | 1 Apr → | |
| inferno | 13–0 | 0.08 | 64% | 31 Mar → | |
| dust2 | 13–1 | 0.10 | 39% | 31 Mar → | |
| mirage | 13–2 | 0.08 | 41% | 31 Mar → | |
| dust2 | 13–6 | 0.17 | 55% | 28 Mar → | |
| train | 9–1 | 0.05 | 18% | 28 Mar → | |
| inferno | 13–6 | 0.01 | 8% | 19 Mar → | |
| office | 13–4 | 0.09 | 33% | 19 Mar → | |
| nuke | 6–3 | -0.05 | 0% | 17 Mar → | |
| inferno | 13–5 | -0.01 | 7% | 17 Mar → | |
| dust2 | 13–7 | 0.01 | 41% | 17 Mar → | |
| overpass | 13–11 | 0.02 | 15% | 14 Mar → | |
| inferno | 6–13 | 0.08 | 18% | 10 Mar → | |
| mirage | 3–0 | 0.00 | 33% | 10 Mar → | |
| dust2 | 13–4 | 0.12 | 48% | 8 Mar → | |
| dust2 | 13–8 | -0.00 | 24% | 8 Mar → | |
| mirage | 5–13 | -0.04 | 11% | 24 Feb → | |
| dust2 | 9–13 | -0.10 | 5% | 23 Feb → | |
| mirage | 13–5 | 0.03 | 25% | 13 Feb → | |
| overpass | 13–4 | 0.08 | 50% | 13 Feb → | |
| inferno | 13–11 | -0.03 | 27% | 11 Feb → | |
| overpass | 8–13 | -0.02 | 3% | 10 Feb → | |
| poseidon | 9–2 | 0.05 | 70% | 3 Feb → | |
| office | 13–1 | 0.04 | 27% | 25 Jan → | |
| dust2 | 13–8 | 0.10 | 30% | 24 Jan → | |
| office | 12–12 | 0.05 | 26% | 24 Jan → | |
| nuke | 9–3 | -0.11 | 18% | 14 Jan → | |
| nuke | 9–2 | 0.20 | 57% | 14 Jan → | |
| overpass | 13–10 | 0.08 | 40% | 14 Jan → | |
| mirage | 11–13 | 0.03 | 33% | 12 Jan → | |
| rooftop | 9–0 | 0.23 | 55% | 9 Jan → | |
| inferno | 9–7 | -0.01 | 36% | 7 Jan → | |
| inferno | 9–1 | 0.08 | 29% | 7 Jan → | |
| inferno | 9–3 | -0.05 | 11% | 6 Jan → | |
| inferno | 9–2 | 0.06 | 31% | 6 Jan → | |
| nuke | 9–0 | 0.05 | 67% | 6 Jan → | |
| overpass | 13–1 | 0.02 | 19% | 5 Jan → | |
| rooftop | 9–0 | 0.16 | 21% | 5 Jan → | |
| vertigo | 9–1 | 0.15 | 50% | 5 Jan → | |
| nuke | 9–4 | 0.04 | 17% | 5 Jan → | |
| inferno | 9–4 | -0.03 | 33% | 5 Jan → | |
| inferno | 9–6 | -0.10 | 21% | 5 Jan → | |
| inferno | 9–1 | 0.22 | 33% | 5 Jan → | |
| inferno | 9–3 | 0.35 | 12% | 5 Jan → | |
| rooftop | 9–5 | 0.17 | 22% | 5 Jan → | |
| mirage | 4–9 | 0.03 | 25% | 5 Jan → | |
| inferno | 8–8 | 0.03 | 64% | 5 Jan → | |
| inferno | 9–1 | 0.19 | 47% | 5 Jan → | |
| inferno | 9–5 | 0.15 | 13% | 5 Jan → | |
| nuke | 9–0 | 0.10 | 60% | 4 Jan → | |
| inferno | 9–1 | 0.21 | 28% | 4 Jan → | |
| dust2 | 13–5 | 0.11 | 33% | 4 Jan → | |
| mirage | 13–7 | -0.08 | 11% | 4 Jan → | |
| nuke | 9–3 | 0.01 | 47% | 3 Jan → | |
| inferno | 9–5 | 0.07 | 75% | 3 Jan → | |
| inferno | 9–3 | 0.07 | 32% | 3 Jan → | |
| vertigo | 9–0 | 0.13 | 60% | 3 Jan → | |
| nuke | 9–2 | 0.09 | 46% | 3 Jan → | |
| nuke | 9–1 | 0.20 | 30% | 3 Jan → | |
| overpass | 9–3 | 0.02 | 33% | 3 Jan → | |
| inferno | 9–2 | 0.15 | 86% | 2 Jan → | |
| train | 10–13 | -0.02 | 14% | 31 Dec → | |
| train | 13–5 | 0.00 | 26% | 31 Dec → | |
| nuke | 15–15 | 0.07 | 37% | 12 Dec → | |
| inferno | 15–15 | 0.04 | 15% | 11 Dec → | |
| anubis | 13–5 | 0.12 | 22% | 11 Dec → | |
| anubis | 13–3 | 0.13 | 16% | 11 Dec → | |
| ancient | 13–6 | -0.01 | 35% | 10 Dec → | |
| inferno | 13–4 | 0.05 | 41% | 10 Dec → | |
| nuke | 13–8 | -0.01 | 41% | 10 Dec → | |
| anubis | 13–3 | 0.03 | 27% | 10 Dec → | |
| anubis | 10–13 | 0.15 | 23% | 10 Dec → | |
| overpass | 16–14 | 0.06 | 27% | 9 Dec → | |
| train | 13–7 | 0.02 | 22% | 9 Dec → | |
| ancient | 14–16 | 0.01 | 25% | 9 Dec → | |
| mirage | 13–3 | 0.02 | 26% | 9 Dec → | |
| nuke | 13–9 | 0.08 | 22% | 8 Dec → | |
| inferno | 13–3 | -0.02 | 16% | 8 Dec → | |
| mirage | 7–13 | 0.12 | 21% | 8 Dec → | |
| inferno | 13–6 | -0.02 | 21% | 7 Dec → | |
| overpass | 13–6 | 0.17 | 27% | 7 Dec → |
Match data via Leetify.
