NinjaRoar

NinjaRoar — CS2 Stats

76561197997796940[U:1:37531212]Steam profile ↗✓ No bans

464Tracked matches48%Win rate2020Tracked since
4,158Hours in CS9Hrs last 2 wks
CSDB Rating5.9 SolidSupport
FaceitLevel 10Top 12.4% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 14 Sep 2026 (30 days ago). Ranks are recorded once per day this page is viewed.

+11Tracked matches · now 464
0.0ppWin rate · 48.3% → 48.3%

Rating over time

Premier CS Rating: 25,416 +6,766 23 May – 9 Aug · 16 days played
18,65025,526peak 25,52623 May9 Aug
25,526Peak Premier in tracked matches
50Days played since 2026-05-17

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

MetricLast 30Previous 30Change
Matches23——
Win rate61%——
K/D1.20——
Headshot %62%——

Measured 14 Sep 2026 → 14 Oct 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 Level 10 among CSDB-tracked players (n=29,846), 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.

MetricThis playerLevel 10 median
Headshot rate59.5%50.9%
Shot accuracy16.0%13.7%
Kill/death ratio1.301.09
Match win rate45.3%48.4%

Share this profile

CSDB.GGNinjaRoarFACEITLevel 10STANDINGTop 12.4% of rankedcsdb.gg/stats

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

Aim82
Positioning48
Utility52

0–100 skill scores via Leetify.

Recent form

STEADY55–41–4Last 10055%Win rateLLLWLLWWWL

Last 10 vs previous 10: −20pp win rate · +0.02 avg rating · +0.2pp headshot accuracy · −19ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.02), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 24%
  • Avg reaction 559ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 29%
  • Avg reaction 543ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 29%
  • Avg reaction 552ms

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: Support — Utility contribution stands above the rest of this profile (+1 against its own average).

Aim8.2
Utility5.2
Positioning4.8
Opening Duels2.2
Clutch4.8

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

ZywOo

Plays most like ZywOo 92% playstyle similarity

Most alike: aim profile, opening-duel success.

Where you differ: lower utility contribution; lower positioning 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

Positioning. Positioning trails aim by 34 points — deaths here waste a strong aim profile.

Reaction time. 557ms 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

Aim8.2
Positioning4.8
Utility5.2
Mechanics7.6
Opening Duels1.4
Win Impact4.4

Composite 5.9/10 (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

Match rating-0.00−0.01
first ⅓ avg 0.01 → last ⅓ avg -0.00
Reaction time577ms−28ms
first ⅓ avg 605ms → last ⅓ avg 577ms
Headshot accuracy27.4%+3.2%
first ⅓ avg 24.2% → last ⅓ avg 27.4%

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

0.17Best match rating · 13–2 · office, 8 Jul →
54%Best headshot accuracy · 13–10 · cache, 9 Aug →
375msFastest reaction time · 8–13 · ancient, 2 Aug →
13–1Biggest win · office, 6 Jul →

Across the last 100 tracked matches.

Highlights

6Longest win streak
L3Current streak
4–7In matches decided by ≤2 rounds
4Overtime games

Map breakdown

nukeBest map · 88% over 8infernoWeakest map · 38% over 8
MapGradePlayedRecordWin rateAvg rating
ancientB2210–1245%0.00
cacheB178–947%0.00
dust2B157–847%0.02
mirageS129–375%0.01
anubisA106–460%-0.00
nukeS87–188%-0.00
infernoC83–538%0.00
overpass—31–233%-0.03
office—22–0100%0.09
train—11–0100%0.09
vertigo—11–0100%0.03
italy—10–10%0.05

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 8). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

189,721Lifetime kills
1.30K/D · Top 25% of Level 10 players
6,688Matches
45.3%Match win rate
59.5%Headshot % · Top 25% of Level 10 players
16.0%Shot accuracy · Top 50% of Level 10 players
22,521MVPs
3,133Hours (in match)
9,138Bombs planted
4,195Bombs defused

Most-used weapons

AK-4768,975
AWP10,559
P2503,408
FAMAS2,050
Knife1,985
UMP-451,642

Lifetime map wins

20,251dust2
9,940inferno
2,978nuke
1,734vertigo
1,606cbble
1,562train
229office
199dust

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

521Matches
55%Win rate
1.15Avg K/D
76.8ADR
58%Headshot %

Clutches & streaks

44%1v1 clutch win
21%1v2 clutch win
8Longest win streak

Recent Faceit resultsWLWWL

MapMatchesWin rateAvg K/DAvg kills
Mirage4949%1.0515.4
Ancient4146%1.0515.8
Inferno2759%1.2516.6
Anubis2458%1.1117.9
Dust21765%1.3217.5
Cache1759%1.1015.7
Nuke1354%0.9916.1
Overpass944%0.8712.4

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.

27.7%Headshot accuracy
32.2%Accuracy (enemy spotted)
34.8%Spray accuracy
84.2%Counter-strafing
9.3°Preaim
557msReaction time
29.4%T opening success
40.8%CT opening success
0.52Enemies flashed / flash
6.3%Flash assists
7.31HE damage / grenade
9.29Flashes / match

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.

  1. 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 29.4327% — below the 40% mark we flag

Spend your practice time on Inferno

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

38% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
anubis8–13-0.0315%30 Sept →
nuke9–13-0.0821%1 Sept →
cache6–130.1031%27 Aug →
train13–50.0921%14 Aug →
ancient10–13-0.0231%14 Aug →
inferno11–130.0433%14 Aug →
cache13–100.0054%9 Aug →
ancient16–120.0318%9 Aug →
nuke13–100.0041%9 Aug →
anubis4–13-0.0426%9 Aug →
ancient9–130.0450%6 Aug →
inferno13–5-0.0413%6 Aug →
ancient13–110.0219%6 Aug →
cache13–9-0.0822%5 Aug →
ancient0–3-0.0350%5 Aug →
cache13–60.0540%5 Aug →
anubis13–10-0.0234%3 Aug →
cache2–13-0.0125%3 Aug →
ancient8–13-0.0415%2 Aug →
ancient13–9-0.0021%2 Aug →
ancient7–13-0.0415%31 Jul →
nuke13–50.0126%30 Jul →
vertigo13–90.0333%29 Jul →
cache12–120.0031%28 Jul →
dust24–130.0129%28 Jul →
dust211–130.0626%27 Jul →
inferno6–13-0.0227%27 Jul →
ancient13–60.0124%24 Jul →
anubis8–13-0.0024%23 Jul →
nuke13–40.0530%18 Jul →
dust23–13-0.0728%17 Jul →
ancient7–13-0.0215%17 Jul →
mirage7–13-0.0416%15 Jul →
anubis25–23-0.0516%15 Jul →
inferno5–13-0.0026%14 Jul →
ancient13–80.0231%13 Jul →
cache13–70.0133%12 Jul →
dust211–130.0621%12 Jul →
inferno13–80.0318%12 Jul →
mirage13–80.1436%10 Jul →
cache10–13-0.0718%10 Jul →
ancient10–13-0.0324%10 Jul →
dust213–60.0321%10 Jul →
cache13–40.0328%10 Jul →
nuke13–100.0920%9 Jul →
mirage13–100.0426%8 Jul →
office13–20.1732%8 Jul →
office13–10.0138%6 Jul →
italy12–120.0544%6 Jul →
anubis13–110.0119%4 Jul →
ancient13–7-0.0125%3 Jul →
cache12–120.0124%1 Jul →
nuke13–9-0.0416%29 Jun →
ancient7–13-0.0431%28 Jun →
mirage13–80.0430%28 Jun →
mirage13–60.0338%26 Jun →
mirage8–1-0.0132%26 Jun →
ancient8–13-0.0129%26 Jun →
dust213–40.0629%24 Jun →
anubis13–40.0324%23 Jun →
mirage5–130.0319%22 Jun →
inferno11–13-0.0135%22 Jun →
overpass10–13-0.0015%18 Jun →
ancient7–130.0314%18 Jun →
dust29–13-0.0116%18 Jun →
ancient13–90.0027%16 Jun →
overpass11–13-0.0618%16 Jun →
ancient11–13-0.0321%16 Jun →
overpass13–4-0.0223%15 Jun →
ancient8–13-0.0125%15 Jun →
inferno13–100.0216%13 Jun →
nuke13–3-0.0341%13 Jun →
cache13–80.0925%13 Jun →
inferno5–13-0.0126%13 Jun →
dust29–130.0228%10 Jun →
dust213–70.0732%10 Jun →
anubis13–40.0527%10 Jun →
dust213–30.0227%10 Jun →
mirage16–140.0125%9 Jun →
dust213–70.1131%8 Jun →
nuke13–9-0.0324%6 Jun →
cache12–120.0129%6 Jun →
mirage13–50.0233%27 May →
dust210–13-0.0123%27 May →
ancient13–50.0722%27 May →
ancient13–60.0338%26 May →
cache13–50.0130%25 May →
mirage9–13-0.0518%25 May →
dust29–13-0.0729%25 May →
ancient13–40.0626%25 May →
cache13–8-0.0216%24 May →
mirage13–7-0.0218%24 May →
cache6–130.0313%24 May →
mirage13–9-0.0310%23 May →
anubis13–30.0119%19 May →
dust213–8-0.0033%19 May →
cache1–13-0.056%17 May →
cache9–13-0.0321%17 May →
dust213–50.0624%17 May →
anubis14–160.0019%17 May →

Match data via Leetify.

Recent teammates

Milestones

Faceit Level 10100 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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