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TS_ScarlettRose

TS_ScarlettRose — CS2 Stats

US76561197984370881[U:1:24105153]Steam profile ↗✓ No bans

4,274Tracked matches52%Win rate2020Tracked since
CSDB Rating4.1 DevelopingPositional Player
FaceitLevel 4Top 81.0% of ranked FACEIT players
WingmanSilver Elite
Ladder ranks via Leetify

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CSDB.GGTS_ScarlettRoseFACEITLevel 4STANDINGTop 81.0% of rankedcsdb.gg/stats

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Performance scores

Aim33
Positioning50
Utility10

0–100 skill scores via Leetify.

Recent form

COLD40–47–13Last 10040%Win rateWLWLTLLWLT

Last 10 vs previous 10: −40pp win rate · −0.01 avg rating · −2.2pp headshot accuracy · −18ms reaction

Win rate down 40pp 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

  • 2–2–1 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 13%
  • Avg reaction 641ms

Last 10

  • 3–5–2 · 30% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 12%
  • Avg reaction 656ms

Last 20

  • 10–7–3 · 50% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 13%
  • Avg reaction 665ms

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 (+2.9 against its own average).

Aim3.3
Utility1.0
Positioning5.0
Opening Duels2.3
Clutch0.0

Limited 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

s1mple

Plays most like s1mple 77% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower utility contribution; 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

CT openings. Opening success drops from 58% on T to 39% on CT — first contacts on the defending side are being lost.

Reaction time. 694ms 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

Aim3.3
Positioning5.0
Utility1.0
Mechanics6.2
Opening Duels4.6
Win Impact5.6

Composite 4.1/10 (Developing), 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+0.02
first ⅓ avg -0.03 → last ⅓ avg -0.00
Reaction time695ms+46ms
first ⅓ avg 649ms → last ⅓ avg 695ms
Headshot accuracy12.5%−1.5%
first ⅓ avg 14.0% → last ⅓ avg 12.5%

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

0.20Best match rating · 13–8 · nuke, 7 Oct →
29%Best headshot accuracy · 13–6 · vertigo, 8 Oct →
438msFastest reaction time · 4–9 · inferno, 9 Oct →
13–2Biggest win · dust2, 13 Oct →

Across the last 100 tracked matches.

Highlights

4Longest win streak
3–6In matches decided by ≤2 rounds
1Overtime games

Map breakdown

nukeBest map · 80% over 5infernoWeakest map · 27% over 11
MapGradePlayedRecordWin rateAvg rating
dust2C6727–4040%-0.01
infernoD113–827%-0.06
trainC52–340%0.00
nukeS54–180%0.04
mirage—41–325%-0.06
vertigo—32–167%-0.08
debris—10–10%-0.21
poseidon—11–0100%-0.01
ancient—10–10%-0.06
anubis—10–10%-0.05
cache—10–10%-0.03

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (27% over 11). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

83Matches
53%Win rate
0.75Avg K/D
67.8ADR
37%Headshot %

Clutches & streaks

0%1v1 clutch win
0%1v2 clutch win
6Longest win streak

Recent Faceit resultsLLLLW

MapMatchesWin rateAvg K/DAvg kills
Mirage1540%0.7814.8
Anubis1155%0.8213.7
Nuke944%0.6811.6
Inferno862%0.8012.9
Vertigo560%0.6513.4
Overpass425%0.6011.5
Ancient425%0.6010.8

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.

12.2%Headshot accuracy
21.5%Accuracy (enemy spotted)
59.8%Spray accuracy
77.9%Counter-strafing
14.5°Preaim
694msReaction time
58.1%T opening success
38.5%CT opening success
0.07Enemies flashed / flash
2.8%Flash assists
8.82HE damage / grenade
0.10Flashes / 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

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 14.5398° — above the 12° mark we flag

    Aim Training →
  2. Best CS2 Crosshair

    Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 12.2342% — below the 15% mark we flag

    Aim Training →
  3. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.0733 — below the 0.5 mark we flag

    Grenade Lineups →
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.

27% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
train13–60.0518%14 Oct →
dust29–13-0.0617%14 Oct →
dust213–9-0.047%14 Oct →
dust28–130.0211%14 Oct →
dust212–120.0913%13 Oct →
dust210–13-0.0214%13 Oct →
dust211–13-0.0311%13 Oct →
dust213–20.0718%13 Oct →
mirage10–13-0.084%13 Oct →
dust212–120.015%13 Oct →
dust24–130.0013%13 Oct →
vertigo9–6-0.076%12 Oct →
nuke9–50.1522%12 Oct →
inferno9–30.1017%12 Oct →
dust213–110.0116%12 Oct →
dust212–120.0217%12 Oct →
dust22–13-0.089%11 Oct →
dust213–6-0.0110%11 Oct →
dust213–110.0216%11 Oct →
dust213–10-0.0616%11 Oct →
dust210–13-0.0310%10 Oct →
dust213–8-0.077%10 Oct →
dust213–5-0.0617%10 Oct →
dust24–13-0.098%10 Oct →
dust29–130.038%10 Oct →
dust27–13-0.0012%10 Oct →
dust213–40.0612%10 Oct →
dust213–9-0.0315%10 Oct →
dust213–20.0517%10 Oct →
dust24–13-0.0412%10 Oct →
dust213–60.0714%10 Oct →
mirage6–13-0.0416%10 Oct →
nuke9–5-0.018%9 Oct →
inferno8–8-0.0118%9 Oct →
inferno4–9-0.1017%9 Oct →
mirage13–8-0.0410%9 Oct →
dust213–70.0212%9 Oct →
nuke8–8-0.1511%9 Oct →
inferno2–9-0.1115%9 Oct →
debris2–9-0.210%9 Oct →
poseidon9–2-0.0119%9 Oct →
inferno6–9-0.162%9 Oct →
inferno3–9-0.173%9 Oct →
inferno8–8-0.058%9 Oct →
dust213–60.0221%9 Oct →
vertigo3–9-0.0718%9 Oct →
dust213–50.0816%9 Oct →
dust25–130.0013%9 Oct →
dust210–130.078%9 Oct →
inferno9–40.039%8 Oct →
train13–2-0.017%8 Oct →
mirage12–12-0.0820%8 Oct →
dust213–50.019%8 Oct →
dust29–13-0.0212%8 Oct →
vertigo13–6-0.1029%8 Oct →
train9–13-0.056%8 Oct →
dust25–13-0.053%8 Oct →
inferno4–3-0.070%8 Oct →
dust212–12-0.0413%8 Oct →
dust29–130.0212%8 Oct →
dust213–70.012%8 Oct →
dust211–130.0312%8 Oct →
dust213–90.0320%8 Oct →
dust26–13-0.0611%8 Oct →
dust29–13-0.0512%8 Oct →
dust24–13-0.159%7 Oct →
nuke13–80.2010%7 Oct →
dust213–50.0215%7 Oct →
train1–8-0.0023%7 Oct →
dust210–13-0.0715%7 Oct →
dust212–120.0213%7 Oct →
dust29–13-0.070%6 Oct →
dust211–13-0.0812%6 Oct →
dust212–12-0.0617%6 Oct →
dust212–120.0025%6 Oct →
train11–130.0315%6 Oct →
nuke13–40.0011%6 Oct →
dust213–100.0117%6 Oct →
dust212–12-0.0114%6 Oct →
ancient8–13-0.069%5 Oct →
dust211–13-0.0610%5 Oct →
dust25–13-0.0810%5 Oct →
inferno2–13-0.0725%5 Oct →
dust213–6-0.0123%5 Oct →
dust210–13-0.0517%4 Oct →
dust29–13-0.057%4 Oct →
dust26–13-0.0717%4 Oct →
dust213–70.0112%4 Oct →
dust213–20.028%4 Oct →
dust26–13-0.0212%3 Oct →
dust213–90.018%3 Oct →
anubis7–13-0.0510%3 Oct →
dust211–4-0.0324%3 Oct →
dust213–10-0.0514%3 Oct →
inferno14–16-0.0115%3 Oct →
cache10–13-0.0314%3 Oct →
dust210–13-0.0212%3 Oct →
dust26–130.0316%2 Oct →
dust213–10-0.0315%2 Oct →
dust212–12-0.0511%2 Oct →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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