AmanDa

AmanDa — CS2 Stats

IN76561198980304577[U:1:1020038849]Steam profile ↗✓ No bans

2,514Tracked matches50%Win rate2020Tracked since
3,476Hours in CS
CSDB Rating5.7 SolidPositional Player
Premier CS Rating13,874Blue band · top ~34.4% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 10 Nov 2026 (4 days ago). Ranks are recorded once per day this page is viewed.

−172Premier CS Rating · 14,046 → 13,874
+1Tracked matches · now 2,514
−1.8ppWin rate · 51.8% → 50.0%

Rating over time

Premier CS Rating: 14,046 -2,076 9 Sept – 10 Nov · 26 days played
12,80818,321peak 18,3219 Sept10 Nov
18,671Peak Premier in tracked matches
24Days played since 2026-09-09

Premier CS Rating

  • 4,447 below peak (18,321)
  • -805 over 30 days · declining
  • Next: Purple band at 15,000 — 1,126 to go
  • Reached: Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-09-09
  • Blue band first seen 2026-09-09

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Compare periods

Last 7 days vs previous 7

No matches recorded between 6 Nov 2026 and 14 Nov 2026.

Measured 6 Nov 2026 → 14 Nov 2026; previous 29 Oct 2026 → 6 Nov 2026.

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=21,222), 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 playerBlue band medianPurple band medianvs Purple band
Headshot rate46.9%42.0%44.4%above
Shot accuracy13.4%9.6%11.9%above
Kill/death ratio1.030.981.03meets
Match win rate35.4%43.8%45.2%9.8% short

This profile matches the typical Purple band player on 3 of 4 comparable metrics.

Widest gap: Match win rate. 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

CSDB.GGAmanDaPREMIER13,874 · Blue bandcsdb.gg/stats

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Performance scores

Aim73
Positioning60
Utility41

0–100 skill scores via Leetify.

Recent form

STEADY51–45–4Last 10051%Win rateLWWWTLLWWW

Last 10 vs previous 10: 0pp win rate · −0.01 avg rating · +0.8pp headshot accuracy · −1ms reaction

Win rate 0pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 3–1–1 · 60% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 23%
  • Avg reaction 622ms

Last 10

  • 6–3–1 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 21%
  • Avg reaction 634ms

Last 20

  • 12–7–1 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 21%
  • Avg reaction 635ms

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 (+2.1 against its own average).

Aim7.3
Utility4.1
Positioning6.0
Opening Duels1.5

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

iM

Plays most like iM 92% playstyle similarity

Most alike: positioning profile, opening-duel success.

Where you differ: lower aim profile; lower 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

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

Reaction time. 643ms 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

Aim7.3
Positioning6.0
Utility4.1
Mechanics7.7
Opening Duels3.0
Win Impact5.0

Composite 5.7/10 (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

Match rating0.01+0.02
first ⅓ avg -0.01 → last ⅓ avg 0.01
Reaction time641ms−15ms
first ⅓ avg 656ms → last ⅓ avg 641ms
Headshot accuracy20.5%−3.7%
first ⅓ avg 24.1% → last ⅓ avg 20.5%

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

0.14Best match rating · 13–7 · inferno, 10 Oct →
67%Best headshot accuracy · 13–0 · anubis, 2 Oct →
484msFastest reaction time · 13–10 · dust2, 4 Oct →
13–0Biggest win · anubis, 2 Oct →

Across the last 100 tracked matches.

Highlights

5Longest win streak
10–10In matches decided by ≤2 rounds
7Overtime games

Map breakdown

mirageBest map · 67% over 18dust2Weakest map · 26% over 19
MapGradePlayedRecordWin rateAvg rating
dust2D195–1426%-0.01
mirageS1812–667%0.02
ancientB178–947%0.01
infernoA169–756%0.00
anubisA148–657%-0.02
cacheA95–456%-0.01
nukeB63–350%0.03
train—11–0100%0.09

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (26% over 19). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

189,070Lifetime kills
1.03K/D · Top 50% of Blue band
8,303Matches
35.4%Match win rate
46.9%Headshot % · Top 50% of Blue band
13.4%Shot accuracy · Top 50% of Blue band
14,950MVPs
3,476Hours (in match)
10,700Bombs planted
1,739Bombs defused

Most-used weapons

AK-4759,923
AWP45,410
FAMAS5,794
MAC-102,243
MP92,220

Lifetime map wins

15,376inferno
6,651dust2
2,405nuke
648train
630vertigo
33lake
16cbble
8ar_shoots

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.

19.7%Headshot accuracy
37.7%Accuracy (enemy spotted)
35.1%Spray accuracy
84.8%Counter-strafing
10.1°Preaim
643msReaction time
46.0%T opening success
37.7%CT opening success
0.41Enemies flashed / flash
5.6%Flash assists
7.00HE damage / grenade
6.21Flashes / 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. 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 0.4133 — below the 0.5 mark we flag

    Grenade Lineups →
  2. Advanced Mechanics

    Losing the first CT duel repeatedly usually means holding angles that favour the peeker.

    CT opening duels 37.6628% — below the 40% mark we flag

Spend your practice time on Dust 2

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

26% win rate across 19 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust24–13-0.0629%17 Oct →
anubis13–6-0.0513%17 Oct →
inferno13–4-0.0317%17 Oct →
cache13–30.0139%17 Oct →
dust212–12-0.0716%17 Oct →
ancient11–130.0418%16 Oct →
mirage6–130.0222%16 Oct →
inferno13–50.1033%15 Oct →
nuke13–110.0813%15 Oct →
nuke13–80.0615%15 Oct →
mirage8–10.1015%14 Oct →
cache13–50.027%14 Oct →
inferno7–13-0.0016%14 Oct →
ancient13–10.0133%14 Oct →
dust211–13-0.0321%14 Oct →
mirage13–70.0126%14 Oct →
ancient13–8-0.0018%14 Oct →
mirage9–130.0323%14 Oct →
inferno7–13-0.067%13 Oct →
dust213–70.1239%13 Oct →
mirage11–130.0621%12 Oct →
anubis8–130.0123%12 Oct →
nuke9–13-0.0215%12 Oct →
ancient1–13-0.0532%12 Oct →
ancient13–60.0710%11 Oct →
dust211–13-0.0419%11 Oct →
ancient15–150.0113%11 Oct →
ancient4–13-0.0825%11 Oct →
nuke5–130.0110%11 Oct →
dust213–10-0.0619%11 Oct →
ancient15–15-0.0215%10 Oct →
inferno13–70.1435%10 Oct →
cache13–10.0419%10 Oct →
cache13–11-0.0217%10 Oct →
ancient13–110.1140%10 Oct →
dust210–130.0635%9 Oct →
inferno13–110.0922%9 Oct →
nuke13–10.0918%9 Oct →
dust28–13-0.0414%5 Oct →
cache8–13-0.0734%5 Oct →
inferno13–70.0217%5 Oct →
inferno13–5-0.0333%4 Oct →
inferno13–4-0.0418%4 Oct →
ancient14–16-0.0320%4 Oct →
dust213–100.0548%4 Oct →
dust213–11-0.0516%4 Oct →
inferno13–11-0.0029%4 Oct →
dust211–130.0233%4 Oct →
mirage13–60.0120%2 Oct →
mirage13–1-0.0413%2 Oct →
ancient14–16-0.0525%2 Oct →
cache8–130.0343%2 Oct →
anubis13–0-0.0367%2 Oct →
mirage13–110.0329%2 Oct →
dust213–80.1352%2 Oct →
mirage11–13-0.0219%25 Sept →
ancient8–130.0242%25 Sept →
dust211–130.0331%25 Sept →
mirage13–70.0240%24 Sept →
mirage13–00.0829%24 Sept →
inferno13–4-0.0133%24 Sept →
ancient13–20.0521%24 Sept →
inferno11–130.0111%22 Sept →
anubis4–130.0524%22 Sept →
mirage10–130.0339%22 Sept →
dust20–13-0.050%22 Sept →
dust29–13-0.0428%22 Sept →
anubis3–13-0.1221%22 Sept →
mirage8–13-0.0422%21 Sept →
dust23–13-0.0411%21 Sept →
ancient13–70.0513%21 Sept →
mirage13–80.0938%21 Sept →
anubis13–40.0836%21 Sept →
inferno13–16-0.0622%20 Sept →
anubis10–13-0.0613%19 Sept →
inferno7–13-0.0526%19 Sept →
ancient10–130.0041%18 Sept →
anubis7–13-0.0720%18 Sept →
cache13–6-0.0321%18 Sept →
anubis13–8-0.0220%18 Sept →
cache10–13-0.0622%18 Sept →
mirage13–60.0140%18 Sept →
mirage16–13-0.0224%17 Sept →
anubis13–110.0730%17 Sept →
dust21–13-0.020%17 Sept →
mirage13–110.0115%17 Sept →
ancient13–50.0243%17 Sept →
mirage13–60.0533%16 Sept →
cache10–130.0243%16 Sept →
anubis13–11-0.0220%16 Sept →
anubis6–13-0.0714%15 Sept →
inferno10–130.0229%15 Sept →
dust20–13-0.0945%14 Sept →
dust212–12-0.0321%13 Sept →
train13–100.0928%13 Sept →
anubis13–4-0.0121%13 Sept →
nuke0–13-0.030%13 Sept →
inferno6–13-0.0718%13 Sept →
ancient16–130.0129%13 Sept →
anubis13–50.0217%13 Sept →

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 →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.