Magdaa

Magdaa — CS2 Stats

PL76561198137728331[U:1:177462603]Steam profile ↗✓ No bans

576Tracked matches43%Win rate2020Tracked since
CSDB Rating3.4 LearningSupport
CSDB Leaderboard#55192 of 261648 tracked
FaceitLevel 5Top 67.6% of ranked FACEIT players
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 22,149 +3,204 17 Sept – 3 Apr · 33 days played
16,38623,808peak 23,80817 Sept3 Apr
23,839Peak Premier in tracked matches
57Days played since 2025-09-06

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

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CSDB.GGMagdaaFACEITLevel 5STANDINGTop 67.6% of rankedcsdb.gg/stats

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Performance scores

Aim35
Positioning40
Utility44

0–100 skill scores via Leetify.

Recent form

HOT48–48–4Last 10048%Win rateWWWLWLWWWW

Last 10 vs previous 10: +60pp win rate · +0.03 avg rating · +18.9pp headshot accuracy · +210ms reaction

Win rate up 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

  • 4–1 · 80% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 25%
  • Avg reaction 744ms

Last 10

  • 8–2 · 80% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 27%
  • Avg reaction 688ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 18%
  • Avg reaction 583ms

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).

Aim3.5
Utility4.4
Positioning4.0
Opening Duels1.7

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 72% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower opening-duel success; 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

Reaction time. 658ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 65% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim3.5
Positioning4.0
Utility4.4
Mechanics3.4
Opening Duels0.9
Win Impact2.8

Composite 3.4/10 (Learning), 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-0.04+0.01
first ⅓ avg -0.04 → last ⅓ avg -0.04
Reaction time581ms−90ms
first ⅓ avg 671ms → last ⅓ avg 581ms
Headshot accuracy16.7%+3.0%
first ⅓ avg 13.7% → last ⅓ avg 16.7%

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

0.13Best match rating · 13–3 · cache, 26 Jul →
67%Best headshot accuracy · 5–6 · ancient, 31 Mar →
203msFastest reaction time · 4–1 · mirage, 7 Jul →
13–0Biggest win · inferno, 18 Feb →

Across the last 100 tracked matches.

Highlights

7Longest win streak
W3Current streak
7–8In matches decided by ≤2 rounds
5Overtime games

Map breakdown

mirageBest map · 75% over 8dust2Weakest map · 32% over 19
MapGradePlayedRecordWin rateAvg rating
ancientB2312–1152%-0.04
infernoB2210–1245%-0.04
dust2D196–1332%-0.04
anubisB147–750%-0.05
mirageS86–275%-0.01
nukeC83–538%-0.04
overpass—43–175%-0.05
cache—21–150%0.02

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (32% over 19). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

18.4%Headshot accuracy
28.0%Accuracy (enemy spotted)
34.3%Spray accuracy
65.4%Counter-strafing
11.3°Preaim
658msReaction time
26.3%T opening success
37.1%CT opening success
0.43Enemies flashed / flash
1.3%Flash assists
8.26HE damage / grenade
8.91Flashes / 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 0.4305 — below the 0.5 mark we flag

    Grenade Lineups →
  2. 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 26.2628% — 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.

32% 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
dust213–11-0.0554%29 Jul →
anubis13–3-0.0630%29 Jul →
mirage13–80.0221%28 Jul →
cache2–6-0.090%28 Jul →
mirage13–6-0.0319%27 Jul →
dust22–13-0.1125%27 Jul →
ancient7–20.0945%27 Jul →
mirage13–70.0221%26 Jul →
cache13–30.1329%26 Jul →
dust213–7-0.0230%24 Jul →
anubis13–60.0230%24 Jul →
dust20–130.000%24 Jul →
anubis7–13-0.046%7 Jul →
mirage4–1-0.040%7 Jul →
nuke9–13-0.086%27 May →
ancient9–13-0.0810%6 May →
overpass4–9-0.0420%6 May →
inferno5–13-0.084%21 Apr →
inferno11–13-0.059%21 Apr →
inferno2–40.000%19 Apr →
inferno0–70.000%3 Apr →
ancient7–13-0.118%3 Apr →
ancient13–11-0.032%1 Apr →
dust213–11-0.0510%1 Apr →
ancient5–6-0.1167%31 Mar →
inferno13–11-0.0315%30 Mar →
anubis11–13-0.0513%29 Mar →
anubis2–8-0.1120%29 Mar →
ancient4–13-0.109%29 Mar →
ancient5–13-0.0321%28 Mar →
ancient13–6-0.009%27 Mar →
mirage13–70.000%26 Mar →
dust210–13-0.0620%26 Mar →
inferno9–13-0.1021%25 Mar →
anubis7–13-0.0527%25 Mar →
ancient12–16-0.0514%25 Mar →
inferno13–6-0.0313%24 Mar →
anubis13–160.0126%20 Mar →
inferno13–90.0923%20 Mar →
ancient13–50.000%17 Mar →
anubis13–9-0.0313%17 Mar →
overpass13–5-0.0111%9 Mar →
ancient13–30.0015%9 Mar →
mirage10–130.000%8 Mar →
nuke13–1-0.0715%8 Mar →
ancient13–7-0.0215%8 Mar →
ancient13–16-0.0912%5 Mar →
overpass13–8-0.1013%2 Mar →
anubis16–13-0.079%1 Mar →
ancient13–2-0.064%1 Mar →
mirage13–11-0.0614%27 Feb →
overpass13–9-0.058%27 Feb →
inferno13–5-0.0511%27 Feb →
nuke13–90.0413%26 Feb →
dust29–13-0.0411%24 Feb →
ancient13–5-0.0613%18 Feb →
dust210–13-0.077%18 Feb →
anubis13–9-0.0710%18 Feb →
inferno13–0-0.034%18 Feb →
inferno0–3-0.0133%11 Feb →
inferno1–7-0.050%11 Feb →
anubis11–13-0.0719%5 Feb →
ancient13–9-0.0015%5 Feb →
ancient13–6-0.0126%4 Feb →
inferno13–00.028%4 Feb →
anubis3–13-0.1110%2 Feb →
inferno9–13-0.0911%2 Feb →
ancient4–13-0.038%2 Feb →
anubis13–4-0.045%27 Jan →
inferno13–30.0121%27 Jan →
mirage10–13-0.0422%21 Jan →
anubis13–7-0.079%20 Jan →
dust212–12-0.026%20 Jan →
nuke12–12-0.0711%20 Jan →
dust210–13-0.0115%18 Jan →
inferno13–7-0.0816%16 Jan →
dust213–30.0113%15 Jan →
inferno10–13-0.0711%14 Jan →
ancient13–9-0.0016%13 Jan →
ancient11–13-0.0322%4 Jan →
inferno9–13-0.0925%25 Dec →
dust213–11-0.0316%25 Dec →
dust21–7-0.0923%21 Dec →
inferno13–9-0.120%21 Dec →
inferno15–15-0.0516%18 Dec →
dust211–13-0.0510%17 Dec →
dust29–13-0.0711%17 Dec →
ancient13–11-0.018%16 Dec →
nuke10–13-0.0315%16 Dec →
inferno8–13-0.0412%27 Sept →
nuke5–13-0.0513%26 Sept →
ancient9–13-0.0019%24 Sept →
ancient12–12-0.0714%23 Sept →
dust22–9-0.0723%23 Sept →
nuke10–130.0017%21 Sept →
dust213–0-0.0013%17 Sept →
inferno13–9-0.0413%17 Sept →
dust28–9-0.0618%7 Sept →
dust26–13-0.0412%6 Sept →
nuke6–1-0.090%6 Sept →

Match data via Leetify.

Recent teammates

Milestones

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

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