Magma

Magma — CS2 Stats

US76561198211237321[U:1:250971593]Steam profile ↗✓ No bans

35Tracked matches53%Win rate2026Tracked since
44Hours in CS
CSDB Rating1.7 LearningAll-Rounder
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 31 Aug 2026 (45 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 35 tracked matches. Play, then come back: the next observation lands here.

Rating over time

13Days played since 2026-04-19

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled.

Performance scores

Aim8
Positioning10
Utility4

0–100 skill scores via Leetify.

Recent form

STEADY17–18Last 3549%Win rateLWLWLWLLWL

Last 10 vs previous 10: −20pp win rate · −0.02 avg rating · −1.8pp headshot accuracy · −53ms reaction

Win rate down 20pp 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

  • 2–3 · 40% win rate
  • Avg rating -0.08
  • Avg headshot accuracy 11%
  • Avg reaction 820ms

Last 10

  • 4–6 · 40% win rate
  • Avg rating -0.08
  • Avg headshot accuracy 10%
  • Avg reaction 800ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 11%
  • Avg reaction 827ms

Newest first, from the last 35 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: All-Rounder — No style dimension stands clear of the others in this profile.

Aim0.8
Utility0.4
Positioning1.0
Opening Duels0.0

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

jL

Plays most like jL 79% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower positioning profile; 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. 809ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 66% 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

Aim0.8
Positioning1.0
Utility0.4
Mechanics3.7
Opening Duels0.0
Win Impact6.1

Composite 1.7/10 (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-0.08+0.02
first ⅓ avg -0.09 → last ⅓ avg -0.08
Reaction time818ms+20ms
first ⅓ avg 798ms → last ⅓ avg 818ms
Headshot accuracy10.9%−0.9%
first ⅓ avg 11.8% → last ⅓ avg 10.9%

Rolling 5-match average across the last 35 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.00Best match rating · 13–7 · anubis, 21 Apr →
33%Best headshot accuracy · 6–13 · cache, 6 May →
586msFastest reaction time · 13–8 · nuke, 21 Apr →
13–1Biggest win · cache, 23 May →

Across the last 35 tracked matches.

Highlights

6Longest win streak

Map breakdown

cacheBest map · 55% over 11trainWeakest map · 33% over 6
MapGradePlayedRecordWin rateAvg rating
cacheA116–555%-0.08
trainD62–433%-0.08
anubisC52–340%-0.06
inferno—43–175%-0.06
dust2—32–167%-0.10
office—21–150%-0.05
mirage—20–20%-0.11
nuke—11–0100%-0.08
ancient—10–10%-0.10

Across the last 35 tracked matches.

Lifetime stats

574Lifetime kills
0.30K/D
103Matches
25.2%Match win rate
44.6%Headshot % · Top 50% of tracked players
0.0%Shot accuracy
21MVPs
44Hours (in match)
71Bombs planted
7Bombs defused

Most-used weapons

Lifetime map wins

108dust2
49inferno
45train
24nuke
20office
4vertigo

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.

12.0%Headshot accuracy
25.3%Accuracy (enemy spotted)
19.3%Spray accuracy
66.4%Counter-strafing
11.6°Preaim
809msReaction time
4.6%T opening success
4.8%CT opening success
0.07Enemies flashed / flash
0.0%Flash assists
0.96HE damage / grenade
0.18Flashes / 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. 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 11.9551% — below the 15% mark we flag

    Aim Training →
  2. Advanced Mechanics

    Sustained sprays are missing more than they land, which is a recoil-control pattern you can drill directly.

    Spray accuracy 19.3214% — below the 20% mark we flag

    Practice Config →
  3. Best CS2 Settings

    Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.

    Reaction time 808.9679ms — above the 700ms mark we flag

    Aim Training →
Spend your practice time on Train

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

33% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
anubis1–13-0.0814%1 Jun →
anubis13–6-0.034%1 Jun →
anubis10–13-0.109%28 May →
cache13–1-0.0720%23 May →
cache3–13-0.126%23 May →
office13–6-0.0215%13 May →
office7–13-0.0811%13 May →
mirage8–13-0.0910%8 May →
cache12–6-0.090%7 May →
cache7–13-0.099%7 May →
cache13–5-0.0622%7 May →
cache13–9-0.0813%7 May →
cache13–4-0.0215%6 May →
cache7–13-0.0715%6 May →
cache6–13-0.1033%6 May →
cache2–13-0.060%6 May →
cache13–7-0.098%29 Apr →
train13–3-0.100%27 Apr →
train9–0-0.000%27 Apr →
train6–13-0.048%27 Apr →
train11–13-0.0710%27 Apr →
train5–13-0.0933%26 Apr →
dust211–13-0.068%26 Apr →
anubis13–70.0011%21 Apr →
inferno13–4-0.0417%21 Apr →
nuke13–8-0.0817%21 Apr →
dust213–9-0.139%21 Apr →
inferno13–8-0.056%21 Apr →
inferno13–2-0.0417%20 Apr →
ancient6–13-0.1015%20 Apr →
inferno8–13-0.1013%20 Apr →
train1–13-0.189%20 Apr →
mirage11–13-0.1314%20 Apr →
dust213–4-0.1013%19 Apr →
anubis4–13-0.080%19 Apr →

Match data via Leetify.

Recent teammates

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

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