Alfwin von Morgenfels

Alfwin von Morgenfels — CS2 Stats

DO76561198883878438[U:1:923612710]Steam profile ↗✓ No bans

153Tracked matches54%Win rate2020Tracked since
665Hours in CS
CSDB Rating5.4 DevelopingPositional Player
Premier CS Rating16,648Purple band · top ~21.8% of ranked players (population est.)
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 4 Aug 2026 (90 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 16,648 -466 2 Aug – 4 Aug · 2 days played
16,64817,114peak 17,1142 Aug4 Aug
17,165Peak Premier in tracked matches
37Days played since 2026-01-02

Premier CS Rating

  • 466 below peak (17,114)
  • Next: Pink band at 20,000 — 3,352 to go
  • Reached: Purple band · Blue band · Light Blue band

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

How this compares with the same rank

Median values for Purple band among CSDB-tracked players (n=37,767), 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 playerPurple band medianPink band medianvs Pink band
Headshot rate35.6%44.4%46.9%11.4% short
Shot accuracy12.1%11.9%13.0%0.9% short
Kill/death ratio1.351.031.08above
Match win rate81.1%45.2%46.7%above

This profile matches the typical Pink band player on 2 of 4 comparable metrics.

Widest gap: Headshot rate. That is the metric furthest from the Pink band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGAlfwin von MorgenfelsPREMIER16,648 · Purple bandcsdb.gg/stats

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Performance scores

Aim61
Positioning50
Utility40

0–100 skill scores via Leetify.

Recent form

COLD45–46–9Last 10045%Win rateLWLLLLWLTL

Last 10 vs previous 10: −30pp win rate · +0.03 avg rating · −2.0pp headshot accuracy · −38ms reaction

Win rate down 30pp 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 (+0.03), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 1–4 · 20% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 9%
  • Avg reaction 505ms

Last 10

  • 2–7–1 · 20% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 9%
  • Avg reaction 528ms

Last 20

  • 7–11–2 · 35% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 10%
  • Avg reaction 547ms

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 (+1.5 against its own average).

Aim6.1
Utility4.0
Positioning5.0
Opening Duels1.5

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

iM

Plays most like iM 92% playstyle similarity

Most alike: utility contribution, positioning profile.

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

T-side openings. Opening success drops from 43% on CT to 28% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 593ms 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

Aim6.1
Positioning5.0
Utility4.0
Mechanics7.8
Opening Duels1.6
Win Impact6.2

Composite 5.4/10 (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-0.01+0.00
first ⅓ avg -0.01 → last ⅓ avg -0.01
Reaction time579ms−50ms
first ⅓ avg 629ms → last ⅓ avg 579ms
Headshot accuracy11.8%−0.3%
first ⅓ avg 12.1% → last ⅓ avg 11.8%

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

0.28Best match rating · 9–0 · vertigo, 30 Sept →
31%Best headshot accuracy · 13–4 · vertigo, 10 May →
367msFastest reaction time · 5–9 · inferno, 30 Sept →
13–1Biggest win · mirage, 23 Jul →

Across the last 100 tracked matches.

Highlights

5Longest win streak
4–2In matches decided by ≤2 rounds
6Overtime games

Map breakdown

mirageBest map · 54% over 13dust2Weakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
vertigoB3516–1946%0.00
infernoB2111–1052%0.01
mirageB137–654%-0.00
nukeB105–550%-0.05
cacheD62–433%-0.03
ancientC52–340%0.02
dust2D51–420%-0.03
anubis—31–233%-0.01
rooftop—20–20%-0.08

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

50,394Lifetime kills
1.35K/D · Top 10% of Purple band
7,492Matches
81.1%Match win rate · Top 1% of Purple band
35.6%Headshot %
12.1%Shot accuracy · Top 50% of Purple band
8,228MVPs
665Hours (in match)
3,233Bombs planted
966Bombs defused

Most-used weapons

AK-479,570
AWP5,693
MP71,971
SG 5531,526
P901,462

Lifetime map wins

4,618inferno
3,101dust2
2,344vertigo
944nuke
718lake
265cbble
233train
123dust

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.

11.8%Headshot accuracy
32.2%Accuracy (enemy spotted)
33.4%Spray accuracy
85.1%Counter-strafing
9.1°Preaim
593msReaction time
27.7%T opening success
42.9%CT opening success
0.41Enemies flashed / flash
1.9%Flash assists
11.02HE damage / grenade
4.31Flashes / 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 11.7562% — below the 15% mark we flag

    Aim Training →
  2. 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 0.405 — below the 0.5 mark we flag

    Grenade Lineups →
  3. 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 27.6636% — 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.

20% win rate across 5 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
inferno5–90.0214%30 Sept →
vertigo9–00.2810%30 Sept →
vertigo9–13-0.0610%12 Sept →
ancient9–130.076%4 Aug →
cache14–16-0.064%4 Aug →
nuke4–9-0.0912%4 Aug →
nuke9–6-0.038%4 Aug →
inferno6–90.0110%4 Aug →
inferno15–15-0.047%2 Aug →
anubis11–13-0.0011%2 Aug →
nuke13–80.0110%2 Aug →
mirage3–0-0.020%2 Aug →
inferno13–9-0.049%2 Aug →
mirage13–70.0212%2 Aug →
nuke7–13-0.0513%2 Aug →
inferno13–60.0420%2 Aug →
ancient5–13-0.0111%2 Aug →
ancient3–13-0.0516%2 Aug →
dust26–13-0.0613%1 Aug →
inferno15–15-0.069%1 Aug →
cache13–8-0.0615%1 Aug →
cache13–90.018%1 Aug →
ancient13–10-0.0015%30 Jul →
cache12–16-0.068%30 Jul →
mirage7–13-0.0514%27 Jul →
anubis8–13-0.0314%23 Jul →
ancient13–60.0717%23 Jul →
dust28–13-0.0614%23 Jul →
nuke16–13-0.0310%23 Jul →
mirage13–60.0016%23 Jul →
mirage13–10.0314%23 Jul →
vertigo13–70.0626%21 Jul →
mirage13–110.0214%21 Jul →
nuke8–13-0.047%21 Jul →
anubis13–110.0013%20 Jul →
vertigo13–9-0.0517%20 Jul →
vertigo12–120.027%20 Jul →
dust28–13-0.036%20 Jul →
inferno9–50.0113%15 Jul →
inferno9–5-0.0116%24 Jun →
nuke4–9-0.209%23 Jun →
vertigo13–20.033%11 Jun →
inferno3–9-0.016%25 May →
inferno6–9-0.070%25 May →
inferno9–60.1711%25 May →
vertigo10–130.0115%19 May →
inferno13–70.0519%19 May →
inferno9–70.107%19 May →
inferno8–8-0.049%18 May →
vertigo13–2-0.046%13 May →
vertigo9–130.0010%13 May →
vertigo9–13-0.0312%13 May →
cache6–13-0.0212%10 May →
vertigo7–13-0.0714%10 May →
vertigo13–40.0131%10 May →
vertigo13–40.038%3 May →
vertigo12–120.0111%3 May →
vertigo9–13-0.0716%3 May →
vertigo13–1-0.0116%3 May →
vertigo12–12-0.0111%3 May →
vertigo13–9-0.038%3 May →
vertigo13–5-0.028%1 May →
cache10–130.0219%1 May →
vertigo4–130.0211%22 Mar →
vertigo4–13-0.088%22 Mar →
vertigo4–00.1325%22 Mar →
mirage13–4-0.0317%20 Mar →
dust26–13-0.0516%19 Mar →
inferno8–80.046%9 Mar →
nuke16–14-0.039%8 Mar →
vertigo2–130.038%2 Mar →
vertigo1–13-0.0911%2 Mar →
vertigo3–13-0.0113%2 Mar →
vertigo7–13-0.0120%2 Mar →
vertigo13–50.0613%1 Mar →
vertigo6–13-0.0721%1 Mar →
nuke13–90.018%1 Mar →
vertigo13–6-0.026%1 Mar →
dust213–60.0311%1 Mar →
mirage5–13-0.009%1 Mar →
vertigo13–20.1110%1 Mar →
mirage12–12-0.047%27 Feb →
vertigo8–130.0411%27 Feb →
inferno6–10.0319%27 Feb →
mirage13–50.1110%27 Feb →
inferno9–30.2714%27 Feb →
mirage7–13-0.0119%15 Feb →
vertigo13–9-0.0114%15 Feb →
vertigo13–100.0114%15 Feb →
mirage10–13-0.015%15 Feb →
nuke7–13-0.0221%8 Feb →
mirage8–13-0.0317%6 Feb →
inferno9–60.0721%20 Jan →
rooftop5–9-0.015%16 Jan →
inferno9–60.0821%16 Jan →
inferno1–9-0.2513%16 Jan →
rooftop4–9-0.150%12 Jan →
inferno1–9-0.196%12 Jan →
vertigo3–13-0.076%5 Jan →
vertigo12–12-0.0515%2 Jan →

Match data via Leetify.

Recent teammates

Milestones

100 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.