Martin Luther Sus

Martin Luther Sus — CS2 Stats

GB76561198148358124[U:1:188092396]Steam profile ↗✓ No bans

960Tracked matches63%Win rate2022Tracked since
CSDB Rating3.0 LearningPositional Player
WingmanGold Nova Master
Ladder ranks via Leetify

What changed since last observed

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

No change since then — still 960 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Faceit ELO: 980 +0 13 Sept – 4 Oct · 2 observations
980980peak 98013 Sept4 Oct
980Highest Faceit ELO seen on CSDB
57Days played since 2025-06-25

Faceit ELO

  • At peak — 980
  • Next: Level 5 at 1,051 — 71 to go
  • Reached: Level 4 · Level 3 · Level 2
  • Level 4 first seen 2026-09-13
  • Level 3 first seen 2026-09-13

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.

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CSDB.GGMartin Luther SusPEAK ELO980csdb.gg/stats

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Performance scores

Aim22
Positioning37
Utility35

0–100 skill scores via Leetify.

Recent form

STEADY67–33Last 10067%Win rateWWLLWWLWWL

Last 10 vs previous 10: 0pp win rate · −0.01 avg rating · +0.8pp headshot accuracy · −68ms 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

  • 3–2 · 60% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 17%
  • Avg reaction 613ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 17%
  • Avg reaction 664ms

Last 20

  • 12–8 · 60% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 17%
  • Avg reaction 698ms

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).

Aim2.2
Utility3.5
Positioning3.7
Opening Duels0.3
Clutch1.4

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

NiKo

Plays most like NiKo 66% 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

Reaction time. 702ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 59% 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

Aim2.2
Positioning3.7
Utility3.5
Mechanics2.1
Opening Duels1.0
Win Impact9.4

Composite 3.0/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.03−0.01
first ⅓ avg -0.02 → last ⅓ avg -0.03
Reaction time698ms+18ms
first ⅓ avg 681ms → last ⅓ avg 698ms
Headshot accuracy19.1%+4.1%
first ⅓ avg 15.0% → last ⅓ avg 19.1%

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

0.11Best match rating · 13–4 · train, 4 Jul →
38%Best headshot accuracy · 13–9 · train, 19 Dec →
484msFastest reaction time · 4–13 · ancient, 25 Jul →
13–1Biggest win · nuke, 27 Sept →

Across the last 100 tracked matches.

Highlights

10Longest win streak
W2Current streak
10–3In matches decided by ≤2 rounds
12Overtime games

Map breakdown

trainBest map · 88% over 8mirageWeakest map · 44% over 25
MapGradePlayedRecordWin rateAvg rating
mirageC2511–1444%-0.02
ancientS2316–770%-0.03
nukeA1610–663%-0.02
overpassS1511–473%-0.02
trainS87–188%-0.03
cache—44–0100%-0.01
dust2—43–175%-0.05
anubis—33–0100%-0.02
inferno—22–0100%-0.03

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (44% over 25). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

347Matches
52%Win rate
0.69Avg K/D
56.0ADR
47%Headshot %

Clutches & streaks

27%1v1 clutch win
17%1v2 clutch win
10Longest win streak

Recent Faceit resultsLLWWL

MapMatchesWin rateAvg K/DAvg kills
Mirage8450%0.679.9
Ancient5456%0.8111.6
Nuke3647%0.7110.3
Overpass3067%0.6810.7
Train1974%0.9514.5
Anubis1867%0.6710.3
Inferno1127%0.559.7
Vertigo1040%0.6011.1

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.

19.5%Headshot accuracy
26.3%Accuracy (enemy spotted)
30.0%Spray accuracy
59.4%Counter-strafing
12.0°Preaim
702msReaction time
28.0%T opening success
38.0%CT opening success
0.50Enemies flashed / flash
10.3%Flash assists
9.17HE damage / grenade
4.32Flashes / 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 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 701.6197ms — above the 700ms 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 0.4968 — 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 28.0123% — below the 40% mark we flag

Spend your practice time on Mirage

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

44% win rate across 25 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient13–9-0.0024%29 Sept →
nuke13–10.0321%27 Sept →
mirage6–13-0.1014%27 Sept →
ancient8–13-0.0913%23 Aug →
mirage13–50.0312%22 Jul →
cache13–7-0.0729%22 Jul →
overpass4–11-0.0713%22 May →
overpass13–7-0.0312%17 May →
cache13–6-0.0118%17 May →
ancient6–13-0.0316%16 May →
overpass4–13-0.1011%16 May →
ancient13–10-0.0219%4 May →
cache19–17-0.0211%3 May →
cache8–50.0522%2 May →
mirage13–8-0.0211%2 Apr →
nuke6–13-0.0318%29 Mar →
mirage9–13-0.0715%7 Mar →
mirage10–13-0.0317%7 Mar →
anubis13–11-0.0316%22 Jan →
mirage16–12-0.0224%20 Dec →
train13–9-0.0838%19 Dec →
mirage13–90.0135%19 Dec →
train9–13-0.0833%19 Dec →
overpass13–40.0829%19 Dec →
ancient9–13-0.0522%16 Nov →
ancient16–14-0.0714%20 Sept →
overpass16–130.0118%20 Sept →
ancient13–10-0.0226%19 Sept →
mirage7–13-0.0714%18 Sept →
mirage13–9-0.0321%10 Sept →
mirage8–13-0.0522%6 Sept →
nuke7–13-0.026%31 Aug →
ancient11–13-0.0417%31 Aug →
mirage5–13-0.1013%30 Aug →
dust213–11-0.0512%18 Aug →
mirage3–13-0.0234%16 Aug →
overpass16–14-0.0415%15 Aug →
ancient9–13-0.055%12 Aug →
ancient8–13-0.0214%7 Aug →
ancient19–17-0.0515%7 Aug →
nuke13–90.0115%7 Aug →
train16–13-0.0610%7 Aug →
ancient13–9-0.0123%6 Aug →
overpass7–13-0.0121%6 Aug →
nuke13–7-0.0338%6 Aug →
nuke13–9-0.0333%5 Aug →
overpass13–40.0119%5 Aug →
nuke13–40.0215%4 Aug →
overpass16–13-0.0323%31 Jul →
mirage8–130.0524%30 Jul →
mirage13–100.0133%30 Jul →
mirage7–130.0224%29 Jul →
mirage4–0-0.070%29 Jul →
ancient13–11-0.0620%29 Jul →
overpass13–50.0112%29 Jul →
ancient4–130.0218%25 Jul →
mirage13–100.0231%24 Jul →
overpass10–13-0.0224%24 Jul →
nuke16–13-0.0328%24 Jul →
nuke13–3-0.0324%22 Jul →
overpass13–10-0.0913%22 Jul →
overpass13–80.0318%22 Jul →
overpass13–7-0.098%21 Jul →
ancient13–7-0.0016%20 Jul →
nuke13–100.0128%19 Jul →
ancient13–40.0132%19 Jul →
inferno13–10-0.0818%18 Jul →
overpass13–7-0.0314%16 Jul →
mirage14–16-0.0133%15 Jul →
anubis13–7-0.049%15 Jul →
nuke9–13-0.0914%13 Jul →
mirage13–40.0912%13 Jul →
train13–11-0.027%13 Jul →
dust213–11-0.0318%12 Jul →
ancient13–10-0.019%12 Jul →
train13–8-0.0314%12 Jul →
inferno16–140.018%11 Jul →
mirage9–13-0.0212%11 Jul →
ancient13–10-0.0219%11 Jul →
nuke13–70.0321%11 Jul →
mirage5–13-0.0312%11 Jul →
dust25–13-0.0922%11 Jul →
mirage13–8-0.0724%11 Jul →
ancient13–3-0.0219%6 Jul →
mirage5–13-0.0113%6 Jul →
nuke4–13-0.0710%6 Jul →
train13–7-0.0720%4 Jul →
ancient13–60.019%4 Jul →
train13–40.1120%4 Jul →
anubis13–9-0.0013%3 Jul →
ancient13–3-0.043%2 Jul →
mirage10–13-0.0413%1 Jul →
mirage13–7-0.0119%1 Jul →
nuke11–13-0.066%30 Jun →
ancient13–8-0.067%29 Jun →
ancient16–12-0.0215%27 Jun →
dust213–5-0.0618%27 Jun →
train13–10-0.0522%26 Jun →
nuke13–60.0116%26 Jun →
nuke7–13-0.0727%25 Jun →

Match data via Leetify.

Recent teammates

Milestones

500 Matches10-Win Streak
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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