Merren

Merren — CS2 Stats

FI76561198371141373[U:1:410875645]Steam profile ↗✓ No bans

1,691Tracked matches39%Win rate2020Tracked since
CSDB Rating2.1 LearningAll-Rounder
FaceitLevel 4Top 81.0% of ranked FACEIT players
WingmanGold Nova Master
Ladder ranks via Leetify

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CSDB.GGMerrenFACEITLevel 4STANDINGTop 81.0% of rankedcsdb.gg/stats

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Performance scores

Aim14
Positioning36
Utility32

0–100 skill scores via Leetify.

Recent form

COLD34–57–9Last 10034%Win rateLWLWLLLLLL

Last 10 vs previous 10: −30pp win rate · +0.04 avg rating · −5.5pp headshot accuracy · −17ms 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 (+0.04), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 2–3 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 18%
  • Avg reaction 761ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 16%
  • Avg reaction 718ms

Last 20

  • 7–12–1 · 35% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 19%
  • Avg reaction 726ms

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

Aim1.4
Utility3.2
Positioning3.6
Opening Duels1.7
Clutch3.2

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

m0NESY

Plays most like m0NESY 61% 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. 688ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 53% 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

Aim1.4
Positioning3.6
Utility3.2
Mechanics0.6
Opening Duels2.3
Win Impact1.4

Composite 2.1/10 (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-0.05−0.02
first ⅓ avg -0.03 → last ⅓ avg -0.05
Reaction time709ms−21ms
first ⅓ avg 730ms → last ⅓ avg 709ms
Headshot accuracy18.1%+5.5%
first ⅓ avg 12.6% → last ⅓ avg 18.1%

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

0.16Best match rating · 9–3 · poseidon, 2 Aug →
100%Best headshot accuracy · 12–12 · train, 18 Aug →
398msFastest reaction time · 13–10 · dust2, 7 Sept →
13–1Biggest win · cache, 26 Aug →

Across the last 100 tracked matches.

Highlights

4Longest win streak
5–8In matches decided by ≤2 rounds
2Overtime games

Map breakdown

trainBest map · 40% over 25poseidonWeakest map · 29% over 35
MapGradePlayedRecordWin rateAvg rating
poseidonD3510–2529%-0.06
trainC2510–1540%-0.02
dust2C166–1038%-0.05
cacheC83–538%-0.02
nukeD62–433%-0.03
anubis—32–167%-0.02
ancient—20–20%-0.05
inferno—20–20%0.02
rush_001—11–0100%-0.11
eldorado—10–10%-0.15
mirage—10–10%-0.08

Across the last 100 tracked matches.

Faceit stats

Combat

1,231Matches
51%Win rate
0.82Avg K/D
72.7ADR
35%Headshot %

Clutches & streaks

36%1v1 clutch win
14%1v2 clutch win
7Longest win streak

Recent Faceit resultsLWLLW

MapMatchesWin rateAvg K/DAvg kills
Ancient5147%0.8413.0
Anubis4347%0.9914.4
Nuke4156%1.0914.6
Inferno3566%1.0213.9
Dust22733%0.9916.3
Mirage2352%1.3614.5
Vertigo1867%1.1316.9
Train1090%0.9514.2

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.

15.4%Headshot accuracy
28.1%Accuracy (enemy spotted)
29.6%Spray accuracy
52.7%Counter-strafing
13.2°Preaim
688msReaction time
38.1%T opening success
40.4%CT opening success
0.33Enemies flashed / flash
3.0%Flash assists
5.39HE damage / grenade
6.95Flashes / 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. Advanced Mechanics

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 13.2105° — above the 12° 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 0.3322 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Nuke

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.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
poseidon4–9-0.0823%2 Nov →
poseidon9–60.0211%2 Nov →
dust25–13-0.0522%30 Oct →
anubis13–110.0520%29 Oct →
dust25–13-0.1014%26 Oct →
dust29–13-0.0316%25 Oct →
train6–13-0.059%25 Oct →
train6–13-0.0810%20 Oct →
train2–13-0.0218%8 Oct →
dust24–13-0.0214%8 Oct →
rush_0015–1-0.110%24 Sept →
poseidon9–50.0920%22 Sept →
poseidon1–9-0.1160%20 Sept →
eldorado5–9-0.150%18 Sept →
poseidon9–00.0750%18 Sept →
poseidon8–8-0.0128%17 Sept →
poseidon2–9-0.1910%16 Sept →
dust213–4-0.1010%16 Sept →
poseidon4–9-0.1919%15 Sept →
poseidon9–7-0.0716%15 Sept →
dust211–13-0.0714%15 Sept →
train9–13-0.064%13 Sept →
poseidon0–9-0.1022%13 Sept →
poseidon4–9-0.1014%10 Sept →
train13–9-0.0710%10 Sept →
dust26–13-0.0519%8 Sept →
dust213–10-0.0330%7 Sept →
dust213–7-0.0817%5 Sept →
dust213–4-0.0221%2 Sept →
dust213–10-0.0312%30 Aug →
dust23–13-0.0612%27 Aug →
cache13–10.1115%26 Aug →
poseidon2–9-0.0436%24 Aug →
cache13–1-0.0327%22 Aug →
nuke11–13-0.0118%22 Aug →
ancient2–13-0.0521%22 Aug →
nuke12–120.005%22 Aug →
dust213–5-0.0515%21 Aug →
dust28–13-0.0619%20 Aug →
train6–13-0.0711%20 Aug →
train12–12-0.06100%18 Aug →
train13–9-0.0411%16 Aug →
train7–13-0.024%15 Aug →
anubis9–13-0.0619%14 Aug →
dust26–13-0.0612%13 Aug →
cache12–12-0.0418%7 Aug →
poseidon7–9-0.1610%7 Aug →
train6–13-0.0521%5 Aug →
poseidon5–9-0.1316%3 Aug →
poseidon7–9-0.1914%2 Aug →
poseidon9–30.166%2 Aug →
poseidon7–9-0.0416%1 Aug →
poseidon0–9-0.2711%31 Jul →
poseidon2–9-0.3227%30 Jul →
poseidon6–90.0013%30 Jul →
train13–4-0.0117%29 Jul →
train8–13-0.0019%29 Jul →
poseidon5–90.0114%28 Jul →
poseidon6–9-0.0810%28 Jul →
poseidon9–50.0414%27 Jul →
cache12–12-0.0215%25 Jul →
train13–70.063%20 Jun →
inferno12–16-0.0510%19 Jun →
ancient8–13-0.065%18 Jun →
poseidon9–60.0618%18 Jun →
inferno8–80.0920%18 Jun →
poseidon4–9-0.1321%18 Jun →
poseidon3–9-0.0510%16 Jun →
poseidon9–7-0.1422%14 Jun →
anubis16–14-0.0512%14 Jun →
nuke8–13-0.0119%14 Jun →
poseidon2–9-0.0912%14 Jun →
poseidon9–10.0921%13 Jun →
train13–3-0.0610%11 Jun →
nuke13–5-0.0410%9 Jun →
poseidon6–9-0.1416%8 Jun →
nuke13–9-0.0215%7 Jun →
mirage8–13-0.086%7 Jun →
train13–80.0315%7 Jun →
poseidon6–9-0.0912%7 Jun →
nuke8–13-0.094%5 Jun →
train8–130.0813%4 Jun →
cache12–12-0.029%4 Jun →
cache2–13-0.1121%2 Jun →
train5–13-0.0710%1 Jun →
cache6–13-0.0514%31 May →
train13–60.0311%31 May →
train12–120.1014%27 May →
poseidon3–9-0.119%21 May →
train13–6-0.059%20 May →
poseidon7–9-0.0121%19 May →
train2–13-0.058%17 May →
poseidon8–80.0319%16 May →
train8–13-0.130%15 May →
train13–11-0.0810%12 May →
dust211–13-0.0113%12 May →
train13–20.139%11 May →
train11–13-0.017%10 May →
cache13–9-0.0016%10 May →
poseidon9–20.0219%9 May →

Match data via Leetify.

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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