MarMar ツ゚

MarMar ツ゚ — CS2 Stats

US76561198822412120[U:1:862146392]Steam profile ↗✓ No bans

1,909Tracked matches41%Win rate2021Tracked since
CSDB Rating4.7 DevelopingClutch Specialist
Premier CS Rating10,112Blue band · top ~54.3% of ranked players (population est.)
CSDB Leaderboard#10097 of 13818 tracked
FaceitLevel 4 · 966 ELOTop 81.0% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGMarMar ツ゚FACEITLevel 4 · 966 ELOSTANDINGTop 81.0% of rankedPREMIER10,112 · Blue bandcsdb.gg/stats

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Performance scores

Aim44
Positioning59
Utility60

0–100 skill scores via Leetify.

Recent form

STEADY45514Last 10045%Win rateWWLWLWLWLL

Last 10 vs previous 10: +10pp win rate · +0.01 avg rating

Player DNA

Primary style: Clutch SpecialistLate-round 1vX conversion well above par.

Aim4.4
Aggression9.2
Utility6.0
Positioning5.9
Opening Duels4.0
Clutch7.6

Reliable in 1v1s

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

jL

Plays most like jL 87% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

Where you differ: 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. 610ms 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

Aim4.4
Positioning5.9
Utility6.0
Mechanics6.0
Opening Duels4.0
Win Impact2.1

Composite 4.7/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.00+0.01
first ⅓ avg -0.00 → last ⅓ avg 0.00
Reaction time604ms−37ms
first ⅓ avg 641ms → last ⅓ avg 604ms
Headshot accuracy12.4%+0.5%
first ⅓ avg 11.8% → last ⅓ avg 12.4%

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.

Highlights

0.12Best rating — dust2 13–8
131Biggest win — train
5Longest win streak
W2Current streak
116In matches decided by ≤2 rounds
9Overtime games

Map breakdown

infernoBest map · 60% over 10nukeWeakest map · 29% over 14
MapGradePlayedRecordWin rateAvg rating
cacheC1981142%0.01
nukeD1441029%-0.02
dust2B147750%0.03
ancientB147750%-0.02
mirageC114736%-0.01
infernoA106460%0.01
trainB63350%-0.01
anubisA53260%-0.04
vertigo42250%-0.01
overpass21150%0.00
office1010%-0.01

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (29% over 14). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

30Matches
67%Win rate
0.91Avg K/D
73.4ADR
44%Headshot %

Clutches & streaks

58%1v1 clutch win
5%1v2 clutch win
5Longest win streak

Recent Faceit resultsLWLWL

MapMatchesWin rateAvg K/DAvg kills
Dust2875%0.8711.6
Anubis450%0.8814.5
Nuke475%1.0514.8
Mirage450%0.649.8
Inferno475%0.9410.3
Ancient475%1.2017.3
Overpass1100%1.2918.0

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.

12.9%Headshot accuracy
30.2%Accuracy (enemy spotted)
27.3%Spray accuracy
76.9%Counter-strafing
9.6°Preaim
610msReaction time
47.5%T opening success
44.1%CT opening success
0.62Enemies flashed / flash
2.4%Flash assists
14.81HE damage / grenade
9.21Flashes / 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 12.9121% — below the 15% mark we flag

    Aim Training
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.

29% win rate across 14 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategyNuke grenade lineups

Recent matches

MapScoreRatingHS%Date
nuke13–11-0.016%3 Aug
dust213–80.0915%3 Aug
cache5–13-0.024%27 Jul
anubis13–9-0.0218%27 Jul
mirage9–13-0.0413%26 Jul
ancient13–60.0413%21 Jul
dust28–130.0828%18 Jul
dust213–100.0412%17 Jul
inferno14–16-0.0115%16 Jul
cache10–13-0.029%15 Jul
inferno3–13-0.037%15 Jul
cache13–110.0512%15 Jul
cache11–130.0017%15 Jul
mirage13–90.0110%14 Jul
ancient12–16-0.037%14 Jul
dust213–7-0.0414%14 Jul
nuke10–130.0411%14 Jul
ancient8–130.0020%14 Jul
inferno13–30.0913%13 Jul
mirage8–13-0.0114%13 Jul
ancient10–13-0.038%13 Jul
dust213–70.0920%13 Jul
inferno13–60.0616%13 Jul
anubis6–130.008%13 Jul
cache2–13-0.069%12 Jul
inferno6–130.0412%12 Jul
nuke2–13-0.0110%12 Jul
ancient13–9-0.0314%12 Jul
dust212–16-0.0116%12 Jul
cache15–15-0.0413%12 Jul
inferno13–90.0115%12 Jul
nuke2–13-0.056%12 Jul
nuke10–13-0.073%12 Jul
dust27–13-0.0121%12 Jul
cache4–13-0.047%12 Jul
ancient16–12-0.079%11 Jul
inferno11–13-0.0612%11 Jul
mirage11–13-0.0114%11 Jul
inferno13–11-0.045%11 Jul
nuke13–8-0.038%11 Jul
ancient9–13-0.067%11 Jul
dust28–13-0.039%10 Jul
mirage8–13-0.0813%10 Jul
ancient13–40.0115%10 Jul
ancient4–13-0.034%10 Jul
nuke8–13-0.0210%9 Jul
cache13–60.0910%9 Jul
anubis7–13-0.0310%9 Jul
nuke8–13-0.0918%9 Jul
cache13–8-0.0311%9 Jul
cache11–130.065%9 Jul
mirage10–13-0.0313%9 Jul
cache16–14-0.014%9 Jul
vertigo13–6-0.0215%8 Jul
nuke13–9-0.0414%8 Jul
dust28–130.0411%8 Jul
cache13–110.082%8 Jul
nuke9–130.0211%8 Jul
inferno13–8-0.0024%8 Jul
vertigo10–130.0318%7 Jul
dust27–130.0319%7 Jul
office10–13-0.019%7 Jul
train9–13-0.025%7 Jul
cache1–13-0.048%7 Jul
train8–130.017%7 Jul
train4–50.0927%7 Jul
cache13–60.044%7 Jul
mirage12–120.0215%7 Jul
nuke12–12-0.0413%6 Jul
train2–13-0.0612%6 Jul
train13–1-0.046%6 Jul
cache4–13-0.058%6 Jul
cache13–50.097%6 Jul
vertigo13–11-0.0116%6 Jul
cache13–10-0.0015%6 Jul
overpass13–80.0321%5 Jul
inferno16–120.0810%5 Jul
nuke15–150.0010%5 Jul
dust213–80.1214%5 Jul
ancient11–13-0.0213%5 Jul
anubis13–9-0.062%5 Jul
mirage13–11-0.028%5 Jul
dust213–11-0.0216%5 Jul
overpass7–13-0.0312%5 Jul
mirage10–130.0111%5 Jul
mirage13–100.013%5 Jul
dust213–160.0215%4 Jul
anubis13–11-0.0618%4 Jul
vertigo9–13-0.0217%4 Jul
train13–3-0.0319%4 Jul
cache6–13-0.0613%4 Jul
cache8–130.1217%4 Jul
ancient13–110.028%4 Jul
nuke13–3-0.006%4 Jul
ancient9–130.019%4 Jul
ancient13–4-0.076%3 Jul
dust213–3-0.0311%3 Jul
nuke4–13-0.0317%3 Jul
mirage13–8-0.018%3 Jul
ancient13–90.0515%3 Jul

Match data via Leetify.

Recent teammates

Milestones

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