MLN FROM THE 5TH

MLN FROM THE 5TH — CS2 Stats

IM76561198058188905[U:1:97923177]Steam profile ↗

1,699Tracked matches48%Win rate2020Tracked since
5,485Hours in CS
CSDB Rating5.7 SolidAggressive Rifler
FaceitLevel 8 · 2,100 ELOTop 31.2% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGMLN FROM THE 5THFACEITLevel 8 · 2,100 ELOSTANDINGTop 31.2% of rankedcsdb.gg/stats

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Performance scores

Aim75
Positioning57
Utility38

0–100 skill scores via Leetify.

Recent form

STEADY47512Last 10047%Win rateLWLWLWWWLL

Last 10 vs previous 10: +10pp win rate · -0.00 avg rating

Player DNA

Primary style: Aggressive RiflerTakes opening fights often, backed by a strong aim profile.

Aim7.5
Aggression7.0
Utility3.8
Positioning5.7
Opening Duels2.6
Clutch4.0

Strong CT-side opener

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

ropz

Plays most like ropz 88% playstyle similarity

Most alike: opening-fight frequency, 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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

T-side openings. Opening success drops from 49% on CT to 32% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 568ms 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

Aim7.5
Positioning5.7
Utility3.8
Mechanics6.8
Opening Duels2.6
Win Impact4.4

Composite 5.7/10 (Solid), 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 rating0.01+0.03
first ⅓ avg -0.02 → last ⅓ avg 0.01
Reaction time564ms−2ms
first ⅓ avg 566ms → last ⅓ avg 564ms
Headshot accuracy26.5%−0.5%
first ⅓ avg 27.0% → last ⅓ avg 26.5%

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

0.09Best rating — anubis 13–9
133Biggest win — overpass
5Longest win streak
47In matches decided by ≤2 rounds
7Overtime games

Map breakdown

trainBest map · 67% over 6mirageWeakest map · 29% over 7
MapGradePlayedRecordWin rateAvg rating
infernoB30161453%-0.00
anubisC1971237%-0.00
overpassA106460%0.01
nukeD93633%-0.01
ancientC83538%-0.04
mirageD72529%-0.00
trainS64267%-0.00
dust242250%0.01
vertigo220100%0.02
edin2020%-0.03
ancient_night110100%0.01
jura1010%-0.07
basalt110100%0.04

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (29% over 7). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Lifetime stats

286,564Lifetime kills
1.01K/D
16,092Matches
73.9%Match win rate · Top 1% of tracked players
57.8%Headshot % · Top 25% of tracked players
16.7%Shot accuracy · Top 25% of tracked players
24,074MVPs
5,485Hours (in match)
6,653Bombs planted
2,451Bombs defused

Most-used weapons

AK-47124,223
AWP43,035
P2506,275
Knife4,931
FAMAS4,839
Tec-93,269

Lifetime map wins

22,232inferno
13,352dust2
7,274nuke
6,539train
3,954cbble
2,844vertigo
166italy
146aztec

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

4,801Matches
51%Win rate
0.99Avg K/D
71.2ADR
49%Headshot %

Clutches & streaks

40%1v1 clutch win
15%1v2 clutch win
9Longest win streak

Recent Faceit resultsLWLLL

MapMatchesWin rateAvg K/DAvg kills
Mirage12449%0.9514.7
Anubis11059%0.9314.5
Inferno10459%0.9915.0
Ancient8947%0.8813.4
Vertigo7757%0.8613.8
Nuke7053%0.9414.6
Dust23247%0.7812.8
Overpass3043%0.8112.8

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.

26.2%Headshot accuracy
31.2%Accuracy (enemy spotted)
32.9%Spray accuracy
80.5%Counter-strafing
9.3°Preaim
568msReaction time
32.0%T opening success
49.0%CT opening success
0.53Enemies flashed / flash
4.9%Flash assists
11.21HE damage / grenade
5.93Flashes / 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

    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 32.007% — 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.

29% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategyMirage grenade lineups

Recent matches

MapScoreRatingHS%Date
anubis8–130.0431%20 Jul
inferno16–130.0022%20 Jul
mirage9–13-0.0038%19 Jul
vertigo13–90.0638%13 Jul
anubis11–130.0537%13 Jul
inferno13–80.0122%2 Jul
overpass13–70.0120%2 Jul
anubis13–40.0626%1 Jul
overpass10–130.0139%14 May
nuke7–13-0.0421%11 Apr
mirage9–13-0.0020%11 Apr
anubis13–90.0930%1 Apr
anubis13–50.0215%1 Apr
mirage11–13-0.0621%1 Apr
inferno12–16-0.0224%29 Oct
nuke11–130.0738%27 Oct
nuke7–120.0128%24 Oct
inferno15–150.0115%24 Oct
ancient13–70.0414%17 Oct
ancient13–70.0934%17 Oct
inferno13–80.0629%11 Oct
inferno7–13-0.0235%10 Oct
ancient3–13-0.1227%7 Oct
overpass4–130.0329%20 Sept
inferno13–5-0.0214%5 Sept
inferno5–13-0.0513%3 Sept
inferno13–70.0130%31 Aug
ancient_night13–110.0120%31 Aug
overpass9–130.0317%29 Aug
mirage13–100.0237%23 Aug
anubis5–130.0543%22 Aug
ancient11–13-0.0425%16 Aug
nuke13–10-0.0420%16 Aug
inferno13–9-0.0228%9 Aug
overpass13–4-0.0130%9 Aug
inferno13–10-0.0029%8 Aug
anubis8–13-0.0342%8 Aug
overpass19–150.0433%6 Aug
mirage9–130.0334%6 Aug
nuke8–130.0226%6 Aug
inferno13–7-0.0126%6 Aug
overpass13–8-0.0125%6 Aug
mirage22–200.0231%26 Jul
anubis13–60.0220%26 Jul
nuke13–50.0347%26 Jul
inferno13–16-0.0630%26 Jul
nuke5–13-0.1119%12 Jul
anubis9–13-0.0421%12 Jul
inferno5–13-0.1211%12 Jul
inferno7–130.0153%28 Jun
ancient5–13-0.0612%28 Jun
inferno13–70.0524%28 Jun
nuke7–130.0126%28 Jun
inferno13–70.0026%28 Jun
train13–90.0532%28 Jun
inferno9–130.0320%24 Jun
nuke13–8-0.0617%24 Jun
inferno13–100.0633%21 Jun
anubis16–130.0331%20 Jun
anubis10–13-0.0042%13 Jun
inferno10–130.0325%13 Jun
anubis13–40.0216%13 Jun
ancient13–7-0.0830%9 Jun
train13–110.0235%8 Jun
inferno13–60.0531%8 Jun
overpass13–50.0728%10 May
jura9–13-0.0733%10 May
anubis7–13-0.0417%9 May
inferno7–13-0.0732%9 May
inferno5–20.0422%3 May
overpass2–13-0.1010%30 Apr
mirage9–13-0.0225%4 Apr
anubis13–110.0023%4 Apr
inferno13–7-0.0135%30 Mar
anubis11–13-0.0624%30 Mar
inferno9–130.0321%30 Mar
anubis7–13-0.0720%30 Mar
dust28–130.0039%21 Mar
ancient1–13-0.0650%7 Mar
anubis5–13-0.0621%28 Feb
inferno13–50.0218%13 Feb
anubis7–13-0.0232%30 Jan
ancient7–13-0.0619%28 Jan
inferno4–13-0.0237%23 Jan
dust24–13-0.0427%16 Jan
vertigo13–9-0.0131%16 Jan
inferno5–130.0128%9 Jan
dust213–80.0136%9 Jan
anubis7–13-0.0621%3 Jan
dust213–70.0745%19 Dec
overpass13–30.0821%19 Dec
inferno13–10-0.0426%8 Dec
inferno11–13-0.0227%5 Dec
basalt13–90.0425%25 Nov
edin12–12-0.0233%25 Nov
train9–13-0.0629%25 Nov
edin11–13-0.0419%24 Nov
train13–90.0225%24 Nov
train13–90.0230%16 Nov
train6–13-0.0722%16 Nov

Match data via Leetify.

Recent teammates

Milestones

2K ELO1,000 Matches
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