Mort

Mort — CS2 Stats

76561198168048248[U:1:207782520]Steam profile ↗✓ No bans

137Tracked matches54%Win rate2025Tracked since
CSDB Rating6.3 SolidSupport
Premier CS Rating19,470Top 50% of 210,367 CSDB-tracked playersPurple band · top ~10.6% of ranked players (population est.)
CSDB Leaderboard#92422 of 257523 tracked
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 22 Sep 2026 (34 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 137 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 19,470 +3,138 21 Nov – 22 Sept · 33 days played
15,00020,581peak 20,58121 Nov22 Sept
20,848Peak Premier in tracked matches
40Days played since 2025-11-21

Premier CS Rating

  • 1,111 below peak (20,581)
  • 0 over 90 days
  • Next: Pink band at 20,000 — 530 to go
  • Reached: Pink band · Purple band · Blue band · Light Blue band
  • Purple band first seen 2026-09-22
  • Blue band first seen 2026-09-22

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

Share this profile

CSDB.GGMortPREMIER19,470 · Purple bandcsdb.gg/stats

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Performance scores

Aim77
Positioning53
Utility65

0–100 skill scores via Leetify.

Recent form

STEADY50–47–3Last 10050%Win rateWWWLWLLWWL

Last 10 vs previous 10: +30pp win rate · +0.02 avg rating · −4.5pp headshot accuracy · −74ms reaction

Win rate up 30pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 4–1 · 80% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 23%
  • Avg reaction 460ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating 0.04
  • Avg headshot accuracy 21%
  • Avg reaction 561ms

Last 20

  • 9–11 · 45% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 23%
  • Avg reaction 598ms

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: Support — Utility contribution stands above the rest of this profile (+0.9 against its own average).

Aim7.7
Utility6.5
Positioning5.3
Opening Duels4.9

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

device

Plays most like device 85% 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. 603ms 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

Aim7.7
Positioning5.3
Utility6.5
Mechanics6.4
Opening Duels3.8
Win Impact6.2

Composite 6.3/10 (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 rating0.02−0.00
first ⅓ avg 0.02 → last ⅓ avg 0.02
Reaction time590ms−18ms
first ⅓ avg 608ms → last ⅓ avg 590ms
Headshot accuracy20.0%+0.8%
first ⅓ avg 19.3% → last ⅓ avg 20.0%

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

0.12Best match rating · 13–1 · mirage, 25 Jun →
44%Best headshot accuracy · 13–2 · cache, 10 Jun →
453msFastest reaction time · 2–13 · inferno, 5 Feb →
13–1Biggest win · mirage, 25 Jun →

Across the last 100 tracked matches.

Highlights

5Longest win streak
W3Current streak
6–7In matches decided by ≤2 rounds
10Overtime games

Map breakdown

overpassBest map · 67% over 9ancientWeakest map · 42% over 12
MapGradePlayedRecordWin rateAvg rating
mirageB3416–1847%0.02
infernoB199–1047%0.01
ancientC125–742%0.00
nukeA127–558%0.04
overpassS96–367%0.01
dust2C73–443%0.03
train—31–233%0.01
anubis—22–0100%0.05
office—10–10%0.00
cache—11–0100%0.10

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (42% over 12). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

20.5%Headshot accuracy
36.5%Accuracy (enemy spotted)
41.0%Spray accuracy
78.7%Counter-strafing
9.4°Preaim
603msReaction time
43.8%T opening success
46.6%CT opening success
0.59Enemies flashed / flash
5.0%Flash assists
9.31HE damage / grenade
12.68Flashes / match

Recommended for you

Spend your practice time on Ancient

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

42% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategy →Ancient grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage13–10.1225%25 Jun →
mirage13–6-0.0221%16 Jun →
mirage13–50.0522%16 Jun →
office0–20.000%10 Jun →
cache13–20.1044%10 Jun →
mirage8–13-0.0218%31 May →
ancient9–13-0.0216%31 May →
nuke13–110.0723%31 May →
mirage13–90.0221%28 May →
nuke9–130.0818%13 May →
inferno5–130.0016%13 May →
overpass6–13-0.0318%13 May →
mirage6–130.0230%13 May →
nuke13–110.0521%13 May →
overpass13–70.0430%13 May →
mirage2–130.0133%4 May →
mirage11–13-0.0125%2 Apr →
inferno5–13-0.0433%2 Apr →
mirage8–130.0524%31 Mar →
ancient13–90.0422%31 Mar →
nuke8–13-0.0018%31 Mar →
nuke16–140.0011%22 Mar →
mirage15–150.0216%22 Mar →
mirage13–9-0.0026%22 Mar →
inferno15–15-0.0316%15 Mar →
inferno13–110.0319%12 Mar →
overpass13–60.0616%2 Mar →
overpass13–9-0.0210%2 Mar →
nuke10–13-0.0013%22 Feb →
inferno13–110.0215%22 Feb →
inferno13–30.1015%22 Feb →
ancient13–70.0312%18 Feb →
nuke13–80.0914%18 Feb →
mirage13–60.026%18 Feb →
ancient3–13-0.0613%16 Feb →
overpass13–70.0320%16 Feb →
ancient13–90.0420%16 Feb →
overpass11–2-0.0315%15 Feb →
mirage5–13-0.0018%15 Feb →
inferno5–13-0.0120%15 Feb →
mirage13–80.0716%15 Feb →
mirage5–13-0.0814%12 Feb →
mirage15–150.008%8 Feb →
anubis13–3-0.0110%8 Feb →
ancient13–80.0611%8 Feb →
overpass3–13-0.037%8 Feb →
dust25–13-0.0112%8 Feb →
inferno13–10-0.0120%8 Feb →
mirage14–16-0.0414%5 Feb →
mirage4–13-0.0415%5 Feb →
inferno2–13-0.088%5 Feb →
inferno13–50.069%4 Feb →
dust213–90.0420%4 Feb →
inferno6–13-0.0215%4 Feb →
inferno14–16-0.0016%1 Feb →
mirage2–13-0.0613%31 Jan →
mirage13–80.0110%31 Jan →
inferno13–100.0122%29 Jan →
overpass4–130.048%29 Jan →
anubis13–100.1117%29 Jan →
mirage12–40.0527%27 Jan →
nuke13–50.0516%27 Jan →
dust27–130.0126%11 Jan →
nuke13–70.0012%2 Jan →
mirage9–130.0713%2 Jan →
overpass13–100.0117%2 Jan →
dust210–130.0521%2 Jan →
ancient16–120.0524%2 Jan →
inferno1–13-0.0726%2 Jan →
train13–60.0316%28 Dec →
mirage7–130.0320%28 Dec →
ancient11–130.0112%28 Dec →
mirage16–120.068%28 Dec →
inferno6–13-0.0013%26 Dec →
mirage6–130.0021%26 Dec →
nuke9–130.0123%22 Dec →
mirage5–130.0515%22 Dec →
inferno8–130.0115%22 Dec →
mirage13–110.0331%21 Dec →
inferno13–90.0519%21 Dec →
inferno13–70.0921%21 Dec →
ancient7–13-0.0218%21 Dec →
dust213–90.0519%21 Dec →
inferno13–60.0427%21 Dec →
mirage13–30.0923%20 Dec →
mirage13–80.0621%15 Dec →
dust213–10.0416%15 Dec →
ancient10–13-0.0310%14 Dec →
dust29–130.0331%7 Dec →
mirage13–10-0.0014%4 Dec →
nuke13–160.0317%1 Dec →
mirage13–100.0720%26 Nov →
nuke13–40.119%26 Nov →
train7–13-0.0233%26 Nov →
mirage13–16-0.0221%24 Nov →
ancient11–13-0.0214%24 Nov →
mirage2–130.043%24 Nov →
ancient9–13-0.0234%21 Nov →
mirage13–9-0.0116%21 Nov →
train11–130.0327%21 Nov →

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 →

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