Slime

Slime — CS2 Stats

XK76561198134524320[U:1:174258592]Steam profile ↗✓ No bans

1,722Tracked matches30%Win rate2022Tracked since
CSDB Rating3.2 LearningSupport
Ladder ranks via Leetify

Performance scores

Aim46
Positioning41
Utility45

0–100 skill scores via Leetify.

Recent form

COLD39–61Last 10039%Win rateLLWLLWLLLL

Last 10 vs previous 10: −20pp win rate · −0.01 avg rating · +4.1pp headshot accuracy · +38ms reaction

Win rate down 20pp 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

  • 1–4 · 20% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 21%
  • Avg reaction 606ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 19%
  • Avg reaction 642ms

Last 20

  • 6–14 · 30% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 17%
  • Avg reaction 623ms

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).

Aim4.6
Utility4.5
Positioning4.1
Opening Duels3.1
Clutch2.8

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 81% 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. 628ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 67% 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

Aim4.6
Positioning4.1
Utility4.5
Mechanics3.7
Opening Duels1.5
Win Impact0.0

Composite 3.2/10 (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-0.04+0.00
first ⅓ avg -0.04 → last ⅓ avg -0.04
Reaction time627ms+6ms
first ⅓ avg 622ms → last ⅓ avg 627ms
Headshot accuracy17.7%−0.1%
first ⅓ avg 17.8% → last ⅓ avg 17.7%

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

0.06Best match rating · 13–10 · mirage, 23 Aug →
50%Best headshot accuracy · 4–11 · vertigo, 3 Aug →
438msFastest reaction time · 13–11 · inferno, 20 Jun →
13–2Biggest win · ancient, 28 Feb →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L2Current streak
12–13In matches decided by ≤2 rounds
10Overtime games

Map breakdown

mirageBest map · 55% over 22infernoWeakest map · 32% over 22
MapGradePlayedRecordWin rateAvg rating
ancientC3212–2038%-0.04
infernoD227–1532%-0.04
mirageA2212–1055%-0.03
dust2C156–940%-0.04
vertigo—41–325%-0.02
anubis—20–20%-0.07
nuke—21–150%-0.03
overpass—10–10%-0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (32% over 22). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

1,449Matches
50%Win rate
0.74Avg K/D
61.1ADR
44%Headshot %

Clutches & streaks

34%1v1 clutch win
13%1v2 clutch win
15Longest win streak

Recent Faceit resultsLWWLL

MapMatchesWin rateAvg K/DAvg kills
Mirage39055%0.7511.7
Ancient25653%0.7011.4
Dust217948%0.6711.3
Inferno14444%0.7211.9
Vertigo4250%0.7412.0
Anubis3231%0.6811.1
Nuke1844%0.8414.8
Train1127%0.9211.2

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.

18.0%Headshot accuracy
30.3%Accuracy (enemy spotted)
38.6%Spray accuracy
66.8%Counter-strafing
11.1°Preaim
628msReaction time
35.9%T opening success
35.9%CT opening success
0.50Enemies flashed / flash
3.7%Flash assists
6.94HE damage / grenade
5.58Flashes / 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 35.8934% — below the 40% mark we flag

Spend your practice time on Inferno

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

32% win rate across 22 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno13–160.0110%11 Sept →
dust211–13-0.0631%16 Aug →
mirage13–6-0.0118%16 Aug →
inferno7–13-0.0430%2 Aug →
mirage9–13-0.0716%12 Jul →
mirage13–6-0.029%12 Jul →
inferno10–13-0.0427%12 Jul →
dust212–16-0.1025%27 Jun →
ancient6–13-0.039%27 Jun →
ancient5–13-0.0117%5 Jun →
ancient7–13-0.0520%29 May →
anubis7–13-0.058%22 May →
mirage13–7-0.0013%8 May →
dust210–13-0.0112%5 May →
ancient13–9-0.0024%17 Apr →
ancient6–13-0.0914%17 Apr →
ancient13–6-0.0616%5 Apr →
ancient9–13-0.0611%26 Mar →
ancient6–13-0.0523%26 Mar →
dust213–100.0513%20 Mar →
ancient13–5-0.0229%7 Mar →
mirage8–13-0.0820%2 Mar →
overpass11–13-0.0113%1 Mar →
ancient13–2-0.0418%28 Feb →
inferno13–70.0229%22 Feb →
dust211–13-0.0115%21 Feb →
mirage10–13-0.0418%14 Feb →
dust29–13-0.0621%14 Feb →
ancient11–13-0.0120%31 Jan →
ancient6–13-0.0515%31 Jan →
ancient16–12-0.0614%31 Jan →
dust213–5-0.0613%31 Jan →
dust213–10-0.0515%20 Dec →
mirage2–13-0.0533%27 Aug →
inferno5–13-0.0628%9 Aug →
nuke12–160.0318%2 Aug →
mirage13–9-0.0710%28 Jul →
mirage13–9-0.0318%23 Jul →
inferno13–11-0.058%20 Jun →
dust26–13-0.1110%13 Jun →
dust213–60.0417%11 Jun →
ancient8–13-0.039%10 Jun →
ancient6–13-0.0911%29 May →
ancient13–90.0011%20 May →
inferno6–13-0.0913%6 May →
inferno14–16-0.0511%1 May →
dust25–13-0.019%24 Apr →
ancient22–25-0.0416%18 Apr →
ancient9–13-0.0321%11 Apr →
mirage11–13-0.0314%11 Apr →
ancient13–11-0.027%7 Feb →
ancient11–13-0.089%7 Feb →
ancient7–13-0.0317%2 Feb →
ancient8–13-0.069%31 Jan →
anubis3–13-0.095%16 Jan →
inferno8–13-0.0315%16 Jan →
ancient2–13-0.0835%30 Dec →
mirage13–110.0117%29 Dec →
inferno13–11-0.0410%29 Dec →
mirage13–11-0.0412%27 Dec →
dust213–10-0.0632%27 Dec →
inferno16–130.0018%25 Dec →
ancient11–13-0.0915%19 Dec →
ancient7–13-0.0216%14 Dec →
inferno8–13-0.0210%14 Dec →
ancient13–30.0520%27 Nov →
mirage11–13-0.0521%11 Oct →
mirage13–11-0.0317%6 Oct →
inferno14–16-0.0410%21 Sept →
ancient10–13-0.0521%21 Sept →
mirage7–12-0.0629%7 Sept →
mirage4–130.0313%6 Sept →
mirage6–13-0.0626%6 Sept →
dust213–50.0420%5 Sept →
mirage13–100.0632%23 Aug →
inferno6–13-0.1225%21 Aug →
inferno13–110.0218%16 Aug →
mirage13–10-0.0417%14 Aug →
dust26–13-0.107%7 Aug →
nuke13–8-0.0822%7 Aug →
inferno13–4-0.0225%6 Aug →
dust27–13-0.0223%5 Aug →
ancient13–11-0.0811%4 Aug →
mirage13–50.0514%4 Aug →
inferno6–13-0.0820%3 Aug →
vertigo4–11-0.0350%3 Aug →
inferno11–13-0.0417%1 Aug →
inferno13–11-0.024%20 Jul →
ancient13–11-0.0615%5 Jul →
inferno10–13-0.054%5 Jul →
inferno14–16-0.086%28 Jun →
vertigo9–13-0.1013%6 Jun →
mirage13–110.0016%6 Jun →
ancient7–13-0.0439%22 May →
vertigo9–130.0016%19 Apr →
inferno6–13-0.0315%6 Mar →
ancient13–11-0.047%6 Mar →
mirage11–13-0.0612%6 Mar →
ancient16–12-0.0813%6 Mar →
vertigo13–50.0511%6 Mar →

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 →

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