SleepyLoggie

SleepyLoggie — CS2 Stats

US76561199024695224[U:1:1064429496]Steam profile ↗✓ No bans

48Tracked matches41%Win rate2025Tracked since
CSDB Rating1.4 LearningPositional Player
Ladder ranks via Leetify

Performance scores

Aim3
Positioning34
Utility21

0–100 skill scores via Leetify.

Recent form

COLD13–32–2Last 4728%Win rateLLWWLLLLLL

Last 10 vs previous 10: −30pp win rate · −0.01 avg rating · +1.5pp headshot accuracy · +14ms reaction

Win rate down 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

  • 2–3 · 40% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 10%
  • Avg reaction 811ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 11%
  • Avg reaction 759ms

Last 20

  • 7–13 · 35% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 10%
  • Avg reaction 752ms

Newest first, from the last 47 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Positional Player — Positioning stands above the rest of this profile (+1.6 against its own average).

Aim0.3
Utility2.1
Positioning3.4
Opening Duels0.0

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

donk

Plays most like donk 58% 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. 755ms 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

Aim0.3
Positioning3.4
Utility2.1
Mechanics0.6
Opening Duels0.0
Win Impact2.1

Composite 1.4/10 (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+0.03
first ⅓ avg -0.08 → last ⅓ avg -0.05
Reaction time747ms−121ms
first ⅓ avg 869ms → last ⅓ avg 747ms
Headshot accuracy10.5%−5.0%
first ⅓ avg 15.6% → last ⅓ avg 10.5%

Rolling 5-match average across the last 47 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.08Best match rating · 9–0 · overpass, 26 Nov →
44%Best headshot accuracy · 9–13 · inferno, 13 Dec →
523msFastest reaction time · 13–5 · mirage, 23 May →
13–1Biggest win · mirage, 13 Dec →

Across the last 47 tracked matches.

Highlights

3Longest win streak
L2Current streak
2–3In matches decided by ≤2 rounds

Map breakdown

dust2Best map · 31% over 13infernoWeakest map · 14% over 7
MapGradePlayedRecordWin rateAvg rating
mirageD144–1029%-0.06
dust2D134–931%-0.06
infernoD71–614%-0.08
overpassD51–420%-0.06
nuke—41–325%-0.08
cache—42–250%-0.06

Across the last 47 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (14% over 7). Start with the 6 essential Inferno 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.

12.1%Headshot accuracy
24.9%Accuracy (enemy spotted)
20.0%Spray accuracy
52.7%Counter-strafing
15.4°Preaim
755msReaction time
22.9%T opening success
29.1%CT opening success
0.37Enemies flashed / flash
0.9%Flash assists
3.74HE damage / grenade
5.07Flashes / 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 15.3845° — above the 12° mark we flag

    Aim Training →
  2. 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 12.1166% — below the 15% mark we flag

    Aim Training →
  3. Best CS2 Settings

    Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.

    Reaction time 755.4218ms — above the 700ms mark we flag

    Aim Training →
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.

14% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage5–13-0.035%25 Jun →
overpass1–13-0.077%25 Jun →
mirage13–3-0.0313%31 May →
nuke13–8-0.0612%31 May →
mirage10–13-0.1013%31 May →
mirage8–13-0.0710%31 May →
dust28–13-0.0614%31 May →
mirage7–13-0.0510%27 May →
nuke4–13-0.0711%27 May →
dust26–13-0.0713%23 May →
mirage13–50.038%23 May →
dust213–11-0.0412%23 May →
mirage11–13-0.110%21 May →
dust28–13-0.0414%21 May →
dust213–4-0.0016%21 May →
dust213–70.017%21 May →
cache4–13-0.073%21 May →
cache13–4-0.065%21 May →
nuke2–13-0.087%13 May →
dust24–13-0.0820%13 May →
cache7–13-0.0319%13 May →
cache13–8-0.0610%13 May →
inferno9–13-0.1144%13 Dec →
mirage13–1-0.056%13 Dec →
inferno13–8-0.0111%29 Nov →
mirage13–11-0.0815%29 Nov →
dust212–12-0.1210%27 Nov →
dust29–13-0.0815%27 Nov →
dust213–7-0.0611%27 Nov →
mirage10–13-0.0518%27 Nov →
dust25–13-0.0118%27 Nov →
inferno11–13-0.086%27 Nov →
overpass9–00.080%26 Nov →
inferno6–9-0.0617%26 Nov →
nuke3–13-0.090%20 Nov →
overpass8–13-0.098%20 Nov →
overpass3–9-0.1525%12 Nov →
inferno6–9-0.1317%12 Nov →
mirage10–13-0.088%11 Nov →
mirage8–13-0.0713%10 Nov →
inferno9–13-0.0727%10 Nov →
mirage11–13-0.1010%7 Nov →
dust29–13-0.0825%7 Nov →
overpass4–13-0.0625%7 Nov →
dust212–12-0.0920%7 Nov →
inferno10–13-0.0727%4 Nov →
mirage5–13-0.1011%4 Nov →

Match data via Leetify.

Recent teammates

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

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