SlimJim ♥™

SlimJim ♥™ — CS2 Stats

AU76561199225839066[U:1:1265573338]Steam profile ↗✓ No bans

1,590Tracked matches72%Win rate2023Tracked since
CSDB Rating4.5 DevelopingPositional Player
Premier CS Rating5,772Light Blue band · top ~75.1% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 6 Sep 2026 (60 days ago). Ranks are recorded once per day this page is viewed.

0Premier CS Rating · 5,772 → 5,772
+3Tracked matches · now 1,590
+6.9ppWin rate · 65.5% → 72.4%

Rating over time

Premier CS Rating: 5,772 +773 13 May – 6 Sept · 8 days played
4,7835,772peak 5,77213 May6 Sept
5,772Peak Premier in tracked matches
33Days played since 2026-05-02

Premier CS Rating

  • At peak — 5,772
  • +644 over 90 days
  • Next: Blue band at 10,000 — 4,228 to go
  • Reached: Light Blue band
  • Light Blue band first seen 2026-09-06

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

Share this profile

CSDB.GGSlimJim ♥™PREMIER5,772 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim44
Positioning43
Utility37

0–100 skill scores via Leetify.

Recent form

HOT53–38–9Last 10053%Win rateWWWWLWWWWW

Last 10 vs previous 10: +50pp win rate · +0.03 avg rating · −3.9pp headshot accuracy · +10ms reaction

Win rate up 50pp 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 -0.01
  • Avg headshot accuracy 8%
  • Avg reaction 647ms

Last 10

  • 9–1 · 90% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 9%
  • Avg reaction 647ms

Last 20

  • 13–6–1 · 65% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 11%
  • Avg reaction 642ms

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

Aim4.4
Utility3.7
Positioning4.3
Opening Duels0.2

Limited utility dependence

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

iM

Plays most like iM 83% 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. 655ms 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
Positioning4.3
Utility3.7
Mechanics8.1
Opening Duels0.4
Win Impact10.0

Composite 4.5/10 (Developing), 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-0.02−0.02
first ⅓ avg -0.00 → last ⅓ avg -0.02
Reaction time637ms−8ms
first ⅓ avg 645ms → last ⅓ avg 637ms
Headshot accuracy9.8%−2.1%
first ⅓ avg 11.9% → last ⅓ avg 9.8%

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 · 13–7 · mirage, 30 May →
29%Best headshot accuracy · 0–5 · ancient, 3 May →
422msFastest reaction time · 5–5 · nuke, 9 Jun →
13–1Biggest win · nuke, 8 Jun →

Across the last 100 tracked matches.

Highlights

8Longest win streak
W4Current streak
8–3In matches decided by ≤2 rounds
2Overtime games

Map breakdown

cacheBest map · 73% over 15trainWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
dust2C2511–1444%-0.02
mirageA1710–759%-0.00
cacheS1511–473%0.01
nukeA95–456%0.01
ancientC94–544%-0.02
infernoA74–357%0.01
anubisC52–340%-0.04
trainD51–420%0.01
vertigo—43–175%0.01
office—21–150%0.06
warden—10–10%-0.03
overpass—11–0100%-0.04

Across the last 100 tracked matches.

Skill profile

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

10.1%Headshot accuracy
31.0%Accuracy (enemy spotted)
31.5%Spray accuracy
86.5%Counter-strafing
11.0°Preaim
655msReaction time
33.1%T opening success
26.8%CT opening success
0.64Enemies flashed / flash
2.7%Flash assists
7.70HE damage / grenade
4.42Flashes / 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 10.1319% — below the 15% mark we flag

    Aim Training →
  2. 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 33.0798% — below the 40% mark we flag

Spend your practice time on Train

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

MapScoreRatingHS%Date
mirage13–60.015%29 Sept →
dust213–6-0.005%29 Sept →
nuke13–7-0.0819%29 Sept →
ancient13–40.026%30 Jun →
mirage6–130.037%29 Jun →
dust213–60.078%29 Jun →
inferno13–9-0.0211%29 Jun →
mirage13–110.007%28 Jun →
cache13–4-0.0216%24 Jun →
mirage13–11-0.038%17 Jun →
dust213–10-0.0313%17 Jun →
nuke13–70.0113%16 Jun →
mirage13–90.0011%16 Jun →
dust25–13-0.0612%13 Jun →
ancient13–90.019%13 Jun →
nuke12–12-0.0210%13 Jun →
dust22–13-0.0725%12 Jun →
mirage9–13-0.0111%12 Jun →
mirage6–13-0.0316%12 Jun →
dust23–13-0.1111%11 Jun →
cache13–11-0.105%11 Jun →
inferno8–130.0610%9 Jun →
nuke5–5-0.010%9 Jun →
anubis13–11-0.048%8 Jun →
cache13–30.023%8 Jun →
mirage13–110.0218%8 Jun →
nuke13–10.067%8 Jun →
dust213–8-0.0811%8 Jun →
mirage13–2-0.0311%6 Jun →
dust213–9-0.037%6 Jun →
nuke3–13-0.058%6 Jun →
cache13–7-0.048%6 Jun →
dust21–13-0.098%5 Jun →
office6–130.054%5 Jun →
vertigo13–40.043%5 Jun →
inferno13–30.0218%5 Jun →
dust213–40.0313%5 Jun →
cache13–6-0.0111%5 Jun →
vertigo13–9-0.0218%5 Jun →
cache5–13-0.0211%4 Jun →
dust25–13-0.0211%4 Jun →
inferno13–4-0.0010%4 Jun →
train12–120.014%2 Jun →
cache13–50.0410%2 Jun →
dust210–13-0.0723%2 Jun →
cache9–130.028%1 Jun →
dust213–60.0910%1 Jun →
mirage13–3-0.0413%1 Jun →
train3–130.0110%1 Jun →
mirage12–12-0.0417%31 May →
ancient12–12-0.0510%31 May →
cache13–60.088%30 May →
nuke13–80.088%30 May →
cache4–13-0.0212%30 May →
mirage13–70.1213%30 May →
dust29–13-0.0610%28 May →
warden5–5-0.030%28 May →
mirage9–13-0.0210%28 May →
dust210–130.0611%23 May →
ancient10–130.016%23 May →
vertigo13–100.0513%23 May →
train12–120.0214%23 May →
mirage8–13-0.0918%21 May →
ancient4–12-0.0711%21 May →
mirage13–70.0219%21 May →
anubis10–13-0.0411%17 May →
inferno15–15-0.006%17 May →
anubis0–13-0.0812%16 May →
nuke7–130.014%16 May →
dust27–130.0414%16 May →
ancient13–110.0110%15 May →
dust213–50.0420%15 May →
inferno13–60.015%15 May →
dust28–130.0014%14 May →
anubis14–16-0.027%14 May →
dust213–5-0.0115%14 May →
ancient4–13-0.0411%14 May →
overpass13–11-0.049%13 May →
dust213–11-0.0011%13 May →
inferno10–130.0014%13 May →
mirage13–6-0.034%13 May →
mirage10–130.0714%9 May →
cache13–6-0.016%9 May →
dust212–12-0.009%7 May →
anubis13–9-0.0510%7 May →
ancient13–60.0216%6 May →
dust213–7-0.0720%6 May →
cache13–70.1010%6 May →
cache13–10.0319%6 May →
nuke13–70.0618%6 May →
train5–13-0.0415%6 May →
dust25–13-0.1310%6 May →
dust28–130.0218%4 May →
vertigo9–13-0.049%4 May →
cache12–12-0.028%3 May →
train13–20.052%3 May →
ancient0–5-0.0729%3 May →
cache13–100.039%3 May →
dust212–12-0.025%3 May →
office13–90.0613%2 May →

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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