Yung Kid Tickler

Yung Kid Tickler — CS2 Stats

76561199644892551[U:1:1684626823]Steam profile ↗✓ No bans

495Tracked matches53%Win rate2024Tracked since
CSDB Rating4.4 DevelopingPositional Player
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 2,107 -33 27 Sept – 1 Jul · 24 days played
1,0002,991peak 2,99127 Sept1 Jul
3,197Peak Premier in tracked matches
38Days played since 2025-09-27

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

Performance scores

Aim37
Positioning52
Utility40

0–100 skill scores via Leetify.

Recent form

HOT40–58–2Last 10040%Win rateWLWWLLWWWW

Last 10 vs previous 10: +10pp win rate · −0.01 avg rating · +0.7pp headshot accuracy · +51ms reaction

Win rate +10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 24%
  • Avg reaction 661ms

Last 10

  • 7–3 · 70% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 21%
  • Avg reaction 715ms

Last 20

  • 13–7 · 65% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 21%
  • Avg reaction 690ms

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 against its own average).

Aim3.7
Utility4.0
Positioning5.2
Opening Duels3.4

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 69% playstyle similarity

Most alike: positioning profile, utility contribution.

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. 708ms 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

Aim3.7
Positioning5.2
Utility4.0
Mechanics5.6
Opening Duels2.3
Win Impact6.1

Composite 4.4/10 (Developing), 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-0.01−0.00
first ⅓ avg -0.00 → last ⅓ avg -0.01
Reaction time695ms+50ms
first ⅓ avg 645ms → last ⅓ avg 695ms
Headshot accuracy19.8%−0.7%
first ⅓ avg 20.5% → last ⅓ avg 19.8%

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

0.19Best match rating · 13–4 · dust2, 26 Jun →
57%Best headshot accuracy · 5–13 · train, 28 Feb →
406msFastest reaction time · 4–13 · dust2, 28 Feb →
13–0Biggest win · dust2, 27 Sept →

Across the last 100 tracked matches.

Highlights

4Longest win streak
9–8In matches decided by ≤2 rounds
6Overtime games

Map breakdown

ancientBest map · 57% over 14infernoWeakest map · 17% over 12
MapGradePlayedRecordWin rateAvg rating
dust2C4418–2641%0.01
ancientA148–657%-0.01
nukeD134–931%-0.01
infernoD122–1017%0.00
cache—42–250%-0.05
overpass—42–250%-0.00
anubis—42–250%0.02
train—20–20%-0.03
mirage—10–10%0.04
office—11–0100%-0.03
palacio—11–0100%-0.02

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (17% over 12). 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.

20.6%Headshot accuracy
29.7%Accuracy (enemy spotted)
29.8%Spray accuracy
75.1%Counter-strafing
12.1°Preaim
708msReaction time
36.7%T opening success
42.0%CT opening success
0.49Enemies flashed / flash
6.1%Flash assists
9.26HE damage / grenade
12.50Flashes / 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 12.0548° — above the 12° mark we flag

    Aim Training →
  2. 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 707.6947ms — above the 700ms mark we flag

    Aim Training →
  3. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.4902 — below the 0.5 mark we flag

    Grenade Lineups →
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.

17% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
cache13–10-0.0126%31 Jul →
dust25–13-0.1118%31 Jul →
cache13–9-0.0032%30 Jul →
inferno13–10-0.0712%30 Jul →
dust24–13-0.0332%26 Jul →
dust210–130.1022%26 Jul →
dust213–60.1321%19 Jul →
dust213–20.0129%19 Jul →
dust213–110.0022%19 Jul →
nuke13–7-0.030%11 Jul →
dust210–130.0115%11 Jul →
cache7–13-0.1216%11 Jul →
ancient13–10-0.0214%1 Jul →
nuke13–110.0526%1 Jul →
dust25–13-0.0042%26 Jun →
dust213–40.1925%26 Jun →
dust213–8-0.0315%26 Jun →
dust213–6-0.0112%26 Jun →
dust21–130.0419%6 Jun →
ancient13–9-0.0122%23 May →
overpass5–20.0412%23 May →
inferno4–13-0.0214%23 May →
dust20–4-0.070%10 May →
nuke6–13-0.1012%30 Apr →
cache3–13-0.0811%30 Apr →
ancient13–11-0.0519%19 Apr →
dust24–13-0.0518%19 Apr →
ancient13–14-0.0727%17 Apr →
inferno9–13-0.0437%11 Apr →
dust213–10.1824%11 Apr →
mirage1–130.0436%11 Apr →
dust20–2-0.090%11 Apr →
dust213–90.0024%4 Apr →
dust211–13-0.0914%4 Apr →
inferno7–11-0.1120%3 Apr →
dust22–130.0316%3 Apr →
ancient15–15-0.0218%21 Mar →
inferno5–13-0.0515%21 Mar →
nuke4–13-0.0238%21 Mar →
nuke13–90.0527%21 Mar →
dust23–13-0.0314%21 Mar →
dust213–50.1018%14 Mar →
nuke8–13-0.0620%14 Mar →
dust213–20.0350%28 Feb →
train5–130.0157%28 Feb →
dust212–120.0216%28 Feb →
dust21–130.0733%28 Feb →
dust213–5-0.0357%28 Feb →
dust27–13-0.0415%28 Feb →
anubis7–130.0314%28 Feb →
dust26–13-0.057%28 Feb →
dust24–13-0.0025%28 Feb →
ancient13–5-0.0027%24 Feb →
anubis1–13-0.0625%24 Feb →
nuke10–13-0.0220%17 Feb →
dust213–70.0616%17 Feb →
inferno4–13-0.0617%17 Feb →
anubis13–110.0016%14 Feb →
inferno1–10.1520%14 Feb →
nuke11–13-0.0226%14 Feb →
ancient13–70.037%13 Feb →
anubis16–120.1125%13 Feb →
dust20–13-0.0621%13 Feb →
ancient13–110.0016%13 Feb →
dust213–20.1012%12 Feb →
dust213–110.0221%11 Feb →
overpass13–90.0413%11 Feb →
dust210–130.0313%11 Feb →
nuke9–13-0.0233%6 Feb →
ancient13–30.0618%6 Feb →
dust21–12-0.035%2 Feb →
inferno13–70.0631%2 Feb →
overpass13–16-0.0024%2 Feb →
ancient13–70.0219%2 Feb →
dust216–14-0.0123%1 Feb →
overpass7–13-0.080%1 Feb →
dust213–90.0616%1 Feb →
nuke2–13-0.0833%1 Feb →
nuke8–130.0645%1 Feb →
dust213–9-0.0122%8 Nov →
ancient10–13-0.0133%8 Nov →
nuke11–130.0013%23 Oct →
dust28–13-0.0127%16 Oct →
ancient9–13-0.0422%16 Oct →
dust25–130.0222%15 Oct →
dust210–130.0111%15 Oct →
dust28–13-0.0410%10 Oct →
ancient9–130.0411%6 Oct →
dust25–13-0.0840%2 Oct →
inferno8–13-0.0020%2 Oct →
office13–5-0.0320%2 Oct →
palacio13–11-0.0218%2 Oct →
dust25–13-0.1313%1 Oct →
inferno11–130.0914%29 Sept →
ancient7–13-0.110%27 Sept →
train8–13-0.0611%27 Sept →
nuke16–140.0533%27 Sept →
inferno5–130.0827%27 Sept →
inferno11–130.0230%27 Sept →
dust213–00.0420%27 Sept →

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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