ProtectedLeaf

ProtectedLeaf — CS2 Stats

US76561198297413739[U:1:337148011]Steam profile ↗✓ No bans

82Tracked matches29%Win rate2020Tracked since
CSDB Rating3.6 LearningPositional Player
Ladder ranks via Leetify

Performance scores

Aim42
Positioning45
Utility24

0–100 skill scores via Leetify.

Recent form

COLD26–44–7Last 7734%Win rateLLLLLWWWLL

Last 10 vs previous 10: +10pp win rate · −0.02 avg rating · +4.9pp headshot accuracy · +100ms 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

  • 0–5 · 0% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 22%
  • Avg reaction 762ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 21%
  • Avg reaction 807ms

Last 20

  • 5–13–2 · 25% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 19%
  • Avg reaction 757ms

Newest first, from the last 77 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 (+2.1 against its own average).

Aim4.2
Utility2.4
Positioning4.5
Opening Duels0.3

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 81% 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

T-side openings. Opening success drops from 37% on CT to 19% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 738ms 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

Aim4.2
Positioning4.5
Utility2.4
Mechanics6.9
Opening Duels0.9
Win Impact0.0

Composite 3.6/10 (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-0.03−0.02
first ⅓ avg -0.01 → last ⅓ avg -0.03
Reaction time754ms+54ms
first ⅓ avg 700ms → last ⅓ avg 754ms
Headshot accuracy19.9%+2.2%
first ⅓ avg 17.8% → last ⅓ avg 19.9%

Rolling 5-match average across the last 77 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.08Best match rating · 13–3 · dust2, 8 Jul →
40%Best headshot accuracy · 13–9 · cache, 3 Jul →
380msFastest reaction time · 10–16 · inferno, 25 Sept →
13–2Biggest win · mirage, 18 Jul →

Across the last 77 tracked matches.

Highlights

4Longest win streak
L5Current streak
11Overtime games

Map breakdown

ancientBest map · 60% over 5infernoWeakest map · 22% over 9
MapGradePlayedRecordWin rateAvg rating
mirageD267–1927%-0.04
cacheC166–1038%-0.03
dust2C135–838%-0.02
infernoD92–722%-0.04
nukeC52–340%-0.03
ancientA53–260%-0.01
anubis—31–233%-0.01

Across the last 77 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (22% over 9). 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.

19.1%Headshot accuracy
29.2%Accuracy (enemy spotted)
29.9%Spray accuracy
81.2%Counter-strafing
10.2°Preaim
738msReaction time
19.0%T opening success
37.2%CT opening success
0.39Enemies flashed / flash
5.4%Flash assists
6.30HE damage / grenade
2.88Flashes / 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 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 737.6661ms — above the 700ms mark we flag

    Aim Training →
  2. 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 0.3858 — below the 0.5 mark we flag

    Grenade Lineups →
  3. 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 19.0202% — 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.

22% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage13–16-0.0423%25 Aug →
mirage8–13-0.0624%17 Aug →
mirage1–13-0.0430%16 Aug →
nuke5–13-0.0127%24 Jul →
cache4–13-0.077%22 Jul →
cache13–60.0135%19 Jul →
mirage13–10-0.0818%18 Jul →
mirage13–2-0.0225%18 Jul →
cache3–13-0.0520%18 Jul →
inferno8–13-0.115%15 Jul →
inferno6–130.0415%14 Jul →
mirage7–130.0116%14 Jul →
mirage12–12-0.0412%11 Jul →
inferno10–13-0.0323%11 Jul →
ancient12–12-0.0620%11 Jul →
mirage4–13-0.0324%10 Jul →
ancient16–12-0.0110%9 Jul →
mirage8–13-0.0716%9 Jul →
cache13–10-0.0616%9 Jul →
cache10–13-0.0413%9 Jul →
anubis13–30.0328%8 Jul →
cache13–6-0.0324%8 Jul →
dust213–30.0823%8 Jul →
nuke1–13-0.0914%7 Jul →
inferno6–13-0.0631%7 Jul →
cache6–13-0.0319%7 Jul →
dust24–13-0.058%7 Jul →
mirage10–13-0.0525%7 Jul →
cache10–13-0.0223%7 Jul →
mirage10–13-0.0710%7 Jul →
mirage6–13-0.055%6 Jul →
mirage3–13-0.0625%6 Jul →
ancient13–40.0721%6 Jul →
mirage13–9-0.0217%6 Jul →
inferno13–3-0.1325%6 Jul →
ancient0–8-0.0533%5 Jul →
dust22–13-0.0718%5 Jul →
cache13–60.0225%5 Jul →
mirage10–13-0.0815%4 Jul →
anubis8–13-0.0718%4 Jul →
mirage4–13-0.0933%4 Jul →
mirage13–11-0.0722%3 Jul →
cache13–9-0.0540%3 Jul →
mirage9–13-0.0425%3 Jul →
inferno12–12-0.0121%3 Jul →
ancient13–3-0.0224%3 Jul →
cache12–12-0.0614%3 Jul →
dust27–13-0.0926%2 Jul →
mirage7–13-0.1011%2 Jul →
mirage13–40.0013%30 Jun →
dust213–6-0.0115%30 Jun →
nuke13–2-0.0318%29 Jun →
cache13–2-0.0211%29 Jun →
mirage12–12-0.0718%29 Jun →
dust27–13-0.0511%16 Jun →
nuke6–13-0.0318%13 Jun →
cache7–13-0.0513%13 Jun →
inferno13–5-0.0312%13 Jun →
anubis6–130.0017%13 Jun →
dust213–8-0.0218%9 Jun →
dust213–90.0219%9 Jun →
cache11–13-0.0423%5 Jun →
dust212–12-0.0122%5 Jun →
dust27–160.0315%25 Sept →
cache3–16-0.0216%24 Sept →
mirage9–40.0411%24 Sept →
mirage8–80.0225%24 Sept →
mirage2–90.0123%24 Sept →
mirage2–16-0.1323%24 Apr →
mirage9–20.0629%2 May →
dust28–16-0.0716%3 Dec →
dust211–160.0016%26 Jul →
cache9–160.0024%20 Jun →
nuke16–80.0014%4 Apr →
inferno2–120.0026%14 Jan →
inferno10–160.009%25 Sept →
dust216–70.0016%15 Sept →

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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