pablo

pablo — CS2 Stats

76561199229276328[U:1:1269010600]Steam profile ↗✓ No bans

133Tracked matches33%Win rate2023Tracked since
CSDB Rating1.2 LearningPositional Player
Premier CS Rating3,903Grey band · top ~83.4% of ranked players (population est.)
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 23 Sep 2026 (53 days ago). Ranks are recorded once per day this page is viewed.

No change since then — still 133 tracked matches. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 3,903 -571 15 Mar – 23 Sept · 17 days played
3,3725,115peak 5,11515 Mar23 Sept
5,115Peak Premier in tracked matches
34Days played since 2025-04-10

Premier CS Rating

  • 1,212 below peak (5,115)
  • Next: Light Blue band at 5,000 — 1,097 to go
  • Reached: Light Blue band

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

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CSDB.GGpabloPREMIER3,903 · Grey bandcsdb.gg/stats

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Performance scores

Aim9
Positioning31
Utility5

0–100 skill scores via Leetify.

Recent form

COLD44–55–1Last 10044%Win rateLLLWLWLLWL

Last 10 vs previous 10: −10pp win rate · −0.06 avg rating · −4.9pp headshot accuracy · +26ms 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

  • 1–4 · 20% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 13%
  • Avg reaction 714ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating -0.09
  • Avg headshot accuracy 8%
  • Avg reaction 762ms

Last 20

  • 7–13 · 35% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 10%
  • Avg reaction 749ms

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 (+1.9 against its own average).

Aim0.9
Utility0.5
Positioning3.1
Opening Duels0.0

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

jL

Plays most like jL 74% 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. 733ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 60% 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

Aim0.9
Positioning3.1
Utility0.5
Mechanics2.2
Opening Duels0.0
Win Impact0.0

Composite 1.2/10 (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-0.06+0.00
first ⅓ avg -0.07 → last ⅓ avg -0.06
Reaction time725ms−16ms
first ⅓ avg 741ms → last ⅓ avg 725ms
Headshot accuracy10.6%+2.0%
first ⅓ avg 8.6% → last ⅓ avg 10.6%

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

0.04Best match rating · 6–13 · inferno, 11 Apr →
35%Best headshot accuracy · 13–4 · dust2, 14 Mar →
492msFastest reaction time · 13–8 · inferno, 23 May →
13–0Biggest win · mirage, 2 Apr →

Across the last 100 tracked matches.

Highlights

4Longest win streak
L3Current streak
6–5In matches decided by ≤2 rounds
12Overtime games

Map breakdown

anubisBest map · 56% over 9nukeWeakest map · 25% over 12
MapGradePlayedRecordWin rateAvg rating
mirageC2511–1444%-0.08
infernoB2311–1248%-0.05
dust2C187–1139%-0.06
nukeD123–925%-0.09
anubisA95–456%-0.07
overpassD62–433%-0.07
ancient—43–175%-0.06
cache—11–0100%-0.04
train—10–10%-0.03
grail—11–0100%-0.07

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (25% over 12). Start with the 6 essential Nuke 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.

10.5%Headshot accuracy
24.5%Accuracy (enemy spotted)
25.3%Spray accuracy
59.8%Counter-strafing
12.1°Preaim
733msReaction time
19.6%T opening success
15.8%CT opening success
0.00Enemies flashed / flash
0.0%Flash assists
1.23HE damage / grenade
0.10Flashes / 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 12.1405° — 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 10.5156% — 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 733.374ms — above the 700ms mark we flag

    Aim Training →
Spend your practice time on Nuke

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

25% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno8–13-0.0618%13 May →
dust25–13-0.0817%13 May →
anubis5–13-0.0420%13 May →
cache13–8-0.045%13 May →
nuke6–13-0.123%26 Apr →
nuke13–10-0.102%24 Apr →
dust24–13-0.120%24 Apr →
dust22–13-0.140%22 Apr →
mirage13–4-0.110%22 Apr →
anubis10–13-0.089%22 Apr →
inferno13–11-0.102%17 Apr →
dust211–130.0115%17 Apr →
inferno4–13-0.0630%12 Apr →
mirage10–13-0.1010%12 Apr →
dust213–20.0017%12 Apr →
nuke7–13-0.0424%12 Apr →
anubis13–60.025%12 Apr →
mirage6–13-0.074%12 Apr →
inferno6–130.047%11 Apr →
anubis13–9-0.0511%11 Apr →
inferno6–13-0.0524%11 Apr →
nuke13–10-0.129%11 Apr →
mirage13–6-0.092%9 Apr →
inferno13–9-0.0815%9 Apr →
inferno3–13-0.0720%5 Apr →
mirage6–13-0.0910%5 Apr →
inferno3–13-0.084%5 Apr →
dust210–13-0.0410%5 Apr →
overpass6–13-0.1114%5 Apr →
mirage13–16-0.0210%3 Apr →
dust26–13-0.046%3 Apr →
mirage16–14-0.076%3 Apr →
nuke7–13-0.0419%3 Apr →
inferno9–13-0.089%3 Apr →
inferno13–70.0110%2 Apr →
nuke8–13-0.137%2 Apr →
mirage13–0-0.017%2 Apr →
dust25–13-0.077%2 Apr →
anubis9–13-0.094%27 Mar →
overpass13–20.0019%27 Mar →
mirage14–16-0.084%27 Mar →
inferno16–14-0.1013%27 Mar →
overpass12–16-0.118%25 Mar →
inferno3–13-0.0712%25 Mar →
mirage10–13-0.0919%25 Mar →
anubis13–5-0.096%23 Mar →
ancient13–10-0.1110%23 Mar →
mirage14–16-0.097%23 Mar →
nuke13–5-0.077%21 Mar →
mirage6–13-0.076%21 Mar →
mirage13–11-0.0911%21 Mar →
overpass13–8-0.0812%20 Mar →
inferno13–3-0.0714%20 Mar →
dust25–13-0.0613%20 Mar →
mirage13–16-0.0710%20 Mar →
dust213–2-0.060%20 Mar →
dust20–8-0.080%18 Mar →
nuke10–13-0.052%18 Mar →
inferno13–16-0.057%15 Mar →
mirage13–6-0.0011%15 Mar →
inferno16–14-0.044%15 Mar →
nuke11–13-0.099%15 Mar →
anubis13–10-0.1014%14 Mar →
mirage13–10-0.110%14 Mar →
dust213–4-0.0635%14 Mar →
mirage16–13-0.0911%14 Mar →
ancient1–13-0.0314%13 Mar →
overpass9–13-0.053%13 Mar →
mirage7–13-0.099%8 Mar →
inferno7–13-0.053%8 Mar →
dust213–9-0.0620%7 Mar →
mirage13–10-0.085%7 Mar →
dust215–15-0.106%7 Mar →
inferno13–7-0.0017%7 Mar →
nuke10–13-0.119%6 Mar →
inferno12–16-0.0915%2 Mar →
mirage2–13-0.0917%2 Mar →
dust213–11-0.065%1 Mar →
mirage7–13-0.067%28 Feb →
nuke6–13-0.126%28 Feb →
mirage7–13-0.0914%27 Feb →
overpass5–13-0.0719%27 Feb →
mirage4–13-0.130%27 Feb →
inferno13–5-0.0315%27 Feb →
inferno13–8-0.0413%23 May →
train6–13-0.0317%23 May →
dust213–9-0.073%18 May →
anubis11–13-0.096%8 May →
ancient11–1-0.015%8 May →
grail13–9-0.070%8 May →
ancient13–8-0.0914%8 May →
anubis13–10-0.075%6 May →
inferno4–13-0.077%6 May →
inferno13–10-0.065%28 Apr →
nuke8–13-0.095%28 Apr →
dust25–13-0.124%28 Apr →
mirage13–6-0.036%14 Apr →
dust213–2-0.0013%10 Apr →
inferno13–9-0.017%10 Apr →
mirage13–4-0.065%10 Apr →

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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