Roberto

Roberto — CS2 Stats

GH76561198061674821[U:1:101409093]Steam profile ↗VAC banned

414Tracked matches61%Win rate2021Tracked since
CSDB Rating8.0 StrongAll-Rounder
Premier CS Rating24,293Top 25% of 212,379 CSDB-tracked playersPink band · top ~3.8% of ranked players (population est.)
CSDB Leaderboard#29796 of 259209 tracked
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 31 Oct 2026 (yesterday). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 24,293 +8,984 22 Nov – 31 Oct · 37 days played
13,67724,293peak 24,29322 Nov31 Oct
24,293Peak Premier in tracked matches
47Days played since 2025-11-22

Premier CS Rating

  • At peak — 24,293
  • Next: Red band at 25,000 — 707 to go
  • Reached: Pink band · Purple band · Blue band · 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.GGRobertoPREMIER24,293 · Pink bandcsdb.gg/stats

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Performance scores

Aim81
Positioning80
Utility69

0–100 skill scores via Leetify.

Recent form

STEADY57–39–4Last 10057%Win rateWWWWLWTLWL

Last 10 vs previous 10: −20pp win rate · +0.00 avg rating · +0.7pp headshot accuracy · +10ms reaction

Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.00), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 4–1 · 80% win rate
  • Avg rating 0.07
  • Avg headshot accuracy 25%
  • Avg reaction 538ms

Last 10

  • 6–3–1 · 60% win rate
  • Avg rating 0.06
  • Avg headshot accuracy 23%
  • Avg reaction 552ms

Last 20

  • 14–5–1 · 70% win rate
  • Avg rating 0.06
  • Avg headshot accuracy 22%
  • Avg reaction 547ms

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: All-Rounder — No style dimension stands clear of the others in this profile.

Aim8.1
Utility6.9
Positioning8.0
Opening Duels7.4

Strong positioning

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

s1mple

Plays most like s1mple 81% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: 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

Strengths

CT openings. 67% CT opening-duel success — winning the first fight on the defending side is rare and valuable.

T openings. 64% T opening-duel success — entries that actually open the round.

Areas to improve

Preaim. Mechanical aim is strong but the crosshair sits 10.0° off target when enemies appear — placement, not flicking, is the bigger win available.

Reaction time. 560ms 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

Aim8.1
Positioning8.0
Utility6.9
Mechanics6.6
Opening Duels8.8
Win Impact8.6

Composite 8.0/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.04+0.00
first ⅓ avg 0.04 → last ⅓ avg 0.04
Reaction time561ms−90ms
first ⅓ avg 651ms → last ⅓ avg 561ms
Headshot accuracy23.7%−3.5%
first ⅓ avg 27.2% → last ⅓ avg 23.7%

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 · 13–11 · nuke, 3 Dec →
56%Best headshot accuracy · 13–2 · inferno, 20 Mar →
406msFastest reaction time · 7–13 · anubis, 17 Aug →
13–0Biggest win · dust2, 2 May →

Across the last 100 tracked matches.

Highlights

6Longest win streak
W4Current streak
9–3In matches decided by ≤2 rounds
12Overtime games

Map breakdown

cacheBest map · 78% over 9anubisWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
dust2A3017–1357%0.04
ancientC177–1041%0.04
infernoS1511–473%0.05
nukeS118–373%0.06
cacheS97–278%0.06
mirageA74–357%0.03
anubisD61–517%0.03
overpass—42–250%0.07
train—10–10%0.02

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (17% over 6). Start with the 6 essential Anubis 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.

23.9%Headshot accuracy
35.4%Accuracy (enemy spotted)
40.8%Spray accuracy
79.5%Counter-strafing
10.0°Preaim
560msReaction time
63.6%T opening success
66.9%CT opening success
0.65Enemies flashed / flash
15.3%Flash assists
10.10HE damage / grenade
12.69Flashes / match

Recommended for you

Spend your practice time on Anubis

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 6 tracked games — your weakest map with enough games to be worth reading into.

Anubis callouts & strategy →Anubis grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust213–90.0516%31 Oct →
cache13–40.1020%31 Oct →
ancient13–30.0734%30 Oct →
inferno13–80.1634%30 Oct →
mirage8–13-0.0119%30 Oct →
cache13–70.1120%30 Oct →
anubis15–150.0523%29 Oct →
dust24–13-0.0315%29 Oct →
cache16–140.0926%29 Oct →
inferno7–130.0521%29 Oct →
ancient13–60.0727%29 Oct →
cache13–40.1123%29 Oct →
inferno13–60.1216%29 Oct →
cache13–70.0319%25 Oct →
inferno13–30.0625%25 Oct →
dust213–60.1420%22 Oct →
mirage9–130.0524%22 Oct →
anubis4–130.0319%22 Oct →
mirage13–100.0016%20 Oct →
cache13–70.0231%20 Oct →
anubis8–130.0622%20 Oct →
dust211–13-0.0226%20 Oct →
anubis5–13-0.0231%16 Oct →
ancient15–150.0529%16 Oct →
nuke6–130.0130%16 Oct →
anubis13–60.0436%16 Oct →
dust213–50.0133%16 Oct →
dust213–50.0630%16 Oct →
mirage10–130.0122%16 Oct →
ancient7–13-0.0312%16 Oct →
dust213–70.0026%16 Oct →
ancient13–6-0.0221%24 Aug →
ancient6–130.0117%23 Aug →
cache6–13-0.0134%23 Aug →
nuke13–40.0925%17 Aug →
anubis7–130.0133%17 Aug →
dust213–50.0438%17 Aug →
inferno13–80.0424%17 Aug →
nuke10–13-0.0125%14 Aug →
cache13–40.0721%13 Aug →
cache4–130.0247%13 Jul →
dust21–9-0.108%12 Jul →
ancient16–130.0731%12 Jul →
dust213–70.1223%12 Jul →
ancient13–110.0430%27 Jun →
dust213–80.0329%24 Jun →
ancient13–110.0936%8 Jun →
inferno6–13-0.0138%8 Jun →
overpass13–20.1333%8 Jun →
dust29–130.0629%8 Jun →
inferno13–110.0533%7 Jun →
dust213–90.0841%6 Jun →
ancient11–130.0130%2 Jun →
dust24–130.1034%1 Jun →
inferno13–90.1132%1 Jun →
overpass13–30.0641%1 Jun →
nuke13–60.0936%2 May →
dust213–00.1133%2 May →
dust20–13-0.0123%2 May →
inferno9–13-0.0428%25 Apr →
dust216–140.0819%25 Apr →
nuke13–80.0523%25 Apr →
ancient5–130.0122%25 Apr →
overpass3–130.0828%16 Apr →
ancient8–13-0.0025%16 Apr →
mirage13–10.0235%10 Apr →
dust213–20.1233%9 Apr →
inferno13–100.1229%23 Mar →
inferno13–90.0428%23 Mar →
dust213–160.0728%23 Mar →
dust21–10-0.0631%21 Mar →
inferno13–20.0856%20 Mar →
dust212–16-0.0125%20 Mar →
inferno14–16-0.0430%20 Mar →
ancient13–40.0835%17 Mar →
inferno13–6-0.0924%15 Mar →
nuke13–50.0029%15 Mar →
mirage13–110.0216%15 Mar →
dust28–13-0.0538%14 Mar →
nuke16–130.0218%14 Mar →
dust213–110.0319%13 Mar →
mirage13–60.1132%18 Jan →
nuke9–130.0732%18 Dec →
dust213–100.1130%17 Dec →
overpass6–130.0218%14 Dec →
dust213–30.1332%13 Dec →
ancient15–150.1024%10 Dec →
nuke13–70.0520%10 Dec →
dust27–130.0230%10 Dec →
dust216–140.0530%5 Dec →
dust213–100.0422%4 Dec →
nuke13–110.1924%3 Dec →
nuke13–70.1123%30 Nov →
ancient7–130.0321%26 Nov →
dust29–130.0019%26 Nov →
ancient15–150.0218%26 Nov →
train7–130.0230%25 Nov →
ancient9–130.0429%23 Nov →
inferno13–20.0430%23 Nov →
dust210–130.0128%22 Nov →

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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