pablo — CS2 Stats
UM76561198994765405[U:1:1034499677]Steam profile ↗✓ No bans
What changed since last observed
CSDB last observed this profile on 8 Sep 2026 (9 days ago). Ranks are recorded once per day this page is viewed.
No change since then — still 223 tracked matches. Play, then come back: the next observation lands here.
CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 47 days played since 7 Nov 2022. Come back after the next session and the change shows above.
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Rating over time
Premier CS Rating
- At peak — 15,716
- +1,106 over 90 days
- Next: Pink band at 20,000 — 4,284 to go
- Reached: Purple band · Blue band · Light Blue band
- Purple band first seen 2026-08-28
- Blue band first seen 2026-08-28
Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do. Faceit ELO is CSDB’s own observation — no feed exposes ELO per match, so that line only has the days the profile was viewed and cannot be backfilled.
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: −20pp win rate · −0.01 avg rating · +2.4pp headshot accuracy · −25ms reaction
Win rate down 20pp 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
- 3–2 · 60% win rate
- Avg rating 0.01
- Avg headshot accuracy 29%
- Avg reaction 570ms
Last 10
- 6–4 · 60% win rate
- Avg rating 0.05
- Avg headshot accuracy 29%
- Avg reaction 568ms
Last 20
- 14–6 · 70% win rate
- Avg rating 0.05
- Avg headshot accuracy 28%
- Avg reaction 580ms
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 (+1.5 against its own average).
Sharp aimerEffective flashesLimited 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
Plays most like s1mple 93% playstyle similarity
Most alike: positioning profile, opening-duel success.
Where you differ: lower utility contribution.
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
Aim. Aim score of 86 — the mechanical foundation is a clear strength.
Areas to improve
Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.
T-side openings. Opening success drops from 60% on CT to 41% on T — the same duels are being taken with worse setups on the attacking side.
Reaction time. 606ms 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
Composite 7.2/10 (Strong), 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
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
Across the last 100 tracked matches.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
 mirage | A | 24 | 15–9 | 63% | 0.04 |
 inferno | B | 18 | 9–9 | 50% | 0.05 |
 dust2 | B | 18 | 9–9 | 50% | 0.01 |
 nuke | S | 12 | 8–4 | 67% | 0.03 |
 anubis | B | 8 | 4–4 | 50% | 0.01 |
 overpass | A | 7 | 4–3 | 57% | 0.00 |
 vertigo | B | 6 | 3–3 | 50% | 0.03 |
 train | — | 3 | 1–2 | 33% | 0.01 |
 ancient | — | 1 | 1–0 | 100% | 0.06 |
| office | — | 1 | 0–1 | 0% | -0.05 |
| agency | — | 1 | 0–1 | 0% | -0.02 |
 cache | — | 1 | 1–0 | 100% | 0.02 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (50% over 18). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.
Faceit stats
Combat
Clutches & streaks
Recent Faceit resultsLWWLL
| Map | Matches | Win rate | Avg K/D | Avg kills |
|---|---|---|---|---|
| Mirage | 7 | 57% | 1.32 | 16.9 |
| Inferno | 5 | 40% | 1.24 | 21.8 |
| Nuke | 4 | 50% | 1.09 | 18.5 |
| Dust2 | 4 | 75% | 1.34 | 19.5 |
| Anubis | 2 | 0% | 1.82 | 30.5 |
| Train | 1 | 100% | 1.33 | 20.0 |
Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.
Skill profile
Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.
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.
- Grenades & UtilityGrenade Lineups →
You are buying and holding utility rather than using it. Unthrown flashes are wasted money every round.
Flashes per match 2.8383 — below the 4 mark we flag
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| nuke | 16–13 | 0.09 | 31% | 18 Jun → | |
| inferno | 11–13 | 0.01 | 27% | 18 Jun → | |
| nuke | 11–13 | -0.04 | 25% | 15 Jun → | |
| anubis | 13–10 | 0.03 | 32% | 15 Jun → | |
| mirage | 16–14 | -0.03 | 30% | 15 Jun → | |
| inferno | 13–4 | 0.09 | 21% | 15 Jun → | |
| mirage | 13–5 | 0.15 | 32% | 10 Jun → | |
| inferno | 11–13 | 0.04 | 35% | 10 Jun → | |
| inferno | 13–10 | 0.03 | 26% | 10 Jun → | |
| nuke | 9–13 | 0.09 | 31% | 7 Jun → | |
| nuke | 13–4 | 0.09 | 35% | 7 Jun → | |
| inferno | 2–13 | -0.01 | 21% | 7 Jun → | |
| anubis | 10–13 | 0.05 | 30% | 7 Jun → | |
| ancient | 13–8 | 0.06 | 11% | 4 Jun → | |
| nuke | 13–8 | 0.05 | 25% | 4 Jun → | |
| dust2 | 13–11 | 0.03 | 27% | 4 Jun → | |
| dust2 | 13–6 | 0.11 | 24% | 3 Jun → | |
| mirage | 13–4 | 0.06 | 24% | 3 Jun → | |
| mirage | 13–11 | 0.07 | 36% | 3 Jun → | |
| dust2 | 13–4 | 0.08 | 33% | 3 Jun → | |
| dust2 | 11–13 | -0.03 | 41% | 2 Jun → | |
| mirage | 10–13 | 0.11 | 35% | 2 Jun → | |
| nuke | 5–1 | -0.04 | 12% | 2 Jun → | |
| nuke | 13–2 | 0.08 | 30% | 1 Jun → | |
| anubis | 0–3 | -0.03 | 20% | 1 Jun → | |
| mirage | 9–13 | -0.02 | 35% | 6 Jan → | |
| anubis | 13–4 | 0.04 | 26% | 6 Jan → | |
| overpass | 12–7 | -0.02 | 38% | 6 Jan → | |
| inferno | 11–13 | 0.15 | 38% | 6 Jan → | |
| vertigo | 8–13 | 0.05 | 45% | 5 Jan → | |
| anubis | 13–10 | 0.04 | 30% | 5 Jan → | |
| nuke | 4–13 | -0.05 | 19% | 25 Oct → | |
| mirage | 9–13 | 0.07 | 31% | 21 Jul → | |
| train | 4–13 | 0.01 | 31% | 21 Jul → | |
| vertigo | 9–13 | 0.05 | 21% | 21 Jul → | |
| inferno | 5–13 | 0.15 | 50% | 21 Jul → | |
| train | 1–13 | 0.03 | 26% | 21 Jul → | |
| dust2 | 13–16 | 0.05 | 26% | 13 Jun → | |
| train | 13–9 | 0.01 | 24% | 7 Jun → | |
| mirage | 13–2 | 0.05 | 29% | 4 Jun → | |
| nuke | 13–4 | 0.04 | 22% | 3 Jun → | |
| overpass | 6–13 | 0.01 | 44% | 3 Jun → | |
| dust2 | 9–13 | -0.01 | 29% | 27 May → | |
| inferno | 13–11 | 0.04 | 37% | 20 May → | |
| dust2 | 10–13 | -0.03 | 40% | 18 May → | |
| mirage | 13–6 | -0.00 | 16% | 17 May → | |
| vertigo | 13–8 | 0.05 | 26% | 17 May → | |
| overpass | 11–13 | 0.04 | 33% | 17 May → | |
| office | 12–12 | -0.05 | 20% | 17 May → | |
| inferno | 12–12 | 0.06 | 27% | 17 May → | |
| nuke | 3–13 | -0.06 | 9% | 10 Mar → | |
| nuke | 13–2 | 0.08 | 30% | 26 Feb → | |
| inferno | 13–6 | -0.02 | 29% | 26 Feb → | |
| overpass | 13–8 | 0.02 | 49% | 11 Aug → | |
| overpass | 16–8 | 0.08 | 24% | 13 May → | |
| dust2 | 16–12 | 0.06 | 40% | 13 May → | |
| mirage | 9–16 | -0.05 | 10% | 22 Apr → | |
| mirage | 15–15 | 0.02 | 32% | 11 Mar → | |
| dust2 | 16–10 | 0.02 | 45% | 11 Mar → | |
| mirage | 16–10 | -0.01 | 26% | 11 Mar → | |
| mirage | 10–1 | 0.01 | 41% | 10 Mar → | |
| dust2 | 7–16 | 0.00 | 48% | 10 Mar → | |
| dust2 | 8–16 | -0.05 | 17% | 10 Mar → | |
| mirage | 9–2 | 0.12 | 35% | 19 Feb → | |
| dust2 | 16–9 | 0.05 | 29% | 19 Jan → | |
| mirage | 8–16 | 0.04 | 18% | 19 Jan → | |
| dust2 | 7–16 | -0.05 | 28% | 19 Jan → | |
| dust2 | 16–7 | -0.05 | 19% | 4 Jan → | |
| dust2 | 16–5 | -0.07 | 39% | 4 Jan → | |
| dust2 | 16–11 | 0.07 | 16% | 27 Dec → | |
| mirage | 16–14 | 0.03 | 29% | 24 Dec → | |
| nuke | 16–11 | -0.01 | 27% | 21 Dec → | |
| dust2 | 15–15 | 0.01 | 16% | 9 Dec → | |
| mirage | 16–12 | 0.02 | 22% | 9 Dec → | |
| mirage | 14–16 | 0.02 | 41% | 8 Dec → | |
| mirage | 6–16 | 0.02 | 29% | 4 Dec → | |
| overpass | 2–16 | -0.07 | 15% | 4 Dec → | |
| agency | 12–16 | -0.02 | 27% | 4 Dec → | |
| mirage | 16–11 | 0.05 | 27% | 2 Dec → | |
| anubis | 9–16 | -0.01 | 34% | 2 Dec → | |
| inferno | 16–5 | 0.10 | 28% | 27 Nov → | |
| vertigo | 16–4 | 0.06 | 24% | 26 Nov → | |
| dust2 | 2–16 | -0.04 | 22% | 19 Nov → | |
| anubis | 5–16 | -0.09 | 13% | 19 Nov → | |
| mirage | 11–16 | 0.01 | 33% | 19 Nov → | |
| anubis | 15–1 | 0.04 | 33% | 19 Nov → | |
| inferno | 7–16 | 0.01 | 35% | 18 Nov → | |
| mirage | 9–7 | 0.08 | 48% | 17 Nov → | |
| inferno | 6–16 | -0.02 | 16% | 17 Nov → | |
| mirage | 16–10 | 0.13 | 31% | 17 Nov → | |
| inferno | 13–3 | -0.02 | 37% | 17 Nov → | |
| inferno | 15–15 | 0.00 | 19% | 15 Nov → | |
| vertigo | 12–16 | -0.05 | 23% | 15 Nov → | |
| cache | 16–6 | 0.02 | 22% | 15 Nov → | |
| inferno | 16–11 | 0.07 | 28% | 13 Nov → | |
| mirage | 16–5 | 0.12 | 24% | 12 Nov → | |
| inferno | 16–5 | 0.07 | 13% | 12 Nov → | |
| overpass | 16–14 | -0.03 | 15% | 8 Nov → | |
| inferno | 16–10 | 0.04 | 24% | 8 Nov → | |
| vertigo | 16–13 | 0.03 | 24% | 7 Nov → |
Match data via Leetify.
