SERGIO GRAMOS

SERGIO GRAMOS — CS2 Stats

AO76561199063861195[U:1:1103595467]Steam profile ↗✓ No bans

1,209Tracked matches32%Win rate2021Tracked since
1,136Hours in CS
CSDB Rating3.0 LearningSupport
Premier CS Rating13,011Blue band · top ~38.9% of ranked players (population est.)
WingmanGold Nova III
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 23 Jun 2026 (132 days ago). 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: 13,011 -3,851 12 Jan – 23 Jun · 27 days played
13,01120,113peak 20,11312 Jan23 Jun
20,113Peak Premier in tracked matches
32Days played since 2026-01-12

Premier CS Rating

  • 7,102 below peak (20,113)
  • -2,764 over 90 days
  • Next: Purple band at 15,000 — 1,989 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.

How this compares with the same rank

Median values for Blue band among CSDB-tracked players (n=21,222), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerBlue band medianPurple band medianvs Purple band
Headshot rate42.7%42.0%44.4%1.7% short
Shot accuracy13.7%9.6%11.9%above
Kill/death ratio0.880.981.030.15 short
Match win rate43.7%43.8%45.2%1.5% short

This profile matches the typical Purple band player on 1 of 4 comparable metrics.

Widest gap: Kill/death ratio. That is the metric furthest from the Purple band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGSERGIO GRAMOSPREMIER13,011 · Blue bandcsdb.gg/stats

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Performance scores

Aim35
Positioning32
Utility58

0–100 skill scores via Leetify.

Recent form

COLD42–50–8Last 10042%Win rateLTLWLWWTLL

Last 10 vs previous 10: +10pp win rate · −0.00 avg rating · +3.4pp headshot accuracy · +118ms 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

  • 1–3–1 · 20% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 13%
  • Avg reaction 653ms

Last 10

  • 3–5–2 · 30% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 17%
  • Avg reaction 649ms

Last 20

  • 5–13–2 · 25% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 15%
  • Avg reaction 590ms

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: Support — Utility contribution stands above the rest of this profile (+2.4 against its own average).

Aim3.5
Utility5.8
Positioning3.2
Opening Duels1.3

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

ZywOo

Plays most like ZywOo 69% playstyle similarity

Most alike: utility contribution, positioning profile.

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. 573ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 65% 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

Aim3.5
Positioning3.2
Utility5.8
Mechanics3.3
Opening Duels0.8
Win Impact0.0

Composite 3.0/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.04−0.02
first ⅓ avg -0.02 → last ⅓ avg -0.04
Reaction time575ms−39ms
first ⅓ avg 615ms → last ⅓ avg 575ms
Headshot accuracy14.9%−2.0%
first ⅓ avg 16.8% → last ⅓ avg 14.9%

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

0.10Best match rating · 13–4 · nuke, 12 Jan →
32%Best headshot accuracy · 11–13 · nuke, 12 Mar →
375msFastest reaction time · 0–13 · ancient, 5 Mar →
13–2Biggest win · overpass, 17 Jan →

Across the last 100 tracked matches.

Highlights

4Longest win streak
8–7In matches decided by ≤2 rounds
14Overtime games

Map breakdown

anubisBest map · 75% over 8mirageWeakest map · 19% over 21
MapGradePlayedRecordWin rateAvg rating
infernoC2511–1444%-0.02
mirageD214–1719%-0.04
ancientD133–1023%-0.03
overpassS128–467%-0.02
dust2B105–550%-0.02
nukeB84–450%-0.02
anubisS86–275%0.02
vertigo—31–233%-0.01

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (19% over 21). Start with the 5 essential Mirage lineups, review the callouts, then spin up a practice server.

Lifetime stats

45,764Lifetime kills
0.88K/D
2,782Matches
43.7%Match win rate
42.7%Headshot % · Top 50% of Blue band
13.7%Shot accuracy · Top 50% of Blue band
6,029MVPs
1,136Hours (in match)
1,067Bombs planted
508Bombs defused

Most-used weapons

AK-4714,032
AWP3,956
Tec-91,340
MP91,284
SSG 081,206
FAMAS1,099

Lifetime map wins

11,506inferno
1,296nuke
1,263vertigo
1,235dust2
873cbble
503train
122lake
13office

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

14.9%Headshot accuracy
29.2%Accuracy (enemy spotted)
33.6%Spray accuracy
64.8%Counter-strafing
12.6°Preaim
573msReaction time
26.0%T opening success
36.2%CT opening success
0.66Enemies flashed / flash
5.3%Flash assists
8.08HE damage / grenade
11.21Flashes / 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 12.6046° — 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 14.888% — below the 15% mark we flag

    Aim Training →
Spend your practice time on Mirage

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

19% win rate across 21 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
vertigo3–9-0.169%23 Jun →
inferno8–8-0.0413%23 Jun →
nuke10–13-0.0611%23 Jun →
mirage13–40.0015%23 Jun →
ancient6–13-0.0116%14 Mar →
inferno16–13-0.0212%14 Mar →
overpass13–10-0.0218%14 Mar →
inferno15–150.0220%13 Mar →
mirage8–13-0.0923%13 Mar →
nuke11–13-0.0532%12 Mar →
ancient1–13-0.0519%9 Mar →
dust213–16-0.0411%7 Mar →
overpass13–4-0.037%5 Mar →
mirage9–13-0.0519%5 Mar →
ancient0–13-0.0820%5 Mar →
mirage5–13-0.0314%4 Mar →
overpass5–13-0.047%3 Mar →
inferno7–13-0.0315%2 Mar →
nuke13–10-0.0616%27 Feb →
inferno12–16-0.018%18 Feb →
dust213–100.0220%18 Feb →
mirage7–13-0.0413%16 Feb →
nuke13–8-0.0317%8 Feb →
mirage4–13-0.0428%8 Feb →
vertigo8–80.0517%6 Feb →
ancient11–13-0.0515%6 Feb →
mirage15–15-0.029%6 Feb →
overpass10–130.0218%5 Feb →
ancient4–13-0.0813%5 Feb →
overpass13–4-0.0617%30 Jan →
anubis16–130.0210%29 Jan →
mirage2–13-0.107%29 Jan →
inferno11–13-0.083%29 Jan →
inferno13–7-0.0111%29 Jan →
inferno13–9-0.0514%28 Jan →
nuke11–13-0.0319%28 Jan →
inferno8–13-0.049%28 Jan →
mirage10–13-0.049%28 Jan →
ancient7–13-0.0315%28 Jan →
overpass13–100.0311%27 Jan →
dust213–9-0.049%27 Jan →
inferno13–110.029%27 Jan →
inferno2–13-0.0813%27 Jan →
mirage3–13-0.0911%26 Jan →
dust23–13-0.016%26 Jan →
inferno15–150.0017%26 Jan →
ancient7–13-0.022%25 Jan →
nuke16–13-0.0213%25 Jan →
dust211–13-0.0220%25 Jan →
overpass3–13-0.0010%25 Jan →
inferno13–70.0722%25 Jan →
anubis13–60.0713%25 Jan →
mirage6–13-0.0416%25 Jan →
ancient7–13-0.079%25 Jan →
anubis13–50.0611%25 Jan →
anubis16–14-0.0313%25 Jan →
anubis13–100.0215%25 Jan →
ancient13–40.0414%25 Jan →
mirage7–13-0.019%24 Jan →
mirage5–13-0.0424%24 Jan →
inferno7–130.0427%24 Jan →
inferno13–60.0311%24 Jan →
ancient15–15-0.0411%24 Jan →
inferno13–10-0.039%24 Jan →
inferno9–13-0.0218%24 Jan →
inferno16–130.1020%23 Jan →
inferno13–11-0.078%23 Jan →
ancient9–130.0110%23 Jan →
anubis13–100.0215%22 Jan →
vertigo13–110.0714%21 Jan →
anubis12–12-0.0410%20 Jan →
overpass16–14-0.0115%19 Jan →
inferno8–2-0.035%19 Jan →
mirage7–13-0.0221%19 Jan →
anubis12–120.0317%19 Jan →
ancient13–110.0113%19 Jan →
inferno11–13-0.0314%18 Jan →
overpass16–13-0.0117%18 Jan →
inferno1–13-0.0812%18 Jan →
dust213–30.0215%18 Jan →
nuke9–13-0.0317%18 Jan →
dust213–10-0.0415%18 Jan →
mirage13–11-0.0525%18 Jan →
mirage7–13-0.0131%18 Jan →
dust210–130.0122%18 Jan →
overpass13–110.0215%18 Jan →
dust213–4-0.0513%18 Jan →
inferno13–40.0215%18 Jan →
inferno9–13-0.0324%18 Jan →
overpass8–13-0.0912%17 Jan →
dust28–13-0.0219%17 Jan →
overpass13–2-0.039%17 Jan →
mirage5–13-0.0328%17 Jan →
inferno9–13-0.0517%16 Jan →
mirage0–13-0.1321%16 Jan →
mirage14–16-0.0623%12 Jan →
nuke13–40.1019%12 Jan →
ancient13–60.0323%12 Jan →
mirage13–6-0.0310%12 Jan →
mirage13–90.0021%12 Jan →

Match data via Leetify.

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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