Lino Lada

Lino Lada — CS2 Stats

SJ76561198258380059[U:1:298114331]Steam profile ↗✓ No bans

360Tracked matches65%Win rate2020Tracked since
1,324Hours in CS12Hrs last 2 wks
CSDB Rating3.6 LearningSupport
FaceitLevel 1Top 100.0% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 13 Sep 2026 (10 days ago). Ranks are recorded once per day this page is viewed.

+6Tracked matches · now 360
−1.4ppWin rate · 66.7% → 65.2%
Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 30 days played since 11 Jun 2026. Come back after the next session and the change shows above.

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Rating over time

30Days played since 2026-06-11

Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled.

How this compares with the same rank

Median values for Level 1 among CSDB-tracked players (n=2,156), 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 playerLevel 1 medianLevel 2 medianvs Level 2
Headshot rate35.9%40.9%41.3%5.4% short
Shot accuracy4.8%14.2%12.7%7.9% short
Kill/death ratio0.710.950.950.25 short
Match win rate45.9%42.1%42.5%above

This profile matches the typical Level 2 player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Level 2 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGLino LadaFACEITLevel 1STANDINGTop 100.0% of rankedcsdb.gg/stats

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Performance scores

Aim26
Positioning33
Utility41

0–100 skill scores via Leetify.

Recent form

STEADY53389Last 10053%Win rateWTWLWLLLWW

Last 10 vs previous 10: −10pp win rate · −0.00 avg rating · −0.0pp headshot accuracy · +1ms 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

  • 311 · 60% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 11%
  • Avg reaction 636ms

Last 10

  • 541 · 50% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 13%
  • Avg reaction 602ms

Last 20

  • 1172 · 55% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 13%
  • Avg reaction 602ms

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: SupportUtility contribution stands above the rest of this profile (+2.3 against its own average).

Aim2.6
Utility4.1
Positioning3.3
Opening Duels0.0
Clutch0.0

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

NiKo

Plays most like NiKo 66% 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. 601ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 66% 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

Aim2.6
Positioning3.3
Utility4.1
Mechanics3.6
Opening Duels0.1
Win Impact10.0

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-0.05−0.03
first ⅓ avg -0.03 → last ⅓ avg -0.05
Reaction time598ms−31ms
first ⅓ avg 629ms → last ⅓ avg 598ms
Headshot accuracy11.5%+0.2%
first ⅓ avg 11.2% → last ⅓ avg 11.5%

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

0.11Best match rating · 13–3 · boulder, 20 Aug
29%Best headshot accuracy · 13–0 · cache, 20 Aug
422msFastest reaction time · 13–4 · office, 3 Sept
13–0Biggest win · cache, 20 Aug

Across the last 100 tracked matches.

Highlights

10Longest win streak
26In matches decided by ≤2 rounds

Map breakdown

vertigoBest map · 80% over 10ancientWeakest map · 33% over 9
MapGradePlayedRecordWin rateAvg rating
cacheB1910953%-0.04
officeB126650%-0.03
vertigoS108280%-0.02
ancientD93633%-0.05
fachwerkC94544%-0.03
boulderA85363%-0.03
overpassA74357%-0.06
infernoD62433%-0.05
shelterC52340%-0.01
mirage41325%-0.05
train42250%-0.00
alpine220100%-0.06
nuke110100%-0.08
anubis110100%-0.03
stronghold110100%-0.03
dust2110100%-0.02
italy1010%-0.07

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (33% over 9). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

9,965Lifetime kills
0.71K/D
922Matches
45.9%Match win rate · Top 25% of Level 1 players
35.9%Headshot %
4.8%Shot accuracy
1,084MVPs
360Hours (in match)
1,480Bombs planted
214Bombs defused

Most-used weapons

Lifetime map wins

1,328office
1,301inferno
926dust2
779nuke
415cbble
346train
323vertigo
151italy

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

Faceit stats

Combat

11Matches
18%Win rate
0.21Avg K/D
27.4ADR
38%Headshot %

Clutches & streaks

0%1v1 clutch win
0%1v2 clutch win
1Longest win streak

Recent Faceit resultsLLLLL

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.

11.3%Headshot accuracy
27.4%Accuracy (enemy spotted)
27.7%Spray accuracy
66.2%Counter-strafing
11.4°Preaim
601msReaction time
22.3%T opening success
31.0%CT opening success
0.48Enemies flashed / flash
0.0%Flash assists
7.41HE damage / grenade
4.10Flashes / 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. 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 11.3204% — below the 15% 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 0.4753 — 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 22.3108% — below the 40% mark we flag

Spend your practice time on Ancient

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

33% win rate across 9 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategyAncient grenade lineups

Recent matches

MapScoreRatingHS%Date
overpass13–11-0.088%16 Sept
boulder12–12-0.047%16 Sept
mirage13–4-0.0223%16 Sept
ancient7–13-0.087%16 Sept
office13–1-0.0012%16 Sept
inferno10–13-0.0816%13 Sept
cache9–130.006%12 Sept
ancient8–13-0.0613%12 Sept
nuke13–11-0.0813%12 Sept
boulder13–3-0.0122%12 Sept
inferno12–12-0.0114%12 Sept
overpass13–7-0.058%12 Sept
vertigo13–50.0319%12 Sept
ancient11–13-0.0413%12 Sept
boulder13–4-0.0012%12 Sept
vertigo8–13-0.1210%5 Sept
inferno13–7-0.0224%4 Sept
overpass13–10-0.0415%4 Sept
cache13–7-0.085%4 Sept
boulder5–13-0.088%4 Sept
fachwerk12–12-0.107%3 Sept
ancient13–10-0.089%3 Sept
office13–40.0114%3 Sept
anubis13–9-0.036%1 Sept
overpass12–12-0.1012%1 Sept
train5–13-0.0910%1 Sept
cache13–3-0.058%31 Aug
mirage12–12-0.0810%31 Aug
overpass12–12-0.0310%31 Aug
fachwerk12–12-0.124%31 Aug
mirage9–13-0.048%31 Aug
vertigo13–5-0.0713%30 Aug
ancient10–13-0.0410%30 Aug
cache13–9-0.045%30 Aug
office13–30.0214%30 Aug
cache13–9-0.0611%29 Aug
ancient13–40.0415%29 Aug
shelter9–130.029%29 Aug
office6–13-0.1010%29 Aug
vertigo13–40.0228%29 Aug
fachwerk8–130.059%29 Aug
fachwerk13–40.0812%29 Aug
boulder6–13-0.048%28 Aug
vertigo13–40.0517%28 Aug
fachwerk13–5-0.0017%28 Aug
inferno7–13-0.110%28 Aug
cache4–13-0.073%28 Aug
vertigo13–40.0114%28 Aug
inferno7–13-0.1010%27 Aug
cache5–13-0.078%27 Aug
cache1–13-0.0413%21 Aug
vertigo13–6-0.057%21 Aug
fachwerk9–13-0.0810%21 Aug
mirage6–13-0.0613%21 Aug
ancient6–13-0.108%21 Aug
boulder13–6-0.1115%21 Aug
cache13–00.0229%20 Aug
office4–13-0.079%20 Aug
ancient10–13-0.0718%20 Aug
boulder13–30.1110%20 Aug
cache6–13-0.190%9 Aug
cache11–13-0.0311%31 Jul
vertigo13–9-0.037%31 Jul
shelter12–12-0.0213%22 Jul
office7–13-0.0826%22 Jul
cache13–5-0.063%22 Jul
vertigo13–6-0.055%16 Jul
shelter11–13-0.027%16 Jul
fachwerk10–13-0.067%16 Jul
fachwerk13–9-0.026%15 Jul
shelter13–7-0.0610%12 Jul
shelter13–30.0017%12 Jul
fachwerk13–6-0.0218%12 Jul
boulder13–5-0.059%12 Jul
office13–8-0.018%8 Jul
stronghold13–6-0.0321%7 Jul
alpine13–5-0.0314%7 Jul
office13–50.078%7 Jul
cache13–4-0.0319%7 Jul
office11–13-0.082%6 Jul
train6–130.0115%6 Jul
overpass2–13-0.087%3 Jul
ancient13–9-0.0213%3 Jul
cache13–90.043%2 Jul
train13–40.056%20 Jun
office13–40.0218%20 Jun
cache12–12-0.0910%20 Jun
train13–20.0315%20 Jun
cache9–13-0.0412%19 Jun
cache13–6-0.0017%19 Jun
office8–13-0.0210%16 Jun
cache11–130.0117%16 Jun
inferno13–9-0.0016%16 Jun
dust211–6-0.0217%16 Jun
alpine13–6-0.097%12 Jun
vertigo11–13-0.019%12 Jun
overpass13–2-0.036%12 Jun
cache13–5-0.0713%12 Jun
italy7–13-0.076%11 Jun
office0–13-0.106%11 Jun

Match data via Leetify.

Recent teammates

Milestones

100 Matches10-Win Streak
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →