lucky_buddy22

lucky_buddy22 — CS2 Stats

US76561198130991809[U:1:170726081]Steam profile ↗✓ No bans

864Tracked matches30%Win rate2023Tracked since
630Hours in CS
CSDB Rating4.7 DevelopingClutch Specialist
Premier CS Rating16,961Purple band · top ~20.6% of ranked players (population est.)
FaceitLevel 5Top 67.6% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 21 Nov 2025 (329 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: 16,961 -2,949 20 Mar – 21 Nov · 15 days played
16,85220,000peak 20,00020 Mar21 Nov
20,109Peak Premier in tracked matches
48Days played since 2025-03-20

Premier CS Rating

  • 3,039 below peak (20,000)
  • Next: Pink band at 20,000 — 3,039 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 Level 5 among CSDB-tracked players (n=13,918), 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 5 medianLevel 6 medianvs Level 6
Headshot rate39.4%43.7%44.8%5.4% short
Shot accuracy1.1%12.0%12.4%11.3% short
Kill/death ratio0.891.021.030.14 short
Match win rate41.4%44.7%45.2%3.9% short

This profile sits below the typical Level 6 player on every metric we can compare.

Widest gap: Shot accuracy. That is the metric furthest from the Level 6 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGlucky_buddy22FACEITLevel 5STANDINGTop 67.6% of rankedPREMIER16,961 · Purple bandcsdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim42
Positioning62
Utility58

0–100 skill scores via Leetify.

Recent form

STEADY41–50–9Last 10041%Win rateLWTLLLWLWW

Last 10 vs previous 10: +20pp win rate · +0.00 avg rating · +1.5pp headshot accuracy · −61ms reaction

Win rate up 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

  • 1–3–1 · 20% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 10%
  • Avg reaction 652ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 14%
  • Avg reaction 634ms

Last 20

  • 6–12–2 · 30% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 13%
  • Avg reaction 665ms

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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+0.9 against its own average).

Aim4.2
Utility5.8
Positioning6.2
Opening Duels4.6
Clutch6.8

Effective flashes

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 63% 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. 669ms 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

Aim4.2
Positioning6.2
Utility5.8
Mechanics5.9
Opening Duels4.1
Win Impact0.0

Composite 4.7/10 (Developing), 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-0.02−0.00
first ⅓ avg -0.02 → last ⅓ avg -0.02
Reaction time670ms+28ms
first ⅓ avg 641ms → last ⅓ avg 670ms
Headshot accuracy12.6%+1.4%
first ⅓ avg 11.3% → last ⅓ avg 12.6%

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

0.08Best match rating · 8–0 · ancient, 16 Sept →
36%Best headshot accuracy · 13–4 · mirage, 11 Sept →
445msFastest reaction time · 13–8 · nuke, 14 Sept →
13–1Biggest win · mirage, 16 Sept →

Across the last 100 tracked matches.

Highlights

3Longest win streak
7–7In matches decided by ≤2 rounds
7Overtime games

Map breakdown

nukeBest map · 65% over 17infernoWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
dust2B209–1145%-0.01
mirageD186–1233%-0.02
ancientC188–1044%-0.02
nukeS1711–665%-0.01
trainC104–640%-0.02
anubisD62–433%-0.03
infernoD51–420%-0.05
overpass—40–40%-0.02
vertigo—20–20%-0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

24,469Lifetime kills
0.89K/D
1,637Matches
41.4%Match win rate
39.4%Headshot %
1.1%Shot accuracy
2,139MVPs
630Hours (in match)
1,215Bombs planted
294Bombs defused

Most-used weapons

Lifetime map wins

1,766nuke
1,673dust2
1,593inferno
1,400vertigo
323train
37ar_shoots
32ar_baggage
10office

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

Faceit stats

Combat

32Matches
56%Win rate
0.98Avg K/D
73.6ADR
34%Headshot %

Clutches & streaks

54%1v1 clutch win
33%1v2 clutch win
5Longest win streak

Recent Faceit resultsLLLLL

MapMatchesWin rateAvg K/DAvg kills
Mirage1050%0.9515.8
Vertigo786%1.2314.9
Inferno540%0.8610.8
Nuke475%1.2015.5
Dust2333%0.6412.7
Ancient20%0.6110.0
Anubis1100%1.0814.0

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.

12.8%Headshot accuracy
31.6%Accuracy (enemy spotted)
36.9%Spray accuracy
76.3%Counter-strafing
11.6°Preaim
669msReaction time
43.6%T opening success
49.3%CT opening success
0.74Enemies flashed / flash
7.5%Flash assists
9.97HE damage / grenade
12.27Flashes / 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 12.8377% — below the 15% mark we flag

    Aim Training →
Spend your practice time on Inferno

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage6–13-0.068%8 Dec →
train13–80.018%8 Dec →
dust212–12-0.0312%3 Dec →
ancient10–13-0.086%3 Dec →
vertigo6–13-0.0415%3 Dec →
ancient10–13-0.0315%2 Dec →
dust213–7-0.0230%2 Dec →
ancient5–13-0.0126%2 Dec →
train13–50.017%1 Dec →
nuke13–7-0.0212%1 Dec →
ancient12–120.0114%1 Dec →
dust210–13-0.109%1 Dec →
overpass13–16-0.049%21 Nov →
dust25–130.0215%21 Nov →
nuke16–14-0.0412%20 Nov →
vertigo9–13-0.048%17 Nov →
mirage10–13-0.0316%17 Nov →
nuke13–80.0310%17 Nov →
train6–13-0.0615%17 Nov →
dust23–13-0.0615%17 Nov →
dust28–130.0418%15 Nov →
ancient1–10-0.000%13 Nov →
mirage9–13-0.0217%13 Nov →
inferno10–13-0.065%13 Nov →
dust27–13-0.0311%12 Nov →
mirage3–13-0.0316%12 Nov →
ancient12–12-0.0512%12 Nov →
mirage11–13-0.0612%12 Nov →
dust213–70.0222%11 Nov →
mirage13–70.0010%10 Nov →
nuke13–9-0.025%9 Nov →
mirage15–150.017%7 Nov →
train13–11-0.0419%6 Nov →
nuke5–13-0.0912%26 Sept →
nuke11–130.0410%25 Sept →
nuke7–13-0.0112%24 Sept →
dust212–12-0.0410%23 Sept →
ancient13–6-0.036%23 Sept →
nuke11–13-0.0912%16 Sept →
mirage13–1-0.0313%16 Sept →
dust213–60.0332%16 Sept →
ancient8–00.0817%16 Sept →
dust211–130.0415%15 Sept →
nuke8–13-0.047%15 Sept →
overpass12–12-0.0214%15 Sept →
dust26–13-0.0521%15 Sept →
ancient13–10-0.0113%15 Sept →
mirage13–60.0513%15 Sept →
overpass9–130.0121%14 Sept →
nuke13–8-0.0613%14 Sept →
dust213–6-0.0021%14 Sept →
overpass4–13-0.057%11 Sept →
mirage13–40.0136%11 Sept →
nuke13–70.0212%11 Sept →
ancient10–13-0.0522%25 Aug →
dust213–9-0.028%25 Aug →
mirage11–13-0.036%23 Aug →
nuke13–60.0215%22 Aug →
ancient9–130.008%18 Jul →
mirage15–15-0.055%17 Jul →
mirage7–13-0.029%17 Jul →
ancient13–11-0.033%17 Jul →
train8–13-0.073%15 Jul →
train9–130.029%30 Jun →
ancient13–4-0.006%30 Jun →
nuke13–60.049%28 Jun →
train2–13-0.0115%21 Jun →
mirage10–13-0.0412%20 Jun →
anubis10–130.0011%19 Jun →
dust213–11-0.017%19 Jun →
anubis3–5-0.000%19 Jun →
dust210–13-0.088%17 Jun →
inferno4–13-0.0710%16 Jun →
nuke13–40.049%16 Jun →
nuke13–11-0.0315%16 Jun →
anubis8–13-0.106%15 Jun →
inferno13–16-0.0317%14 Jun →
train14–16-0.048%12 Jun →
inferno13–10-0.027%12 Jun →
nuke13–40.025%12 Jun →
mirage13–8-0.018%12 Jun →
ancient5–13-0.0513%12 Jun →
dust213–6-0.0219%12 Jun →
anubis13–10-0.027%12 Jun →
mirage15–15-0.064%11 Jun →
ancient13–110.0014%11 Jun →
inferno4–13-0.068%11 Jun →
dust213–20.0515%11 Jun →
anubis13–11-0.0410%11 Jun →
nuke12–120.0113%10 Jun →
dust210–130.0125%10 Jun →
train13–60.0114%30 May →
ancient13–9-0.0519%29 May →
ancient4–13-0.049%29 May →
mirage8–2-0.044%29 May →
train7–13-0.0313%24 May →
mirage7–13-0.0313%23 May →
dust213–100.0110%18 May →
anubis4–13-0.0521%7 Apr →
ancient13–10-0.0317%20 Mar →

Match data via Leetify.

Recent teammates

Milestones

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

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.