Sir_banana123

Sir_banana123 — CS2 Stats

76561199494320191[U:1:1534054463]Steam profile ↗✓ No bans

92Tracked matches60%Win rate2026Tracked since
CSDB Rating1.8 LearningPositional Player
Ladder ranks via Leetify

Performance scores

Aim7
Positioning21
Utility11

0–100 skill scores via Leetify.

Recent form

STEADY40–48–3Last 9144%Win rateLLWWLWWWWL

Last 10 vs previous 10: −10pp win rate · +0.01 avg rating · +5.7pp headshot accuracy · −87ms 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

  • 2–3 · 40% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 14%
  • Avg reaction 614ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 14%
  • Avg reaction 634ms

Last 20

  • 13–7 · 65% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 11%
  • Avg reaction 677ms

Newest first, from the last 91 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 against its own average).

Aim0.7
Utility1.1
Positioning2.1
Opening Duels0.0

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

jL

Plays most like jL 72% 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. 685ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 56% 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

Aim0.7
Positioning2.1
Utility1.1
Mechanics1.4
Opening Duels0.0
Win Impact8.3

Composite 1.8/10 (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+0.00
first ⅓ avg -0.06 → last ⅓ avg -0.05
Reaction time689ms−26ms
first ⅓ avg 716ms → last ⅓ avg 689ms
Headshot accuracy11.5%−2.2%
first ⅓ avg 13.6% → last ⅓ avg 11.5%

Rolling 5-match average across the last 91 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.06Best match rating · 13–11 · nuke, 11 Aug →
32%Best headshot accuracy · 2–13 · anubis, 17 Aug →
523msFastest reaction time · 13–8 · inferno, 8 Sept →
13–2Biggest win · dust2, 2 Oct →

Across the last 91 tracked matches.

Highlights

5Longest win streak
L2Current streak
11–6In matches decided by ≤2 rounds

Map breakdown

mirageBest map · 60% over 5infernoWeakest map · 38% over 16
MapGradePlayedRecordWin rateAvg rating
dust2C4118–2344%-0.05
infernoC166–1038%-0.05
trainC83–538%-0.07
nukeC83–538%-0.02
anubisB63–350%-0.05
mirageA53–260%-0.07
cache—32–167%-0.03
ancient—21–150%-0.05
overpass—21–150%-0.06

Across the last 91 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (38% over 16). Start with the 6 essential Inferno 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.

11.8%Headshot accuracy
27.0%Accuracy (enemy spotted)
26.1%Spray accuracy
56.1%Counter-strafing
16.1°Preaim
685msReaction time
11.9%T opening success
17.9%CT opening success
0.38Enemies flashed / flash
1.4%Flash assists
1.57HE damage / grenade
1.70Flashes / 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 16.0731° — 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 11.7599% — below the 15% mark we flag

    Aim Training →
  3. 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 0.3777 — below the 0.5 mark we flag

    Grenade Lineups →
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.

38% win rate across 16 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage5–13-0.0413%9 Oct →
inferno1–13-0.0718%9 Oct →
dust213–2-0.0017%2 Oct →
dust213–11-0.0417%2 Oct →
dust27–13-0.064%13 Sept →
dust213–11-0.0523%8 Sept →
inferno13–8-0.0113%8 Sept →
inferno13–11-0.087%4 Sept →
cache13–10-0.0321%3 Sept →
train1–13-0.077%30 Aug →
inferno5–13-0.120%29 Aug →
mirage13–11-0.146%29 Aug →
dust28–13-0.079%28 Aug →
dust213–4-0.096%28 Aug →
nuke13–20.062%26 Aug →
ancient13–8-0.0511%26 Aug →
inferno13–6-0.0220%26 Aug →
mirage13–3-0.0611%26 Aug →
dust26–13-0.0813%26 Aug →
cache13–10-0.005%24 Aug →
nuke10–90.017%24 Aug →
dust210–13-0.0517%24 Aug →
train13–8-0.0912%23 Aug →
dust213–11-0.0316%23 Aug →
train8–13-0.118%22 Aug →
dust213–6-0.0715%22 Aug →
dust28–13-0.0418%22 Aug →
dust20–13-0.0710%22 Aug →
anubis5–13-0.0613%21 Aug →
anubis13–3-0.098%19 Aug →
dust24–13-0.0114%19 Aug →
dust213–8-0.0423%19 Aug →
nuke5–13-0.0118%19 Aug →
dust213–11-0.0617%19 Aug →
anubis7–13-0.0419%19 Aug →
train11–13-0.097%18 Aug →
train13–50.0030%18 Aug →
nuke6–8-0.0213%18 Aug →
dust213–10-0.0419%18 Aug →
train9–13-0.0517%17 Aug →
anubis2–13-0.1132%17 Aug →
dust26–20.0314%17 Aug →
inferno13–60.0525%13 Aug →
train8–13-0.0510%13 Aug →
dust28–13-0.099%12 Aug →
nuke13–110.0622%11 Aug →
inferno11–13-0.0913%11 Aug →
inferno7–13-0.079%9 Aug →
anubis13–11-0.0816%9 Aug →
inferno11–13-0.0315%7 Aug →
inferno13–5-0.057%7 Aug →
dust22–13-0.0518%6 Aug →
dust23–13-0.0713%4 Aug →
inferno12–12-0.0511%4 Aug →
dust212–12-0.0711%4 Aug →
dust213–5-0.035%4 Aug →
cache5–13-0.0519%3 Aug →
anubis13–50.0518%2 Aug →
dust213–9-0.0522%2 Aug →
mirage13–6-0.059%2 Aug →
mirage8–13-0.0723%31 Jul →
dust212–12-0.0626%31 Jul →
dust210–13-0.0613%29 Jul →
nuke5–13-0.084%29 Jul →
overpass5–13-0.0911%28 Jul →
dust213–9-0.0415%28 Jul →
dust21–13-0.096%25 Jul →
train13–11-0.0713%25 Jul →
inferno2–13-0.018%23 Jul →
dust27–13-0.027%23 Jul →
overpass13–3-0.0224%21 Jul →
dust28–13-0.0712%21 Jul →
inferno6–13-0.0421%21 Jul →
dust24–13-0.0517%21 Jul →
inferno8–5-0.030%21 Jul →
dust24–13-0.0213%20 Jul →
dust26–13-0.068%20 Jul →
dust22–13-0.0510%20 Jul →
dust27–13-0.1311%20 Jul →
inferno10–13-0.0817%20 Jul →
nuke11–13-0.0911%20 Jul →
dust213–20.0110%18 Jul →
nuke11–13-0.0619%18 Jul →
dust213–11-0.0414%16 Jul →
inferno8–13-0.0724%16 Jul →
dust213–7-0.0615%16 Jul →
dust213–8-0.0214%12 Jul →
dust24–13-0.0713%12 Jul →
ancient1–13-0.0618%12 Jul →
dust213–10-0.0322%11 Jul →
dust22–13-0.1316%4 Jul →

Match data via Leetify.

Recent teammates

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

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