Jonnyboy

Jonnyboy — CS2 Stats

AL76561198752221744[U:1:791956016]Steam profile ↗✓ No bans

72Tracked matches43%Win rate2026Tracked since
CSDB Rating3.9 LearningSupport
WingmanGold Nova I
Ladder ranks via Leetify

Performance scores

Aim50
Positioning40
Utility43

0–100 skill scores via Leetify.

Recent form

STEADY28–39–5Last 7239%Win rateWWWLLLWLLW

Last 10 vs previous 10: +10pp win rate · +0.03 avg rating · −3.1pp headshot accuracy · −80ms 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

  • 3–2 · 60% win rate
  • Avg rating 0.04
  • Avg headshot accuracy 12%
  • Avg reaction 517ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 10%
  • Avg reaction 570ms

Last 20

  • 9–11 · 45% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 12%
  • Avg reaction 610ms

Newest first, from the last 72 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 (+1.5 against its own average).

Aim5.0
Utility4.3
Positioning4.0
Opening Duels0.0

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

iM

Plays most like iM 80% 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. 598ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 70% 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

Aim5.0
Positioning4.0
Utility4.3
Mechanics4.4
Opening Duels0.6
Win Impact2.8

Composite 3.9/10 (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 rating0.01+0.03
first ⅓ avg -0.02 → last ⅓ avg 0.01
Reaction time593ms+20ms
first ⅓ avg 574ms → last ⅓ avg 593ms
Headshot accuracy11.7%−0.9%
first ⅓ avg 12.6% → last ⅓ avg 11.7%

Rolling 5-match average across the last 72 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.25Best match rating · 9–2 · vertigo, 28 Oct →
33%Best headshot accuracy · 13–2 · anubis, 23 Sept →
375msFastest reaction time · 13–2 · anubis, 23 Sept →
13–0Biggest win · anubis, 24 Oct →

Across the last 72 tracked matches.

Highlights

3Longest win streak
W3Current streak
2–4In matches decided by ≤2 rounds

Map breakdown

anubisBest map · 55% over 11infernoWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
dust2B157–847%-0.00
anubisA116–555%0.02
vertigoD113–827%-0.01
nukeC104–640%-0.03
mirageD103–730%-0.03
infernoD61–517%0.01
office—31–233%-0.01
cache—21–150%-0.01
ancient—21–150%-0.01
fachwerk—10–10%-0.08
overpass—11–0100%0.08

Across the last 72 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (17% over 6). 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.

13.5%Headshot accuracy
32.7%Accuracy (enemy spotted)
32.3%Spray accuracy
69.8%Counter-strafing
9.2°Preaim
598msReaction time
28.3%T opening success
35.0%CT opening success
0.45Enemies flashed / flash
4.6%Flash assists
7.99HE damage / grenade
12.20Flashes / 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 13.4575% — 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 0.4546 — 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 28.2918% — below the 40% mark we flag

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.

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke13–100.0513%3 Nov →
nuke9–6-0.025%31 Oct →
inferno9–50.1226%31 Oct →
dust28–130.049%31 Oct →
nuke3–130.008%31 Oct →
dust210–130.0111%30 Oct →
dust213–80.038%30 Oct →
cache8–13-0.056%30 Oct →
nuke7–130.029%29 Oct →
ancient13–80.139%29 Oct →
inferno5–9-0.0410%29 Oct →
nuke13–70.0218%29 Oct →
mirage4–130.027%29 Oct →
anubis9–4-0.0013%29 Oct →
mirage0–13-0.0815%29 Oct →
ancient0–6-0.1511%29 Oct →
vertigo9–20.2516%28 Oct →
dust210–130.044%28 Oct →
mirage4–13-0.0620%28 Oct →
dust213–60.0721%28 Oct →
vertigo7–9-0.105%26 Oct →
anubis6–13-0.0310%26 Oct →
dust27–13-0.0515%25 Oct →
nuke6–90.0313%25 Oct →
mirage13–90.0512%25 Oct →
office5–13-0.0020%25 Oct →
inferno8–80.0616%25 Oct →
cache13–100.0313%25 Oct →
anubis13–110.1518%25 Oct →
nuke9–13-0.0615%24 Oct →
anubis13–00.0816%24 Oct →
anubis13–70.0325%24 Oct →
vertigo13–2-0.0125%24 Oct →
anubis7–11-0.0318%22 Oct →
nuke9–4-0.0414%20 Oct →
inferno7–90.0016%20 Oct →
vertigo3–9-0.1210%20 Oct →
inferno3–13-0.0713%20 Oct →
dust213–10-0.0315%19 Oct →
dust213–70.0113%19 Oct →
mirage3–13-0.103%19 Oct →
dust28–13-0.0415%18 Oct →
office13–40.0714%18 Oct →
vertigo3–11-0.093%18 Oct →
dust213–5-0.0310%18 Oct →
vertigo3–9-0.097%18 Oct →
dust213–9-0.008%17 Oct →
mirage10–13-0.0415%11 Oct →
dust24–13-0.0926%11 Oct →
dust213–7-0.069%6 Oct →
nuke3–9-0.1810%2 Oct →
dust25–13-0.0326%29 Sept →
vertigo1–13-0.0213%29 Sept →
dust211–130.1414%29 Sept →
anubis3–13-0.096%27 Sept →
vertigo4–13-0.0212%27 Sept →
vertigo12–120.0113%26 Sept →
anubis1–130.0014%26 Sept →
mirage12–12-0.040%26 Sept →
mirage13–5-0.039%26 Sept →
fachwerk3–13-0.088%26 Sept →
anubis13–80.0313%25 Sept →
mirage4–13-0.0210%25 Sept →
nuke7–9-0.1215%25 Sept →
inferno12–120.0010%25 Sept →
vertigo12–12-0.015%24 Sept →
overpass9–60.0817%24 Sept →
office0–13-0.1011%23 Sept →
mirage13–110.0117%23 Sept →
anubis13–2-0.0233%23 Sept →
vertigo13–90.076%23 Sept →
anubis5–130.088%21 Sept →

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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