Donald Trump

Donald Trump — CS2 Stats

76561199886961350[U:1:1926695622]Steam profile ↗✓ No bans

412Tracked matches33%Win rate2026Tracked since
1,067Hours in CS
CSDB Rating3.8 LearningPassive Rifler
Premier CS Rating2,229Grey band · top ~90.5% of ranked players (population est.)
CSDB Leaderboard#42211 of 53962 tracked
WingmanSilver II
Ladder ranks via Leetify

How this compares with the same rank

Median values for Grey band among CSDB-tracked players (n=369), 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 playerGrey band medianLight Blue band medianvs Light Blue band
Headshot rate33.1%37.5%39.7%6.6% short
Shot accuracy0.0%4.5%6.7%6.7% short
Kill/death ratio0.880.820.910.02 short
Match win rate38.0%39.1%42.1%4.1% short

This profile sits below the typical Light Blue band player on every metric we can compare.

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

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CSDB.GGDonald TrumpPREMIER2,229 · Grey bandcsdb.gg/stats

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Performance scores

Aim63
Positioning44
Utility12

0–100 skill scores via Leetify.

Recent form

COLD33625Last 10033%Win rateLWLLLLLLWL

Last 10 vs previous 10: +0pp win rate · +0.02 avg rating

Player DNA

Primary style: Passive RiflerAim-led profile without a single dominant tendency.

Aim6.3
Aggression4.2
Utility1.2
Positioning4.4
Opening Duels0.6

Strong CT-side openerLimited 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.

Your pro match

NiKo

Plays most like NiKo 73% playstyle similarity

Most alike: opening-fight frequency, positioning profile.

Where you differ: lower aim profile; lower utility contribution.

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

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

T-side openings. Opening success drops from 40% on CT to 25% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 717ms 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

Aim6.3
Positioning4.4
Utility1.2
Mechanics7.9
Opening Duels1.3
Win Impact0.0

Composite 3.8/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.01−0.02
first ⅓ avg 0.01 → last ⅓ avg -0.01
Reaction time697ms−14ms
first ⅓ avg 711ms → last ⅓ avg 697ms
Headshot accuracy12.6%−1.8%
first ⅓ avg 14.3% → 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.

Highlights

0.17Best rating — overpass 5–13
131Biggest win — mirage
3Longest win streak
68In matches decided by ≤2 rounds
5Overtime games

Map breakdown

mirageBest map · 50% over 14infernoWeakest map · 24% over 25
MapGradePlayedRecordWin rateAvg rating
infernoD2561924%-0.02
dust2C1871139%0.01
nukeC1661038%0.00
mirageB147750%0.01
ancientD62433%0.03
anubis41325%0.00
cache41325%0.03
vertigo3030%-0.07
train3030%0.00
overpass2020%0.12
eldorado21150%-0.01
debris21150%0.03
boulder110100%0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (24% over 25). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

12,203Lifetime kills
0.88K/D · Top 50% of Grey band
906Matches
38.0%Match win rate
33.1%Headshot %
0.0%Shot accuracy
2,103MVPs
1,067Hours (in match)
905Bombs planted
192Bombs defused

Most-used weapons

Lifetime map wins

1,201inferno
1,128nuke
1,003dust2
237vertigo
81train
17office
4italy
1ar_shoots

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.

12.0%Headshot accuracy
38.7%Accuracy (enemy spotted)
49.5%Spray accuracy
85.5%Counter-strafing
12.0°Preaim
717msReaction time
24.6%T opening success
40.1%CT opening success
0.27Enemies flashed / flash
0.9%Flash assists
3.40HE damage / grenade
1.69Flashes / 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 11.9821% — below the 15% mark we flag

    Aim Training
  2. Best CS2 Settings

    Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.

    Reaction time 716.6587ms — above the 700ms 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 0.2698 — 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.

24% win rate across 25 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
anubis13–16-0.023%30 Aug
inferno9–60.0323%30 Aug
inferno6–9-0.085%30 Aug
inferno2–13-0.0119%29 Aug
nuke5–130.0117%25 Aug
inferno7–130.010%23 Aug
vertigo0–13-0.070%23 Aug
mirage2–13-0.080%23 Aug
ancient13–50.1045%23 Aug
inferno6–9-0.0025%23 Aug
inferno3–9-0.1425%23 Aug
mirage13–80.0110%22 Aug
dust23–13-0.0919%22 Aug
dust22–13-0.075%22 Aug
nuke9–130.0315%22 Aug
ancient2–130.018%20 Aug
dust213–60.019%19 Aug
mirage5–13-0.0316%18 Aug
dust210–130.0018%18 Aug
nuke7–13-0.0417%17 Aug
inferno16–14-0.0511%17 Aug
mirage12–10.100%17 Aug
overpass8–80.078%17 Aug
dust23–130.007%17 Aug
nuke13–30.082%16 Aug
dust213–11-0.0612%16 Aug
nuke16–140.0517%16 Aug
train0–13-0.0025%15 Aug
inferno11–13-0.080%14 Aug
nuke4–13-0.0317%9 Aug
dust213–90.0016%9 Aug
inferno7–130.0013%9 Aug
nuke2–13-0.028%9 Aug
dust24–13-0.0621%8 Aug
mirage16–140.109%8 Aug
nuke13–90.037%8 Aug
dust20–8-0.060%7 Aug
anubis2–130.0012%5 Aug
inferno7–90.092%2 Aug
inferno3–90.0313%1 Aug
eldorado7–9-0.155%1 Aug
dust28–130.0512%30 Jul
nuke5–90.038%30 Jul
inferno7–13-0.0725%28 Jul
nuke4–00.000%28 Jul
mirage13–7-0.029%28 Jul
mirage13–10.054%28 Jul
vertigo3–9-0.1216%28 Jul
dust213–50.019%28 Jul
inferno4–9-0.0312%27 Jul
inferno0–9-0.3110%27 Jul
inferno6–9-0.148%27 Jul
debris9–30.167%27 Jul
cache4–130.0112%27 Jul
nuke7–70.0917%27 Jul
inferno8–80.0513%27 Jul
inferno12–120.058%22 Jul
cache7–10.086%21 Jul
mirage13–160.069%12 Jul
nuke4–130.0110%12 Jul
boulder13–40.0115%10 Jul
debris3–9-0.103%10 Jul
eldorado9–70.136%10 Jul
cache9–13-0.018%9 Jul
mirage4–13-0.0311%9 Jul
dust211–130.080%8 Jul
dust213–90.0713%8 Jul
inferno7–80.0713%6 Jul
anubis4–130.018%5 Jul
ancient7–13-0.028%3 Jul
mirage13–90.0212%3 Jul
inferno6–9-0.130%3 Jul
cache1–100.0511%2 Jul
mirage13–40.1016%29 Jun
inferno9–60.1321%28 Jun
ancient11–130.079%28 Jun
nuke2–4-0.0231%28 Jun
inferno3–9-0.0432%27 Jun
overpass5–130.1713%27 Jun
dust212–120.115%27 Jun
inferno13–40.0314%27 Jun
vertigo4–13-0.0112%27 Jun
train1–130.0310%27 Jun
dust213–7-0.0224%27 Jun
mirage3–13-0.0516%26 Jun
nuke13–8-0.0115%24 Jun
ancient7–130.0213%24 Jun
dust23–13-0.0320%24 Jun
inferno13–10.1227%24 Jun
nuke7–90.0413%24 Jun
nuke1–9-0.229%24 Jun
mirage4–13-0.107%24 Jun
ancient13–90.0120%24 Jun
inferno0–9-0.2125%24 Jun
dust213–60.1117%24 Jun
train0–13-0.0313%23 Jun
anubis13–60.029%23 Jun
inferno9–60.0913%23 Jun
dust212–120.1314%23 Jun
mirage10–13-0.055%23 Jun

Match data via Leetify.

Recent teammates

Milestones

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