Hugo Stiglitz

Hugo Stiglitz — CS2 Stats

PL76561198208267711[U:1:248001983]Steam profile ↗✓ No bans

1,595Tracked matches50%Win rate2023Tracked since
4,749Hours in CS33Hrs last 2 wks
CSDB Rating5.7 SolidPassive Rifler
Premier CS Rating25,000Top 25% of 17,162 CSDB-tracked playersRed band · top ~3% of ranked players (population est.)
CSDB Leaderboard#4198 of 32237 tracked
WingmanLegendary Eagle Master
Ladder ranks via Leetify

How this compares with the same rank

Median values for Red band among CSDB-tracked players (n=1,873), 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 playerRed band median
Headshot rate67.8%49.9%
Shot accuracy8.6%13.4%
Kill/death ratio0.831.12
Match win rate32.9%48.4%

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CSDB.GGHugo StiglitzPREMIER25,000 · Red bandcsdb.gg/stats

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Performance scores

Aim80
Positioning39
Utility31

0–100 skill scores via Leetify.

Recent form

COLD52426Last 10052%Win rateWTLLLLWWLL

Last 10 vs previous 10: -40pp win rate · -0.02 avg rating

Player DNA

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

Aim8.0
Aggression3.8
Utility3.1
Positioning3.9
Opening Duels0.9
Clutch4.0

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.

Your pro match

NiKo

Plays most like NiKo 82% playstyle similarity

Most alike: opening-duel success, opening-fight frequency.

Where you differ: lower positioning 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

Positioning. Positioning trails aim by 42 points — deaths here waste a strong aim profile.

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

Reaction time. 568ms 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

Aim8.0
Positioning3.9
Utility3.1
Mechanics7.6
Opening Duels1.3
Win Impact5.0

Composite 5.7/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.05 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.01
first ⅓ avg -0.02 → last ⅓ avg -0.02
Reaction time577ms−56ms
first ⅓ avg 633ms → last ⅓ avg 577ms
Headshot accuracy25.0%+4.5%
first ⅓ avg 20.5% → last ⅓ avg 25.0%

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

0.10Best rating — vertigo 9–3
131Biggest win — anubis
6Longest win streak
63In matches decided by ≤2 rounds
4Overtime games

Map breakdown

vertigoBest map · 80% over 5infernoWeakest map · 14% over 7
MapGradePlayedRecordWin rateAvg rating
mirageB22111150%-0.02
dust2A2011955%-0.03
cacheB189950%-0.02
ancientS107370%-0.01
anubisS86275%-0.04
infernoD71614%-0.03
nukeD72529%-0.02
vertigoS54180%0.04
train31233%0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (14% over 7). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

346,869Lifetime kills
0.83K/D
7,117Matches
32.9%Match win rate
67.8%Headshot % · Top 5% of Red band
8.6%Shot accuracy
14,379MVPs
8,493Hours (in match)
3,215Bombs planted
2,392Bombs defused

Most-used weapons

AK-47226,631
AWP14,575
FAMAS3,225
MP92,497

Lifetime map wins

8,920dust2
6,187inferno
4,312vertigo
2,415nuke
1,127train
876cbble
32office
28lake

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

Faceit stats

Combat

726Matches
53%Win rate
1.15Avg K/D
76.3ADR
51%Headshot %

Clutches & streaks

40%1v1 clutch win
16%1v2 clutch win
11Longest win streak

Recent Faceit resultsLLLLW

MapMatchesWin rateAvg K/DAvg kills
Ancient8751%1.0315.0
Mirage8149%1.0414.9
Anubis5052%1.1316.6
Dust23656%0.9314.1
Vertigo2959%1.0914.9
Inferno2157%1.1015.2
Nuke1953%1.0615.9
Train1155%0.9716.0

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.

24.8%Headshot accuracy
32.6%Accuracy (enemy spotted)
39.2%Spray accuracy
84.2%Counter-strafing
9.8°Preaim
568msReaction time
26.8%T opening success
40.5%CT opening success
0.44Enemies flashed / flash
2.6%Flash assists
4.83HE damage / grenade
4.85Flashes / 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. 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 0.437 — below the 0.5 mark we flag

    Grenade Lineups
  2. 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 26.7908% — 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.

14% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategyInferno grenade lineups

Recent matches

MapScoreRatingHS%Date
vertigo13–90.0530%29 Aug
dust212–12-0.0233%29 Aug
inferno4–13-0.0522%28 Aug
nuke11–13-0.0423%28 Aug
nuke2–13-0.0240%23 Aug
inferno7–13-0.0511%23 Aug
nuke6–3-0.0620%23 Aug
cache13–11-0.0417%23 Aug
dust27–130.0016%22 Aug
mirage6–13-0.1026%21 Aug
dust213–4-0.0027%21 Aug
mirage13–5-0.0215%21 Aug
ancient1–13-0.1014%21 Aug
mirage13–50.0115%21 Aug
mirage13–30.0224%21 Aug
dust213–9-0.0513%21 Aug
nuke13–100.0120%21 Aug
dust213–3-0.0427%21 Aug
cache9–13-0.0118%16 Aug
train10–130.0433%16 Aug
train13–70.0735%16 Aug
vertigo12–12-0.0430%16 Aug
dust20–13-0.0324%16 Aug
dust210–13-0.0729%15 Aug
vertigo13–20.0218%15 Aug
ancient3–13-0.0742%15 Aug
cache6–13-0.1041%15 Aug
mirage13–6-0.0222%15 Aug
cache9–13-0.0331%15 Aug
ancient13–10-0.0624%15 Aug
mirage13–100.0033%15 Aug
dust213–30.0026%15 Aug
cache12–160.0225%15 Aug
nuke6–13-0.0220%15 Aug
train8–13-0.0729%14 Aug
inferno5–13-0.0332%14 Aug
mirage8–13-0.0328%14 Aug
cache13–60.0234%14 Aug
dust27–13-0.0431%14 Aug
mirage2–13-0.0320%14 Aug
ancient13–8-0.0424%9 Aug
ancient11–13-0.0418%9 Aug
dust215–150.0224%9 Aug
cache13–40.0111%9 Aug
nuke11–13-0.0923%8 Aug
ancient13–70.0631%8 Aug
ancient13–110.0219%8 Aug
cache15–15-0.0314%7 Aug
mirage5–13-0.0724%7 Aug
inferno7–130.0014%7 Aug
anubis13–10-0.0612%7 Aug
cache5–13-0.0217%7 Aug
dust23–13-0.0525%7 Aug
ancient13–60.0526%7 Aug
anubis13–8-0.0126%7 Aug
dust21–6-0.0922%2 Aug
mirage13–5-0.0119%2 Aug
dust213–10-0.0831%2 Aug
anubis13–10.0028%2 Aug
mirage13–11-0.0228%1 Aug
dust213–70.0119%1 Aug
cache13–3-0.0427%1 Aug
mirage12–12-0.0326%1 Aug
dust213–5-0.0418%31 Jul
mirage13–30.0212%31 Jul
vertigo9–30.0411%31 Jul
vertigo9–30.1032%31 Jul
cache13–4-0.0419%30 Jul
ancient13–70.0619%30 Jul
dust24–13-0.0524%30 Jul
cache13–60.0226%30 Jul
mirage1–13-0.0613%30 Jul
cache13–3-0.0027%26 Jul
anubis0–13-0.050%26 Jul
dust213–70.0424%24 Jul
inferno2–9-0.1439%24 Jul
inferno8–80.0727%24 Jul
anubis2–13-0.0914%18 Jul
cache8–13-0.0016%18 Jul
mirage3–13-0.0424%18 Jul
nuke4–130.0722%18 Jul
mirage13–9-0.0611%18 Jul
anubis13–100.0114%18 Jul
dust213–60.0119%18 Jul
dust213–9-0.0119%18 Jul
ancient13–8-0.0016%18 Jul
mirage6–130.0317%18 Jul
mirage12–160.0320%12 Jul
dust213–9-0.0428%12 Jul
anubis13–8-0.0324%12 Jul
cache5–13-0.0336%12 Jul
mirage13–11-0.0620%11 Jul
inferno13–11-0.0118%11 Jul
cache13–60.0618%11 Jul
anubis13–11-0.0517%11 Jul
cache13–9-0.0031%11 Jul
mirage13–5-0.0031%11 Jul
mirage9–13-0.079%11 Jul
mirage7–13-0.0317%11 Jul
cache8–13-0.0619%10 Jul

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →