Sexolog Dennis

Sexolog Dennis — CS2 Stats

NO76561198426921248[U:1:466655520]Steam profile ↗5 game bans

233Tracked matches52%Win rate2020Tracked since
166Hours in CS
CSDB Rating3.8 LearningPositional Player
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 13,078 +1,306 26 Feb – 22 Apr · 33 days played
10,10214,115peak 14,11526 Feb22 Apr
14,115Peak Premier in tracked matches
41Days played since 2025-02-26

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Performance scores

Aim37
Positioning44
Utility22

0–100 skill scores via Leetify.

Recent form

STEADY49–48–3Last 10049%Win rateLLWLLWWWTL

Last 10 vs previous 10: 0pp win rate · −0.03 avg rating · +0.5pp headshot accuracy · +48ms reaction

Win rate 0pp 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

  • 1–4 · 20% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 11%
  • Avg reaction 678ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 13%
  • Avg reaction 655ms

Last 20

  • 8–11–1 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 13%
  • Avg reaction 630ms

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: Positional Player — Positioning stands above the rest of this profile (+2 against its own average).

Aim3.7
Utility2.2
Positioning4.4
Opening Duels0.7

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

b1t

Plays most like b1t 80% playstyle similarity

Most alike: positioning profile, utility contribution.

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. 615ms 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

Aim3.7
Positioning4.4
Utility2.2
Mechanics5.7
Opening Duels0.6
Win Impact5.6

Composite 3.8/10 (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-0.03−0.01
first ⅓ avg -0.02 → last ⅓ avg -0.03
Reaction time628ms+25ms
first ⅓ avg 602ms → last ⅓ avg 628ms
Headshot accuracy12.7%−0.4%
first ⅓ avg 13.0% → last ⅓ avg 12.7%

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

0.10Best match rating · 13–3 · ancient, 1 Apr →
33%Best headshot accuracy · 1–13 · ancient, 28 Feb →
438msFastest reaction time · 3–13 · dust2, 6 Apr →
13–2Biggest win · ancient, 8 Apr →

Across the last 100 tracked matches.

Highlights

3Longest win streak
L2Current streak
6–8In matches decided by ≤2 rounds
8Overtime games

Map breakdown

ancientBest map · 63% over 24nukeWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
ancientA2415–963%-0.01
dust2C2310–1343%-0.03
infernoB1910–953%-0.03
anubisD93–633%-0.03
agencyB84–450%-0.01
mirageC83–538%-0.02
nukeD51–420%-0.01
train—43–175%0.00

Across the last 100 tracked matches.

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

Lifetime stats

6,075Lifetime kills
0.82K/D
409Matches
47.2%Match win rate · Top 50% of tracked players
40.1%Headshot %
8.1%Shot accuracy
834MVPs
166Hours (in match)
472Bombs planted
61Bombs defused

Most-used weapons

Lifetime map wins

953dust2
655inferno
181nuke
139train
72vertigo
44office

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
30.4%Accuracy (enemy spotted)
31.5%Spray accuracy
75.5%Counter-strafing
12.4°Preaim
615msReaction time
33.6%T opening success
31.6%CT opening success
0.55Enemies flashed / flash
3.2%Flash assists
8.75HE damage / grenade
9.99Flashes / 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 12.3743° — 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 12.0382% — below the 15% mark we flag

    Aim Training →
Spend your practice time on Nuke

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.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient7–13-0.044%19 Jul →
inferno6–13-0.1113%19 Jul →
dust216–12-0.1015%23 Jun →
ancient11–130.0615%29 Aug →
agency2–13-0.036%15 May →
agency13–9-0.0218%15 May →
agency13–6-0.0421%12 May →
agency13–6-0.027%12 May →
agency12–12-0.0014%10 May →
agency5–13-0.0415%9 May →
agency9–13-0.019%9 May →
agency13–50.0912%9 May →
dust23–13-0.0320%22 Apr →
mirage3–130.0121%18 Apr →
ancient13–11-0.028%18 Apr →
anubis11–13-0.0011%17 Apr →
ancient10–13-0.0313%17 Apr →
dust213–100.0116%15 Apr →
dust27–13-0.116%15 Apr →
ancient13–10-0.007%14 Apr →
anubis13–8-0.073%13 Apr →
dust213–6-0.0112%13 Apr →
anubis4–13-0.038%11 Apr →
inferno13–7-0.019%11 Apr →
inferno13–9-0.0213%11 Apr →
anubis13–10-0.0411%10 Apr →
anubis11–13-0.0114%10 Apr →
nuke13–110.0116%10 Apr →
inferno6–13-0.0315%10 Apr →
ancient13–9-0.078%8 Apr →
dust28–13-0.0710%8 Apr →
mirage13–3-0.0128%8 Apr →
ancient13–2-0.0318%8 Apr →
dust22–13-0.118%7 Apr →
inferno13–8-0.0224%7 Apr →
ancient13–70.0118%7 Apr →
dust215–150.0318%7 Apr →
ancient13–40.0918%7 Apr →
dust23–13-0.118%6 Apr →
dust211–130.0310%4 Apr →
mirage6–13-0.048%4 Apr →
dust210–130.0110%3 Apr →
nuke4–100.0124%3 Apr →
train13–90.0416%3 Apr →
inferno13–40.0213%3 Apr →
ancient13–70.019%3 Apr →
mirage9–13-0.0016%3 Apr →
mirage16–14-0.0218%2 Apr →
ancient13–40.0313%2 Apr →
mirage0–13-0.068%2 Apr →
dust213–20.0115%1 Apr →
dust213–5-0.0013%1 Apr →
inferno8–13-0.0314%1 Apr →
anubis9–13-0.028%1 Apr →
ancient0–2-0.030%1 Apr →
ancient13–30.1015%1 Apr →
ancient13–7-0.0720%1 Apr →
dust213–110.0421%1 Apr →
inferno9–13-0.049%29 Mar →
train2–13-0.0711%28 Mar →
ancient13–30.0610%27 Mar →
dust213–7-0.0315%27 Mar →
anubis11–13-0.0210%27 Mar →
ancient10–13-0.0510%27 Mar →
dust28–13-0.0112%26 Mar →
inferno13–6-0.0414%26 Mar →
inferno6–13-0.0916%24 Mar →
anubis13–20.0215%23 Mar →
ancient13–7-0.048%23 Mar →
mirage16–140.0320%23 Mar →
inferno9–130.0010%22 Mar →
inferno4–13-0.0315%14 Mar →
dust213–4-0.0513%14 Mar →
inferno13–70.0319%14 Mar →
mirage15–15-0.0312%13 Mar →
nuke4–13-0.0412%13 Mar →
dust213–60.0714%13 Mar →
inferno16–13-0.0317%13 Mar →
ancient4–13-0.069%12 Mar →
inferno13–8-0.0415%11 Mar →
dust214–16-0.0412%11 Mar →
inferno13–8-0.014%10 Mar →
dust25–1-0.1025%10 Mar →
ancient13–90.0117%8 Mar →
nuke13–16-0.0511%7 Mar →
anubis10–13-0.097%7 Mar →
train13–60.0615%7 Mar →
inferno13–90.0314%6 Mar →
ancient5–11-0.038%1 Mar →
ancient13–70.0311%1 Mar →
train13–7-0.018%1 Mar →
ancient1–13-0.0633%28 Feb →
ancient13–11-0.021%28 Feb →
inferno8–13-0.068%28 Feb →
dust27–130.0414%28 Feb →
dust211–13-0.0312%27 Feb →
ancient8–130.0113%27 Feb →
dust27–13-0.0914%27 Feb →
nuke7–130.038%26 Feb →
inferno2–13-0.0714%26 Feb →

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 →

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