Ted_Logan

Ted_Logan — CS2 Stats

DE76561199875503413[U:1:1915237685]Steam profile ↗✓ No bans

107Tracked matches52%Win rate2025Tracked since
CSDB Rating5.0 DevelopingSupport
WingmanMaster Guardian II
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 10,116 -461 3 Jun – 30 Jun · 5 days played
10,11610,577peak 10,5773 Jun30 Jun
10,577Peak Premier in tracked matches
62Days played since 2025-09-17

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

Performance scores

Aim54
Positioning54
Utility58

0–100 skill scores via Leetify.

Recent form

STEADY52–40–8Last 10052%Win rateWLWWLWLWLW

Last 10 vs previous 10: +40pp win rate · −0.05 avg rating · +2.5pp headshot accuracy · +24ms reaction

Win rate up 40pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (−0.05), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 11%
  • Avg reaction 602ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 14%
  • Avg reaction 540ms

Last 20

  • 8–11–1 · 40% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 12%
  • Avg reaction 528ms

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: Support — Utility contribution stands above the rest of this profile (+1.2 against its own average).

Aim5.4
Utility5.8
Positioning5.4
Opening Duels2.7

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

NiKo

Plays most like NiKo 76% 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

Counter-strafing. Only 65% 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

Aim5.4
Positioning5.4
Utility5.8
Mechanics3.3
Opening Duels3.3
Win Impact5.6

Composite 5.0/10 (Developing), 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-0.01−0.00
first ⅓ avg -0.01 → last ⅓ avg -0.01
Reaction time550ms−61ms
first ⅓ avg 611ms → last ⅓ avg 550ms
Headshot accuracy12.8%−2.0%
first ⅓ avg 14.8% → last ⅓ avg 12.8%

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

0.13Best match rating · 13–3 · overpass, 3 Jun →
29%Best headshot accuracy · 3–13 · train, 3 Mar →
438msFastest reaction time · 1–9 · inferno, 7 Oct →
13–0Biggest win · train, 6 Jan →

Across the last 100 tracked matches.

Highlights

6Longest win streak
9–5In matches decided by ≤2 rounds
5Overtime games

Map breakdown

cacheBest map · 67% over 6dust2Weakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
infernoB3217–1553%-0.02
anubisB2211–1150%0.01
overpassA106–460%0.01
cacheS64–267%0.00
nukeC52–340%-0.03
dust2D51–420%-0.02
mirageA53–260%-0.00
vertigoC52–340%-0.01
trainA53–260%0.01
ancient—32–167%0.04
office—21–150%0.00

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Dust 2 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.

12.9%Headshot accuracy
36.1%Accuracy (enemy spotted)
33.9%Spray accuracy
64.7%Counter-strafing
10.3°Preaim
549msReaction time
45.7%T opening success
40.6%CT opening success
0.50Enemies flashed / flash
3.7%Flash assists
9.05HE damage / grenade
11.24Flashes / 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 12.8988% — 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 0.4971 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Dust 2

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.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno13–11-0.0417%29 Oct →
nuke7–13-0.0812%29 Oct →
inferno7–4-0.030%29 Oct →
inferno13–7-0.0521%25 Oct →
dust27–13-0.047%25 Oct →
cache13–110.0217%25 Oct →
nuke11–13-0.0614%19 Oct →
anubis16–130.0419%19 Oct →
inferno1–9-0.2421%7 Oct →
mirage13–60.0210%3 Oct →
vertigo13–90.0714%3 Oct →
vertigo10–13-0.036%26 Sept →
vertigo12–12-0.0310%25 Sept →
anubis6–13-0.0617%20 Sept →
dust27–13-0.039%20 Sept →
anubis6–13-0.0113%16 Sept →
inferno9–20.0810%12 Sept →
cache3–13-0.0512%10 Sept →
inferno10–13-0.0112%10 Sept →
inferno7–130.089%4 Sept →
inferno9–40.0416%25 Aug →
anubis13–110.0814%25 Aug →
inferno13–70.0117%6 Aug →
inferno13–30.098%31 Jul →
vertigo10–130.0315%31 Jul →
anubis13–80.0410%26 Jul →
anubis13–110.0112%21 Jul →
inferno13–80.0010%15 Jul →
office10–13-0.0616%11 Jul →
cache13–11-0.0313%8 Jul →
nuke13–11-0.0118%8 Jul →
cache9–13-0.047%4 Jul →
inferno6–13-0.0820%30 Jun →
inferno11–13-0.0310%30 Jun →
overpass7–13-0.0323%30 Jun →
train13–40.1020%23 Jun →
anubis13–16-0.048%22 Jun →
dust213–160.0215%19 Jun →
overpass12–12-0.0315%17 Jun →
dust27–13-0.037%17 Jun →
inferno6–13-0.0023%17 Jun →
inferno8–130.0113%16 Jun →
inferno6–13-0.0714%14 Jun →
overpass13–30.1324%3 Jun →
inferno13–90.014%3 Jun →
ancient13–80.0713%3 Jun →
inferno13–3-0.019%3 Jun →
cache13–60.1116%3 Jun →
anubis5–13-0.017%28 May →
anubis8–20.0420%28 May →
anubis8–13-0.0613%28 May →
ancient13–100.0310%26 May →
inferno13–7-0.0613%26 May →
cache13–80.0015%3 May →
inferno13–50.139%3 May →
inferno13–100.0016%20 Apr →
mirage3–13-0.0519%9 Apr →
anubis13–50.085%2 Apr →
overpass13–20.0520%26 Mar →
inferno3–13-0.026%19 Mar →
inferno12–120.0222%18 Mar →
dust213–10-0.0127%18 Mar →
overpass15–150.0113%13 Mar →
mirage13–50.0913%13 Mar →
overpass13–2-0.0114%13 Mar →
overpass7–9-0.0314%12 Mar →
inferno2–13-0.053%6 Mar →
train3–13-0.0429%3 Mar →
train12–12-0.0717%3 Mar →
ancient15–150.0016%18 Feb →
inferno13–20.0018%18 Feb →
anubis12–120.0316%10 Feb →
mirage13–6-0.037%10 Feb →
nuke5–13-0.0514%10 Feb →
office13–90.0712%21 Jan →
overpass13–30.0622%14 Jan →
inferno9–130.0312%12 Jan →
anubis13–110.0411%11 Jan →
train13–00.069%6 Jan →
inferno2–13-0.1219%24 Dec →
anubis12–12-0.017%24 Dec →
anubis8–13-0.046%18 Dec →
vertigo13–9-0.0710%18 Dec →
inferno13–10-0.0411%15 Dec →
anubis11–13-0.005%11 Dec →
overpass13–3-0.0314%19 Nov →
overpass13–8-0.0225%19 Nov →
train13–10-0.0211%6 Nov →
anubis11–130.0321%2 Nov →
inferno13–11-0.0318%2 Nov →
inferno10–13-0.0621%2 Nov →
anubis13–100.0916%24 Oct →
anubis13–90.0118%15 Oct →
nuke13–60.0418%15 Oct →
anubis13–80.0215%15 Oct →
anubis3–10.0223%15 Oct →
inferno13–6-0.0210%4 Oct →
inferno9–13-0.0214%23 Sept →
anubis3–13-0.0617%21 Sept →
mirage3–13-0.047%17 Sept →

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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