← Italy

MonoNukeLeosi

#5,450 in the world · #491 in Italy · in the top 12% nationally. 28 official events, 58 matches won and 24 lost.

  • 1649±36Rating · margin ±36
  • 1503Average field · 9 entr.
  • 0%vs top 5% (0–1)

What they have done so far

  • Has won 6 tournaments. The biggest one had 10 players entered.
  • Made top 8 26 times in 28 tournaments: 93% of the time.
  • Their best run is 3 tournaments in a row with the rating going up.
  • Their all-time peak is 1,708 points.
  • The toughest field they have faced averaged 1,533 points, across 24 entrants.
  • They are 51 points away from the top 250: Italy.

How the rating moved

Between 1,455 and 1,701, across 28 events with history.

Last 28 events

Date Event Entrants Field Pos. Record Rating
01/09/26 Tuesday Morning Nexus Nights - 1v1 Palermo 10 1491 3–1 +9
19/08/26 Wednesday Afternoon Vendetta Summoner Skirmish I Palermo 9 1486 2–1–1 -6
06/08/26 Thursday Morning Nexus Nights - 1v1 Palermo 10 1491 2–1–1 -5
28/07/26 Tuesday Afternoon Nexus Nights - Multiplayer Palermo 10 1491 0–0–1 -7
23/07/26 Thursday Afternoon Nexus Nights - 1v1 Palermo 10 1491 2–1–1 -6
17/07/26 Friday Morning Nexus Nights - Multiplayer Palermo 9 1504 0–0–1 -6
09/07/26 Monday Afternoon Summoner Skirmish - July Palermo 9 1491 6–0 +53
02/07/26 La scimmia nerd Nexus Nights - Multiplayer Palermo 9 1491 3–1 +15
24/06/26 Wednesday Evening Nexus Nights - 1v1 Palermo 9 1491 3–1 +19
18/06/26 Monday Afternoon Summoner Skirmish - June Palermo 9 1491 0–3 -48
04/06/26 Thursday Evening Nexus Nights - 1v1 Palermo 8 1508 1–2 -28
27/05/26 Wednesday Evening Nexus Nights - 1v1 Palermo 10 1491 2–1–1 -14
20/05/26 Wednesday Evening Nexus Nights - Multiplayer Palermo 10 1491 0–0–1 -8
13/05/26 Wednesday Afternoon Nexus Nights - 1v1 Palermo 7 1515 2–1 +2
04/05/26 Monday Afternoon Unleashed Pre-Rift Event Palermo 8 1494 2–1 -8
03/05/26 Friday Afternoon Unleashed Pre-Rift Event Palermo 9 1504 2–1–1 -14
28/04/26 Tuesday Afternoon Riftbound Open Play Palermo 10 1484 4–0 +29
21/04/26 martedì Afternoon Summoner Skirmish - April Palermo 10 1484 5–1 +18
15/04/26 Tuesday Afternoon Riftbound Open Play Palermo 6 1522 3–0 +26
09/04/26 Thursday Morning Learn-to-Play Event Palermo 9 1486 0–0–1 -8
25/03/26 mercoledì Afternoon Summoner Skirmish - March Palermo 10 1474 6–0 +54
25/02/26 Wednesday Afternoon Nexus Nights - 1v1 Palermo 7 1493 2–0–1 +27
17/02/26 Tuesday Evening Nexus Nights - 1v1 Palermo 6 1514 3–0 +61
08/02/26 PRE-RELEASE Spiritforged Pre-Rift Event Palermo 24 1533 21° 0–1–1 -20
06/02/26 venerdì Afternoon Spiritforged Pre-Rift Event Palermo 11 1513 3–1 +59
18/01/26 venerdì Afternoon Summoner Skirmish - January Palermo 6 1573 1–2 -7
21/12/25 mercoledì Afternoon Summoner Skirmish - December Palermo 6 1580 1–2 +1
01/11/25 Prerelease Riftbound Origins - Sabato 1 SICILIA 5 0–2 -39

Form and consistency

On a 3-win streak.

  • 16 to 99 1 events 0%
  • Under 16 27 events 64%

The overall win rate hides this difference: some players dominate at their store and vanish at regionals. Here you can see it.

Toughest opponents faced

Sorted by the opponent's rating, with the head-to-head record. Beating a 1900-rated player counts for more than six wins against a regular at your local store.

What the Field column means

Two columns Elo alone cannot give you. Field is the average rating of the opponents a player actually faced, with how many entrants their events had on average: the same score can be built grinding eight-player events against unrated opposition, or playing 200-player regionals. When the field stays around 1500 or events run under 16 entrants, the number is flagged. vs top 5% answers the same question match by match: how many they won against the 2,503 players rated above 1700. The gap is stark — some sit at 59%, others with a higher Elo sit at 30%. Computing these takes the full entry list of every event plus a rating system: sites that start from decklists cannot.

Ratings recomputed on 2026-09-02 05:41. The calculation runs twice a day on public standings from UVS Games events: between runs the scores do not change. How we compute the ranking →

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