COM 1-2 ASR · 47% ELC 1-1 CEL · 45% CRY 1-1 NOT · 45% HUL 1-2 EVE · 45% NIC 2-1 STR · 46% LAZ 2-0 MON · 51% LEC 0-1 BOL · 43% 1.F 2-2 BOR · 42% REA 2-0 DEP · 51% REN 2-1 AUX · 47% LIV 1-1 MAN · 43% SCF 2-0 FCS · 54% SAS 1-2 ACM · 47% REA 2-1 OSA · 45% COM 1-2 ASR · 47% ELC 1-1 CEL · 45% CRY 1-1 NOT · 45% HUL 1-2 EVE · 45% NIC 2-1 STR · 46% LAZ 2-0 MON · 51% LEC 0-1 BOL · 43% 1.F 2-2 BOR · 42% REA 2-0 DEP · 51% REN 2-1 AUX · 47% LIV 1-1 MAN · 43% SCF 2-0 FCS · 54% SAS 1-2 ACM · 47% REA 2-1 OSA · 45%
KBO Oct 3, 2026 · 05:00 Finished

NC Dinos
vs
SSG Landers.

Quick answer

Who will win NC Dinos vs SSG Landers?

Final score: NC Dinos 13–1 SSG Landers. Before kickoff, 10 of 10 AI models pick SSG Landers to win (100%); the consensus was wrong. The AI predicted score was 7–8.

Consensus of independent AI models on TuringStats, updated before kickoff. Not betting advice.

All 10 AIs agree. When the whole council agrees, it has been right 58% of the time (234 games).

10 AI models read this game. The plurality on the winner leans toward SSG Landers (10 of 10 models). The mean predicted score (rounded from all models) is 7–8 at 56% mean confidence (Medium band) — see the strip and table below.

Who do you think will win?

Vote before kick-off and compare with AI

10 AI models · council in session Live match data · Pro

Still not sure? Ask 10 AIs at once:
“Will NC Dinos beat SSG Landers in their upcoming match?”

Every model votes yes or no and defends it in a sentence or two. Attach this match's last-5 form, head-to-head and the picks above so they argue from real data — then keep asking the same council follow-ups.

Ask the Council Free today · sign in with Google to convene the council
— Consensus

Where the panel lands.

Vote share across models. Read this strip first, then the line-by-line table.

NC Dinos win 0%

0 / 10 models

SSG Landers win 100%

10 / 10 models

— Model breakdown

10 picks. Receipts attached.

Line-by-line comparison of each system’s call.

#
Model
Pick
Score
Conf.
Reasoning
01
GPT-5.6 Luna
SSG Landers win
7–8
68%
SSG Landers won four of the five listed meetings, including three decisive victories, while NC Dinos allowed at least seven runs in those losses. Recent history supports an away edge, though roster changes limit confidence.
02
Claude Sonnet 5
SSG Landers win
7–8
58%
SSG Landers won 4 of last 5 meetings with strong run production, suggesting an edge in this high-scoring matchup despite NC Dinos hosting.
03
Gemini 3.8 Flash
SSG Landers win
4–6
62%
SSG Landers have dominated the head-to-head series with consistently explosive offense against NC Dinos' pitching, giving them the edge despite being on the road.
04
Grok 4.6
SSG Landers win
4–7
58%
SSG took four of five recent H2H games, often by large margins; NC home edge is modest against that scoring pattern.
05
DeepSeek V4 Pro
SSG Landers win
7–8
63%
SSG Landers have dominated recent H2H, winning four of five with strong run totals. NC Dinos' home edge is offset by SSG's superior recent scoring form.
06
Qwen 3.8 Max
SSG Landers win
4–6
62%
SSG dominated recent H2H convincingly, winning four of five meetings with strong offensive output. Their road form against NC suggests continued edge despite venue disadvantage.
07
Mistral Medium 3.5
SSG Landers win
7–8
68%
SSG Landers dominate recent H2H with higher scoring; NC Dinos struggle to contain their offense.
08
Kimi K3
SSG Landers win
4–6
62%
SSG Landers dominated recent H2H, outscoring NC Dinos 37-15 across five meetings. Their offensive consistency and NC's defensive struggles against them suggest another high-scoring away victory.
09
GLM 5.3
SSG Landers win
6–7
58%
SSG Landers won all five recent H2H meetings with strong scoring (10, 7, 12 runs), outpacing NC's offense despite venue edge; rosters may have shifted, so confidence stays moderate.
10
MiMo V2.5 Pro
SSG Landers win
6–7
62%
SSG Landers have dominated recent H2H, winning four of five, and show a consistent scoring pattern against NC Dinos, supporting an away win.
— Scoreline frequency

How often each scoreline showed up.

4 of 10 models settled on 7–8. The rest of the list shows where dissent still lives before kickoff.

  • 7–8
    4 models
  • 4–6
    3 models
  • 6–7
    2 models
  • 4–7
    1 model

Match overview

Looking for a today prediction on NC Dinos vs SSG Landers in KBO? TuringStats aggregates multiple AI scorelines into one readable page so you can see who the models favor, the mean predicted score shown in the hero (7 - 8; the frequency chart below lists the most common exact scorelines), and implied splits before kickoff.

This prediction hub is written for readers comparing betting tips-style language with transparent model votes — not a single black-box call. The headline read is SSG Landers win, with vote shares roughly 0% / 100% home and away (rounded).

If you are asking who will win NC Dinos vs SSG Landers, start with the consensus strip and model table, then cross-check form and injuries in Match context further down — that order keeps the strongest signals first.

— Aggregated insights

What’s moving the panel.

01
Consensus favors SSG Landers

100% of models lean away — the clearest cluster on this fixture before kickoff.

02
Medium confidence

Mean 56% across the panel with real dispersion — compare unanimous calls vs split tickets in the model table.

03
Expected runs tilt 5.60 vs 7.10

Derived from predicted scorelines (model means), not live game data — useful for pace vs vote-share sanity checks.

04
Match context

Expected-goals tilt and home-field rhythm (see xG on this page) usually explain whether the game stays open or compresses late.

Ask the Council about this match

Pro

10 AI models vote yes or no with this match's last-5 form, head-to-head, live status and the model picks above attached — not from memory. Then keep asking the same council follow-ups.

Confidence trend

Cumulative average confidence in table order.

First model Last model

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Ask multiple AIs about this match.

10 models vote yes or no with this match's last-5 form, head-to-head, live status and our model picks attached — not from memory. Then ask follow-ups to the same council.