EXM 1-0 THA · 49% SEA 2-1 REA · 56% AND 0-0 MAL · 52% NET 1-1 GER · 53% SER 1-0 GRE · 54% POR 2-0 WAL · 61% NOR 1-1 DEN · 53% AUS 2-0 ISR · 58% KOS 1-1 REP · 51% LIE 0-1 LIT · 59% BOR 2-1 WER · 63% RBL 2-1 EIN · 62% 189 2-1 HAM · 60% SCF 2-0 FCS · 63% EXM 1-0 THA · 49% SEA 2-1 REA · 56% AND 0-0 MAL · 52% NET 1-1 GER · 53% SER 1-0 GRE · 54% POR 2-0 WAL · 61% NOR 1-1 DEN · 53% AUS 2-0 ISR · 58% KOS 1-1 REP · 51% LIE 0-1 LIT · 59% BOR 2-1 WER · 63% RBL 2-1 EIN · 62% 189 2-1 HAM · 60% SCF 2-0 FCS · 63%
SHL · Week 2 Sep 24, 2026 · 17:00 Not Started

Farjestad
vs
Rögle.

Quick answer

Who will win Farjestad vs Rögle?

7 of 10 AI models pick Rögle to win (70%). The mean predicted score is 2–3 at 59% average confidence (medium).

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

10 AI models read this game. The plurality on the winner leans toward Rögle (7 of 10 models). The mean predicted score (rounded from all models) is 2–3 at 59% 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 Farjestad beat Rögle 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.

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— Consensus

Where the panel lands.

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

Farjestad win 30%

3 / 10 models

Rögle win 70%

7 / 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
Rögle win
3–4
62%
Rögle won four of the five latest meetings, including three in Farjestad, suggesting a matchup edge. Early-season uncertainty and home ice keep this close rather than projecting another decisive result.
02
Claude Sonnet 5
Rögle win
2–3
55%
Rögle won four of last five meetings with strong scoring, suggesting a stylistic edge that likely persists early this season despite home ice for Farjestad.
03
Gemini 3.8 Flash
Farjestad win
3–2
58%
Färjestad hold strong regular-season home ice advantage in Karlstad, giving them a narrow edge over a competitive Rögle squad.
04
Grok 4.6
Farjestad win
3–2
55%
Rögle won four of five April meetings, but this is Week 3 SHL at Farjestad; home ice and early-season variance point to a tight home win.
05
DeepSeek V4 Pro
Rögle win
2–3
58%
Rögle have won four of the last five H2H meetings, often scoring heavily; Farjestad's home edge keeps it close but not enough to reverse the trend.
06
Qwen 3.8 Max
Rögle win
2–3
62%
Rögle dominated the recent H2H series 4-1, winning four of five meetings convincingly. Early-season form and momentum favor Rögle despite Farjestad's home advantage.
07
Mistral Medium 3.5
Rögle win
3–4
65%
Rögle dominated recent H2H with strong offense; Farjestad struggles to contain them.
08
Kimi K3
Rögle win
2–4
62%
Rögle dominated the recent H2H series, winning four of five meetings including a 7-2 blowout, suggesting a stylistic edge that persists despite roster changes. Farjestad's home ice provides some resistance, but Rögle's superior offensive depth should secure the win.
09
GLM 5.3
Farjestad win
3–2
52%
Rögle dominated recent H2H, but new season rosters limit that signal; Farjestad's home ice in Karlstad gives a narrow edge in a tight matchup.
10
MiMo V2.5 Pro
Rögle win
2–3
62%
Rögle dominated recent H2H (4 wins in last 5), showing superior form and finishing. Farjestad's home venue offers some counter, but Rögle's momentum and scoring consistency suggest an away win.
— Scoreline frequency

How often each scoreline showed up.

4 of 10 models settled on 2–3. The rest of the list shows where dissent still lives before kickoff.

  • 2–3
    4 models
  • 3–2
    3 models
  • 3–4
    2 models
  • 2–4
    1 model

Match overview

Looking for a today prediction on Farjestad vs Rögle in SHL? 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 (2 - 3; 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 Rögle win, with vote shares roughly 30% / 70% home and away (rounded).

If you are asking who will win Farjestad vs Rögle, 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 Rögle

70% of models lean away — the clearest cluster on this fixture before kickoff.

02
Medium confidence

Mean 59% across the panel with real dispersion — compare unanimous calls vs split tickets in the model table.

03
xG tilt 2.50 vs 3.00

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

Explore more

Keep browsing today prediction coverage and league hubs.

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— Journal

Articles linked to these clubs or AI forecasting.

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.