KOR 1-0 SKB · 53% BRA 1-2 BOD · 57% SCP 1-2 189 · 58% MOD 1-1 EMP · 51% DIN 1-1 FAR · 53% SAN 1-1 BOC · 54% PAN 0-2 PAO · 63% LEC 2-0 RAD · 59% ACM 2-0 LEC · 66% MAR 1-2 PAR · 60% VAL 1-1 REA · 58% COR 1-0 FLU · 52% VIT 1-1 CRU · 50% LEG 1-0 GRA · 53% KOR 1-0 SKB · 53% BRA 1-2 BOD · 57% SCP 1-2 189 · 58% MOD 1-1 EMP · 51% DIN 1-1 FAR · 53% SAN 1-1 BOC · 54% PAN 0-2 PAO · 63% LEC 2-0 RAD · 59% ACM 2-0 LEC · 66% MAR 1-2 PAR · 60% VAL 1-1 REA · 58% COR 1-0 FLU · 52% VIT 1-1 CRU · 50% LEG 1-0 GRA · 53%
MLB Sep 17, 2026 · 01:38 Finished

Los Angeles Angels
vs
Seattle Mariners.

Quick answer

Who will win Los Angeles Angels vs Seattle Mariners?

Final score: Los Angeles Angels 2–7 Seattle Mariners. Before kickoff, 9 of 10 AI models pick Seattle Mariners to win (90%); the consensus was right.

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 Seattle Mariners (9 of 10 models). The mean predicted score (rounded from all models) is 4–5 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 Los Angeles Angels beat Seattle Mariners 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.

Los Angeles Angels win 10%

1 / 10 models

Seattle Mariners win 90%

9 / 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
Seattle Mariners win
4–5
60%
Seattle won three of the latest five meetings, including two clearly controlled victories and a 1-0 shutout. At Angels Stadium, I expect a competitive, moderately low-scoring game with the Mariners’ recent matchup edge deciding it.
02
Claude Sonnet 5
Seattle Mariners win
5–6
58%
Mariners have won 4 of last 5 head-to-head meetings, including a recent sweep-like stretch in late June/July, suggesting a favorable matchup continues.
03
Gemini 3.8 Flash
Seattle Mariners win
3–5
58%
Seattle's stronger pitching rotation and consistent success in mid-season matchups against the Angels give them a decisive late-game advantage on the road.
04
Grok 4.6
Seattle Mariners win
3–5
58%
July H2H was a Mariners sweep with 8-3 and 6-2 wins; April Angels home wins are older. Thin 2026 form, so a modest Seattle road edge in a typical-run game.
05
DeepSeek V4 Pro
Seattle Mariners win
2–4
61%
Mariners have won the last three meetings, including a 1-0 and 6-2, showing better pitching and late-game control; Angels' home edge is not enough to reverse that trend.
06
Qwen 3.8 Max
Seattle Mariners win
4–5
62%
Mariners won 3 of last 5 H2H including a dominant July series; Angels' offense has been inconsistent this season.
07
Mistral Medium 3.5
Seattle Mariners win
4–5
65%
Seattle's recent series sweep shows form edge over Angels.
08
Kimi K3
Seattle Mariners win
3–5
62%
Mariners won three straight over Angels in July 2026 by a combined 15-5, showing matchup control; Angels' bats went quiet in those games. Seattle's edge carries to a moderate road win.
09
GLM 5.3
Los Angeles Angels win
4–3
52%
Mariners won recent meetings but those were in Seattle; Angels took both home clashes in April. Home venue edge in a likely low-scoring AL West matchup.
10
MiMo V2.5 Pro
Seattle Mariners win
4–5
55%
Seattle Mariners won the last three meetings against Angels, showing recent dominance, though home venue may keep the margin moderate.
— Scoreline frequency

How often each scoreline showed up.

4 of 10 models settled on 4–5. The rest of the list shows where dissent still lives before kickoff.

  • 4–5
    4 models
  • 3–5
    3 models
  • 5–6
    1 model
  • 2–4
    1 model
  • 4–3
    1 model

Match overview

Looking for a today prediction on Los Angeles Angels vs Seattle Mariners in MLB? 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 (4 - 5; 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 Seattle Mariners win, with vote shares roughly 10% / 90% home and away (rounded).

If you are asking who will win Los Angeles Angels vs Seattle Mariners, 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 Seattle Mariners

90% 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
Expected runs tilt 3.60 vs 4.80

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.