UTA 1-1 SEP · 51% WID 1-0 WIE · 54% SPV 1-0 1.F · 52% VFL 2-0 SVD · 58% KAS 1-1 KON · 50% LYN 1-2 SIL · 52% SAR 2-1 KFU · 55% RAP 2-0 WSG · 60% ANN 1-0 DIJ · 51% GRE 1-1 CLE · 52% LAV 1-0 SOC · 52% PAU 1-1 DUN · 51% REI 1-0 MON · 54% ROD 1-0 NAN · 51% UTA 1-1 SEP · 51% WID 1-0 WIE · 54% SPV 1-0 1.F · 52% VFL 2-0 SVD · 58% KAS 1-1 KON · 50% LYN 1-2 SIL · 52% SAR 2-1 KFU · 55% RAP 2-0 WSG · 60% ANN 1-0 DIJ · 51% GRE 1-1 CLE · 52% LAV 1-0 SOC · 52% PAU 1-1 DUN · 51% REI 1-0 MON · 54% ROD 1-0 NAN · 51%
Major League Soccer · Regular Season - 26 Sep 14, 2026 · 01:00 · UTC Snapdragon Stadium, San Diego Match Finished · 90'

San Diego
vs
Philadelphia Union.

Quick answer

Who will win San Diego vs Philadelphia Union?

Final score: San Diego 0–5 Philadelphia Union. Before kickoff, 8 of 10 AI models pick San Diego to win (80%); the consensus was wrong.

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

Head-to-head history → San Diego form Philadelphia Union form

10 AI models read this match. The plurality on 1X2 leans toward San Diego (8 of 10 models). The mean predicted score (rounded from all models) is 2–1 at 53% mean confidence (Low 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 San Diego beat Philadelphia Union 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.

San Diego win 80%

8 / 10 models

Draw 20%

2 / 10 models

Philadelphia Union win 0%

0 / 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
San Diego win
2–1
51%
San Diego’s Snapdragon Stadium home advantage should offset Philadelphia Union’s established MLS quality. With no usable form or head-to-head data, a competitive, moderately open match and narrow home win is the most balanced estimate.
02
Claude Sonnet 5
San Diego win
2–1
52%
San Diego as an expansion side has leaned on strong home form at Snapdragon Stadium; Philadelphia's away form is inconsistent late in season, favoring a narrow home win.
03
Gemini 3.8 Flash
Draw
1–1
50%
Expansion side San Diego enjoys home advantage at Snapdragon Stadium, but Philadelphia Union's structured counter-pressing makes them resilient on the road, pointing toward a balanced stalemate.
04
Grok 4.6
San Diego win
1–0
48%
No H2H or 2026 form. Snapdragon plus Union’s long east-to-west trip favors a tight San Diego win more than a multi-goal game.
05
DeepSeek V4 Pro
San Diego win
1–0
55%
San Diego's home edge at Snapdragon Stadium and likely tighter defensive shape against a Philadelphia side with modest away scoring.
06
Qwen 3.8 Max
San Diego win
1–0
52%
San Diego's home advantage at Snapdragon Stadium gives them a slight edge; context is thin so a narrow, low-scoring home win is the most grounded pick.
07
Mistral Medium 3.5
Draw
1–1
55%
Balanced matchup; home edge offset by Philadelphia's road consistency. Common MLS scoreline fits.
08
Kimi K3
San Diego win
2–1
55%
San Diego's strong home record at Snapdragon and attacking style give them the edge; Philadelphia's organized press should still produce a goal, but no H2H data keeps confidence moderate.
09
GLM 5.3
San Diego win
2–1
55%
San Diego have been strong at Snapdragon Stadium with an attacking style, while Philadelphia remain dangerous on the road; home edge but no H2H data, so moderate confidence.
10
MiMo V2.5 Pro
San Diego win
1–0
55%
Home venue at Snapdragon Stadium in MLS regular season; limited data, but home advantage often edges low-scoring games.
— Scoreline frequency

How often each scoreline showed up.

4 of 10 models settled on 2–1. The rest of the list shows where dissent still lives before kickoff.

  • 2–1
    4 models
  • 1–0
    4 models
  • 1–1
    2 models

Match overview

Looking for a today prediction on San Diego vs Philadelphia Union in Major League Soccer? 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 - 1; 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 San Diego win, with vote shares roughly 80% / 20% / 0% home, draw, and away (rounded).

If you are asking who will win San Diego vs Philadelphia Union, 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 San Diego

80% of models lean home — the clearest cluster on this fixture before kickoff.

02
Low confidence

Mean 53% across the panel with real dispersion — compare unanimous calls vs split tickets in the model table.

03
xG tilt 1.40 vs 0.60

Derived from predicted scorelines (model means), not live match 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
Result check

Actual Philadelphia Union win · AI San Diego win

1X2: Miss Score: Off
— Match context

Form, history, team news.

San Diego
Last 5
L
0 GF · 5 GA
Recent fixtures
  • Philadelphia Union 0-5 L
Team news

No major injury updates in the current API snapshot.

Philadelphia Union
Last 5
W
5 GF · 0 GA
Recent fixtures
  • San Diego 0-5 W
Team news

No major injury updates in the current API snapshot.

— Head to head

Last five meetings.

SAN 0 · D 0 · PHI 1

SAN VS PHI
0-5
AWAY WIN
Sep 14, 2026

Betting tips (AI-signal view)

Educational only — not financial advice. We summarize how the AI picks cluster so you can cross-check with your own staking plan.

  • Lean with the plurality: when 80% of models side with San Diego, treat that as the default script unless late team news breaks the assumptions.
  • Watch the draw lane at 20% — tight Major League Soccer games often compress toward stalemates when both midfields win the second-ball.
  • If you chase “best bets today” narratives, require alignment between the headline pick and the score-frequency table; conflicting signals usually mean thinner edge.

Odds & analysis (implied probabilities)

Implied fair percentages from the model vote share (normalized to 100%) approximate how a balanced market might price the 1X2 if it mirrored this panel — useful for odds analysis homework even though we do not quote sportsbook ticks here.

San Diego
~80%
implied lean
Draw
~20%
implied lean
Philadelphia Union
~0%
implied lean

Over / under prediction (totals)

Model-derived xG sums to 2.00 goals in expectation. A notional totals line near 2.3 is consistent with that pace (rounded for readability). If your sportsbook posts a similar number, compare juice and live team news before deciding either side of the total.

Handicap prediction (spread-style read)

When San Diego is priced as the stronger side in the model vote, a −1 handicap narrative only clears if the most common scorelines include multi-goal wins. Cross-check the score-frequency list: if tight one-goal wins dominate, Asian handicaps near pick’em or −0.5 / −0.75 splits often fit the story better than a full −1.5 sell.

BTTS prediction (both teams to score)

With combined offensive weight near 2.00 xG, a heuristic “both teams score” prior lands around 55% yes before defensive adjustments. If several top models forecast clean-sheet pathways, downgrade BTTS enthusiasm even when the raw xG sum looks juicy.

Best bet framing (consensus-led)

Our headline best bet label follows the consensus recommendation: San Diego win. Pair that with the confidence band (Low) — high dispersion across models usually argues for smaller stake or pass, even when the headline pick looks tempting for a today prediction card on social.

Explore more

Keep browsing today prediction coverage and league hubs.

— 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.