FCC 1-2 PHI · 50% COL 2-1 DCU · 54% NEW 1-0 CFM · 47% AL- 3-0 AL- · 65% COR 1-1 VIT · 42% SPO 1-2 FCD · 60% ST. 2-1 SAN · 49% ACM 1-1 INT · 42% EST 0-1 LEM · 44% AND 1-2 KVC · 43% SKB 0-2 UNI · 62% BAR 3-0 ALA · 64% AST 1-0 FUL · 46% DEP 0-0 TAL · 37% FCC 1-2 PHI · 50% COL 2-1 DCU · 54% NEW 1-0 CFM · 47% AL- 3-0 AL- · 65% COR 1-1 VIT · 42% SPO 1-2 FCD · 60% ST. 2-1 SAN · 49% ACM 1-1 INT · 42% EST 0-1 LEM · 44% AND 1-2 KVC · 43% SKB 0-2 UNI · 62% BAR 3-0 ALA · 64% AST 1-0 FUL · 46% DEP 0-0 TAL · 37%
Major League Soccer · Regular Season - 33 Snapdragon Stadium, San Diego Not Started

San Diego
vs
Sporting Kansas City.

Quick answer

Who will win San Diego vs Sporting Kansas City?

10 of 10 AI models pick San Diego to win (100%). The mean predicted score is 2–0 at 57% average confidence (medium).

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

Head-to-head history → San Diego form Sporting Kansas City form

All 10 AIs agree. When the whole council agrees, it has been right 62% of the time (800 matches).

10 AI models read this match. The plurality on 1X2 leans toward San Diego (10 of 10 models). The mean predicted score (rounded from all models) is 2–0 at 57% mean confidence (Medium band) — see the strip and table below.

Who do you think will win?

Vote before kick-off and compare with AI

Major League Soccer table Where San Diego and Sporting Kansas City stand right now
— Consensus

Where the panel lands.

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

San Diego win 100%

10 / 10 models

Draw 0%

0 / 10 models

Sporting Kansas City 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-6 Luna
San Diego win
2–0
72%
San Diego's home advantage, stronger record and two recent wins over Kansas City contrast with SKC's 21 losses, 77 conceded goals and poor form. A controlled home victory with a clean sheet is the best fit.
02
Claude Sonnet 5.5
San Diego win
2–0
61%
San Diego hold home venue edge and clean sheet history against SKC, who sit near bottom with 21 losses and weak defense conceding 77 goals.
03
Gemini 3.8 Flash
San Diego win
2–0
62%
Sporting KC have conceded 77 goals with just one clean sheet all season. San Diego's strong attack led by Dreyer should control the game against a struggling defense.
04
Grok 4.7
San Diego win
2–0
48%
SKC’s 21-loss season and 77 goals conceded contrast San Diego at Snapdragon; SKC often blanks while San Diego’s recent draws still support a modest home win.
05
DeepSeek V4 Pro
San Diego win
2–0
48%
San Diego unbeaten in five but drawing heavily; Sporting KC leak 2.3 goals per away game and have lost five straight. H2H shows San Diego winning twice without conceding.
06
Qwen 3.8 Max
San Diego win
1–0
45%
SKC's dire form (LDLLL, 77 conceded) and 10 blanks support a San Diego clean sheet, but San Diego's draw-heavy run (DLDDD) caps expected margin.
07
Meta Muse Spark 1.3
San Diego win
2–0
56%
San Diego dominate H2H with three clean sheets and face league-worst defence conceding 80. Dreyer-led attack at Snapdragon should break through.
08
Kimi K3
San Diego win
2–0
58%
Sporting KC's league-worst defense (77 conceded) and one clean sheet meet San Diego's strong home form and Dreyer's 25 goal contributions; H2H shows two recent away wins for San Diego.
09
GLM 5.3
San Diego win
2–0
58%
San Diego unbeaten-ish at home with strong H2H (two wins over SKC), while SKC's 6W-21L record and weak attack (10 scoreless games) support a controlled home win.
10
MiMo V2.6 Pro
San Diego win
2–0
58%
Sporting KC's 21 losses and 77 goals conceded make them vulnerable at Snapdragon; San Diego's Dreyer-led attack and H2H edge (two wins, no goals conceded) point to a controlled home win, though San Diego's draw-heavy form caps confidence.
— Scoreline frequency

How often each scoreline showed up.

9 of 10 models settled on 2–0. That convergence is a strong scoreline signal—many fixtures fan out wider across the panel.

  • 2–0
    9 models
  • 1–0
    1 model
Team news

Predicted lineups: San Diego vs Sporting Kansas City

Each side's last starting XI, with players ruled out of this match marked. The confirmed lineups replace this about an hour before kickoff.

San Diego

4-3-3 · XI v Vancouver Whitecaps, 29 Oct
Mikey Varas
90 A. Pellegrino
90 Pellegrino
94 C. Bakambu
94 Bakambu
10 A. Dreyer
10 Dreyer
12 Gabriel Pirani
12 Pirani
20 A. Godoy
20 Godoy
6 J. Tverskov
6 Tverskov
Left
5 Kieran Sargeant
5 Sargeant
26 M. Duah
26 Duah
97 C. McVey
97 McVey
33 O. Verhoeven
33 Verhoeven
13 P. Sisniega
13 Sisniega

1 of this XI is ruled out of this match or no longer at the club.

Sporting Kansas City

4-4-2 · XI v Minnesota United FC, 29 Oct
R. Wicky
17 S. Afrifa
17 Afrifa
19 T. Calheira
19 Calheira
7 Capita
7 Capita
20 K. Agyabeng
20 Agyabeng
16 J. Bartlett
16 Bartlett
11 André Luiz
11 Luiz
18 E. Karić
18 Karić
28 Wyatt Meyer
28 Meyer
15 Jansen Miller
15 Miller
8 J. Davis
8 Davis
30 S. Cleveland
30 Cleveland

Season data

Major League Soccer numbers for both sides, when they score and the players who carry them.

San Diego

4-3-3
W-D-L
8-11-13
Goals
56-62
Clean sheets
7
Failed to score
5
Best win run
3
Penalties
10/12
When they score
15'30'45'60'75'90'
When they concede
15'30'45'60'75'90'

Sporting Kansas City

4-4-2
W-D-L
6-4-22
Goals
38-80
Clean sheets
1
Failed to score
10
Best win run
2
Penalties
0/1
When they score
15'30'45'60'75'90'
When they concede
15'30'45'60'75'90'

Key players · San Diego

  • A. Dreyer 13 G · 12 A · 31 apps

Key players · Sporting Kansas City

  • No player in the competition's top scorers or assisters.

Top scorers · Major League Soccer

  1. 1 L. Messi Inter Miami 25
  2. 2 P. Musa FC Dallas 22
  3. 3 Rafael Navarro St. Louis City 19
  4. 4 M. Iloski Philadelphia Union 19
  5. 5 D. Bouanga Los Angeles FC 18
Venue Snapdragon Stadium, San Diego
New at San Diego D. Nyangono (FC Nordsjaelland), S. Vines (Houston Dynamo), C. Bakambu (Real Betis)
New at Sporting Kansas City R. Ramos (Los Angeles Galaxy), S. Reid (New York City FC), O. Wolff (Austin)
— Aggregated insights

What’s moving the panel.

01
Consensus favors San Diego

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

02
Medium confidence

Mean 57% across the panel with real dispersion — compare unanimous calls vs split tickets in the model table.

03
xG tilt 1.90 vs 0.00

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.

— Match context

Form, history, team news.

San Diego
#13 · 35 PTS · GD -6
Last 5
L D D D L
9 GF · 15 GA
Recent fixtures
  • Vancouver Whitecaps 4-1 L
  • Seattle Sounders 2-2 D
  • Los Angeles Galaxy 2-2 D
  • Houston Dynamo 3-3 D
  • New York Red Bulls 4-1 L
Team news
A. Alvarado Jr — Knee Injury E. Boateng — Lower-Body Injury W. Eisner — Lower-Body Injury W. Kumado — Lower-Body Injury A. Reyes — Lower-Body Injury P. Sisniega — Red Card L. Morgan — Thigh Injury D. Vazquez — Lower-Body Injury K. Sargeant — Lower-Body Injury C. McVey — Red Card A. Pellegrino — Lower-Body Injury I. Pilcher — Lower-Body Injury
Sporting Kansas City
#15 · 22 PTS · GD -42
Last 5
L L L L D
6 GF · 15 GA
Recent fixtures
  • Minnesota United FC 3-1 L
  • Austin 1-2 L
  • Real Salt Lake 1-3 L
  • Nashville SC 4-0 L
  • Portland Timbers 3-3 D
Team news
J. Kortkamp — Ankle Injury R. Schewe — Hand Injury S. Afrifa — Hamstring Injury Z. Bassong — Muscle Injury J. Reynolds — Injury I. James — Injury S. Cleveland — Ankle Injury W. Meyer — Knee Injury J. Reid — Ankle Injury Diego Borges — Groin Injury K. Agyabeng — Groin Injury J. Miller — Hamstring Injury

Confidence trend

Cumulative average confidence in table order.

First model Last model

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 100% of models side with San Diego, treat that as the default script unless late team news breaks the assumptions.
  • Watch the draw lane at 0% — 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
~100%
implied lean
Draw
~0%
implied lean
Sporting Kansas City
~0%
implied lean

Over / under prediction (totals)

Model-derived xG sums to 1.90 goals in expectation. A notional totals line near 2.2 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 1.90 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 (Medium) — 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.

Match overview

Looking for a today prediction on San Diego vs Sporting Kansas City 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 - 0; 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 100% / 0% / 0% home, draw, and away (rounded).

If you are asking who will win San Diego vs Sporting Kansas City, 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.

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.