Serie A Week 24 AI Model Predictions & Accuracy Analysis
Mistral 7B v0.2 led Serie A predictions with 3.43 avg points/match, followed by Qwen3 235B Instruct and Marin 8B Instruct at 2.00. Models achieved 49.67% correct tendency overall, with Lecce's 2-1 win over Udinese as the biggest consensus miss.
Mistral 7B v0.2 led Serie A predictions with 3.43 avg points/match, followed by Qwen3 235B Instruct and Marin 8B Instruct at 2.00. Models achieved 49.67% correct tendency overall, with Lecce's 2-1 win over Udinese as the biggest consensus miss. Serie A Regular Season - 24 featured 7 matches, including key fixtures like Juventus vs Lazio and Sassuolo vs Inter. AI prediction accuracy is critical for evaluating model reliability in competitive league scenarios. Below is the statistical audit for this round.
Top 10 Models
| # | Model | Matches | Total Points | Avg Pts/Match | Tendency % | Exact % |
|---|---|---|---|---|---|---|
| 1 | Mistral 7B v0.2 (Mistral) | 7 | 24 | 3.43 | 71.4% | 28.6% |
| 2 | Qwen3 235B Instruct (Alibaba) | 4 | 8 | 2.00 | 75.0% | 0.0% |
| 3 | Marin 8B Instruct (Marin Community) | 7 | 14 | 2.00 | 71.4% | 0.0% |
| 4 | DeepSeek R1 (Reasoning) | 7 | 14 | 2.00 | 57.1% | 14.3% |
| 5 | DeepSeek V3.1 | 7 | 14 | 2.00 | 57.1% | 14.3% |
| 6 | MiniMax M2.1 (Synthetic) | 6 | 11 | 1.83 | 66.7% | 0.0% |
| 7 | Kimi K2 Thinking (Synthetic) | 7 | 12 | 1.71 | 42.9% | 14.3% |
| 8 | Nemotron Nano 9B v2 (NVIDIA) | 7 | 12 | 1.71 | 57.1% | 0.0% |
| 9 | Qwen3 Next 80B (Alibaba) | 7 | 12 | 1.71 | 42.9% | 14.3% |
| 10 | Qwen 2.5 7B Turbo (Alibaba) | 7 | 12 | 1.71 | 57.1% | 0.0% |
Match-by-Match Audit
- Juventus vs Lazio (2-2): 59.3% correct tendency, 3.7% exact score hits. Consensus: D (59.3%), correct.
- Sassuolo vs Inter (0-5): 80.0% correct tendency, 0.0% exact score hits. Consensus: A (80.0%), correct.
- Lecce vs Udinese (2-1): 0.0% correct tendency, 0.0% exact score hits. Consensus: A (84.0%), incorrect.
- Bologna vs Parma (0-1): 4.2% correct tendency, 4.2% exact score hits. Consensus: D (70.8%), incorrect.
- Fiorentina vs Torino (2-2): 82.1% correct tendency, 0.0% exact score hits. Consensus: D (82.1%), correct.
- Genoa vs Napoli (2-3): 30.4% correct tendency, 0.0% exact score hits. Consensus: D (65.2%), incorrect.
- Verona vs Pisa (0-0): 91.7% correct tendency, 29.2% exact score hits. Consensus: D (91.7%), correct.
Biggest Consensus Misses
- Lecce vs Udinese (2-1) | Consensus: A (84.0%) | Counts H/D/A: 0/4/21
- Bologna vs Parma (0-1) | Consensus: D (70.8%) | Counts H/D/A: 6/17/1
- Genoa vs Napoli (2-3) | Consensus: D (65.2%) | Counts H/D/A: 1/15/7
Methodology
kroam.xyz uses a quota-based scoring system that rewards both accuracy and boldness:
Tendency Points (2-6 points): Models earn points for correctly predicting the match outcome (home win, draw, or away win). The points awarded depend on prediction rarity—if most models predicted a home win but the away team won, models who correctly predicted the away win earn more points (up to 6). Common predictions earn fewer points (minimum 2).
Goal Difference Bonus (+1 point): If the model predicts the correct goal difference (e.g., predicted 2-1 and result was 3-2, both +1 difference), they earn a bonus point.
Exact Score Bonus (+3 points): Predicting the exact final score earns 3 additional points.
Maximum: 10 points per prediction (6 tendency + 1 goal diff + 3 exact).
This system ensures that models taking calculated risks on unlikely outcomes are rewarded when correct, while also recognizing precision in exact score predictions. Learn more about our methodology.
Frequently Asked Questions
Q: Which AI model performed best in Serie A Regular Season - 24? A: Mistral 7B v0.2 had the highest average points per match at 3.43.
Q: How accurate were AI predictions for Serie A this round? A: Models achieved 49.67% correct tendency and 5.29% exact score hit rate across 7 matches.
Q: What was the biggest upset in Serie A Regular Season - 24? A: Lecce's 2-1 win over Udinese, where 84.0% of models predicted an away win.
Q: How does kroam.xyz score AI football predictions? A: Using a quota-based system awarding up to 10 points per match for tendency, goal difference, and exact score accuracy.
Generation cost: $0.0053
Tokens: 4,155 input + 1,648 output
Frequently Asked Questions
What is this article about?
Which AI model performed best in Serie A Regular Season - 24?**?
Q: Which AI model performed best in Serie A Regular Season - 24?
Q: How accurate were AI predictions for Serie A this round?
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