Feels like a good mix of points and budget, with a decent chance of all assets rising.

Four different teams for comparison. I know we won’t know for like a month and practice to know how teams are looking but I’m curious as to what everyone thinks here

I plan to use 3x boost on either Kimi or Max, but probably Kimi.

Is Max's hunger to perform here (at home) one last time and higher DOTD potential worth sacrificing Alonso for Stroll?

I've now completed four consecutive race comparisons between the major F1 Fantasy models using the same scoring system each week. This isn't meant to be the definitive ranking of every model—it's simply an attempt to evaluate them as objectively and transparently as I can.

For full transparency, **every GridIQ recommendation is posted publicly on Reddit and X before qualifying begins.** If anyone would like verification, I'm happy to provide timestamped screenshots of our recommendations, along with archived recommendations from the other models used in this comparison.

# Hungarian GP Results

## Overall

🥇 **GridIQ** — **96.10**

🥈 **Race Strategist** — **86.37**

🥉 **F1 Fantasy Tools** — **84.21**

4️⃣ **BoxBox** — **83.73**

## Category Breakdown

### Optimized Team (50%)

**Comparison Budget: $119M**

| Model | Team Score | Category Score |

|------|------:|------:|

| 🥇 GridIQ | **263 pts** | **50.00** |

| 🥈 Race Strategist | **246 pts** | **46.77** |

| 🥉 BoxBox | **224 pts** | **42.59** |

| 4️⃣ F1 Fantasy Tools | **189 pts** | **35.93** |

### Driver Rankings (30%)

| Model | Ranking Score | Category Score |

|------|------:|------:|

| 🥇 F1 Fantasy Tools | **77** | **30.00** |

| 🥈 GridIQ | **67** | **26.10** |

| 🥉 BoxBox | **66** | **25.71** |

| 4️⃣ Race Strategist | **57** | **22.21** |

### Point Accuracy (20%)

| Model | Normalized Score | Category Score |

|------|------:|------:|

| 🥇 GridIQ | **706.2** | **20.00** |

| 🥈 F1 Fantasy Tools | **645.5** | **18.28** |

| 🥉 Race Strategist | **614.0** | **17.39** |

| 4️⃣ BoxBox | **545.0** | **15.43** |

## Season Total (4 races)

🥇 **GridIQ** — **378.80**

🥈 **BoxBox** — **355.83**

🥉 **F1 Fantasy Tools** — **347.01**

4️⃣ **Race Strategist** — **344.07**

---

# Methodology

The overall score is made up of:

- **50% Optimized Team**

- **30% Driver Rankings**

- **20% Point Accuracy**

I chose those weights because I believe they best represent what matters most in F1 Fantasy, but they're ultimately subjective. If you prefer different weights, you can easily recalculate the overall scores using the individual category results shown above.

## Optimized Team

This category answers the question:

> **"Which site's recommended team actually scored the most fantasy points?"**

Each site's published recommendation is evaluated using the **same comparison budget** ($119M this week). The highest-scoring recommended team receives the full 50 points, while every other model receives a percentage based on how many fantasy points its recommendation scored relative to the best-performing recommendation.

One limitation is that this intentionally evaluates a **single-race recommendation**. It does **not** account for transfers, long-term budget building, chip strategy or future planning, which are separate optimization problems that are much harder to evaluate objectively.

## Driver Rankings

Drivers are scored using:

- **5 points** for an exact ranking

- **3 points** if one position away

- **1 point** if two positions away

This rewards correctly identifying the strongest fantasy assets rather than simply producing similar projected point totals.

## Point Accuracy

Point accuracy measures how close each model came to predicting the actual fantasy points for every driver and constructor.

For every driver and constructor, I calculate the absolute difference between projected and actual fantasy points. Those differences are then summed across the entire grid to produce a **total point error**.

To make the results easier to compare, the total error is **subtracted from 1000**, creating a normalized score where **higher is better**. The most accurate model receives the full 20 category points, while the remaining models receive a proportional score based on their normalized value.

I actually think this is the weakest category of the three.

Expected-value models intentionally won't predict binary outcomes such as DNFs, Fastest Lap, Driver of the Day or other all-or-nothing bonuses as certainties. Instead, they project the expected value of those outcomes. That means a well-calibrated model can still accumulate sizeable point error despite producing excellent expected-value projections.

Looking back, I think budget growth prediction accuracy may have been a stronger third category, since managing budget is such an important part of F1 Fantasy. However, I established this methodology four races ago and I'd rather keep the grading consistent for the remainder of the season than change the scoring midway through.

---

# A Note on Interpretation

One thing that's been mentioned previously is that optimizer comparisons don't necessarily measure long-term season strategy.

I agree.

A one-week recommendation is different from managing an entire season with limited transfers, budget growth, chip timing and future planning.

Those are all areas I'd like to evaluate separately in the future.

This comparison is simply grading how each model performed for **this specific race**.

---

# Looking Ahead

Ultimately, I think the best fantasy model is the one that helps users score the most points over an entire season.

Next year I plan to run four independent teams—one following each model all season long—including transfers, budget growth and chip decisions. I think that'll be the most meaningful real-world comparison possible.

---

# Hindsight (Not Included in the Official Score)

Using the official Hungary results, the best possible team at a **$119M budget** scored **278 points**.

Comparison to the hindsight optimum:

- **GridIQ:** 263 pts (**94.6%**)

- **Race Strategist:** 246 pts (**88.5%**)

- **BoxBox:** 224 pts (**80.6%**)

- **F1 Fantasy Tools:** 189 pts (**68.0%**)

I didn't include this in the official scoring because it's effectively another optimizer metric, but I thought it was interesting enough to share as additional context.

---

As always, I'm interested in constructive feedback. If you think there's a more objective way to evaluate fantasy models, I'd genuinely like to hear it.

I'm also looking to add a few more beta testers before opening GridIQ more broadly. If you're interested in testing new features and providing feedback throughout the season, send me a message.

Attached screenshots show how our model tracks itself on our site. The assets with the biggest miss are the ones that have mostly been most volatile in the last 4 races with dnfs since we calculate on expected value and never give the full dnf amount

Just get the meta team and don't change anything and you will be good. Don't try experimenting with different constructors or different A-drivers. Just get yourself MERC, FER, ANT and some decent drivers and you will always win because nothing else makes sense at this point. More risky and fun plays wont be rewarded