2026 Home Run Derby: A Statcast Approach to Finding Betting Value
2026 Home Run Derby: A Statcast Approach to Finding Betting Value
Every July I have a little baseball project I look forward to.
The Home Run Derby is one of the most unique events on the baseball calendar, and every year I find myself asking the same question:
If the Derby isn't played like a normal baseball game, why would I handicap it like one?
This year's version actually came together much faster than usual.
Not because there was less work—but because of the work that's already been done.
Over the past six years I've spent countless hours building baseball models, testing ideas, throwing away the ones that didn't work, and slowly developing a research process that asks better baseball questions. This year, with that framework already in place—and with ChatGPT helping me organize and test the research—I was able to spend less time wrestling with spreadsheets and more time doing the part I enjoy most: thinking about baseball.
To me, that's a pretty good trade.
This Derby project isn't meant to be a comprehensive projection model. It's simply a fun annual research project to see if a few carefully chosen Statcast metrics can uncover value in one of baseball's most entertaining events.
Since I started building this three-player Derby portfolio in 2019, it has included the eventual Home Run Derby champion in five of the last six years. That's certainly not enough to prove anything on its own, but it's been encouraging enough that I look forward to building it every July.
Looking Beyond Home Run Totals
The Home Run Derby strips baseball down to one objective: hit the baseball over the fence.
There are no two-strike counts.
No defensive positioning.
No pitching strategy.
Because of that, I don't believe regular-season home run totals tell the entire story.
For this year's project, I analyzed three years of Statcast data against offspeed pitches.
Why offspeed?
While nothing perfectly recreates Derby conditions, offspeed pitches better resemble the slower, repeatable pitches hitters see during batting practice than a steady diet of upper-90s fastballs.
From there I focused on two simple metrics:
HR per Ball in Play (HR/BIP) — How often a ball put in play becomes a home run.
Average Launch Speed — A measure of how consistently a hitter produces elite contact.
Rather than trying to identify one perfect winner, I rank the field using those metrics and build a three-player Dutch betting portfolio around the best combination of probability and value.
📊 Basewinner Derby Ratings
Three-Year Statcast Profile vs. Offspeed Pitches (2024–2026)
The table below summarizes each participant's performance against offspeed pitches over the past three MLB seasons. While no metric perfectly predicts the Home Run Derby, I believe these measurements provide a better picture of Derby-style power than simply looking at season home run totals.
| Rank | Player | HR/BIP | Avg. Launch Speed | Basewinner Rating |
|---|---|---|---|---|
| 1 | Kyle Schwarber | 13.0% | 91.8 mph | ⭐⭐⭐⭐⭐ |
| 2 | Willson Contreras | 8.4% | 92.3 mph | ⭐⭐⭐⭐ |
| 3 | Jordan Walker | 6.1% | 92.8 mph | ⭐⭐⭐⭐ |
| 4 | Jac Caglianone | 5.7% | 89.7 mph | ⭐⭐⭐ |
| 5 | Bryce Harper | 5.0% | 89.8 mph | ⭐⭐⭐ |
| 6 | Ben Rice | 5.5% | 88.6 mph | ⭐⭐ |
| 7 | Junior Caminero | 3.8% | 88.8 mph | ⭐⭐ |
| 8 | Munetaka Murakami* | 17.6% | 89.3 mph | ⚠️ Small Sample |
Murakami's HR/BIP is based on just 17 balls in play, making the sample too small for me to include him in this year's portfolio.
🔬 Methodology
This year's mini-model uses:
Sample: Last three MLB seasons (2024–2026)
Pitch Type: Offspeed pitches only
Primary Metrics: HR per Ball in Play (HR/BIP) and Average Launch Speed
Betting Strategy: Three-player Dutch portfolio
Track Record: Since 2019, the portfolio has included the Derby champion in five of the last six years
⭐ Star Plays
Kyle Schwarber (+325)
Schwarber grades as the strongest overall profile in this year's field.
He leads the group in HR/BIP, has outstanding contact quality, owns Derby experience, and gets the added benefit of hitting in front of the Philadelphia crowd.
Jordan Walker (+650)
Walker owns the highest average launch speed in the field.
His combination of raw power and attractive odds makes him one of my favorite values on the board.
💣 Bomb Play
Willson Contreras (+1400)
Every year I look for one player whose underlying metrics appear stronger than his betting odds.
This year, that's Willson Contreras.
His HR/BIP ranks second in the field, his launch speed is among the best, and I think +1400 offers excellent value relative to his Statcast profile.
💰 $100 Dutch Portfolio
Rather than betting one player outright, I prefer to spread my investment across the three highest-rated values.
| Player | Odds | Stake |
|---|---|---|
| ⭐ Kyle Schwarber | +325 | $54.00 |
| ⭐ Jordan Walker | +650 | $30.60 |
| 💣 Willson Contreras | +1400 | $15.40 |
Portfolio Summary
Total Risk: $100
Approximate Return (if any selection wins): $230
Approximate Net Profit: +$130
The objective isn't to identify one perfect pick.
It's to consistently put ourselves in good betting positions and let the odds work for us over time.
Final Thoughts
One of the things I enjoy most about baseball is that there's always another question worth asking.
Some ideas turn into useful models.
Others end up in the recycling bin.
That's all part of the process.
This little Derby project is one of my favorite traditions each season because it reminds me how much I enjoy digging into the numbers and seeing where they lead. Every year I learn something new, and every year I try to make the process just a little better than it was the year before.
Hopefully this year's portfolio adds another winner to the list. If not, I'll be back tomorrow morning with another cup of coffee, another baseball question, and another model to build.
Thanks for reading, and I hope you enjoyed following along with this year's project as much as I enjoyed putting it together.
⚾ Basewinner Notes
☕ Coffee Consumed: Just enough.
🐶 Doghouse Rating: ⭐☆☆☆☆
Reason: Six years of refining the process—and a little help from ChatGPT—meant this year's project came together quickly enough that I even had time to hang out with my wife.