MLB Home Run Props Today: Best HR Picks & Odds

Here are the best MLB Home Run props for Saturday, October 17, 2026.

Looking to hit a home run with your MLB betting (I know, cheezy🤪)? Daily home run prop bets are one of the most exciting ways to get in on the action, offering bettors and DFS players a chance to wager on which sluggers will go yard in any given game. Whether you’re a seasoned sports bettor or a crazed DFS player dipping your toes into the world of player props, our daily MLB home run props have you covered.

From top power hitters to under-the-radar sleepers, we’ll break down the best bets, key stats, and expert insights to help you make informed HR picks every day of the season. Bookmark this page and swing by for the latest updates as we track the dingers all season long!

Home Run Props Today

You are looking at live home run props data for games on October 17, 2026. Our algorithm takes into account career stats vs. SPs, weather, ballpark factors, and recent advanced-stats performance.

Recent Home Run Prop Hit Rates For Today

• Patrick Bailey has hit the Home Runs Over in 2 of his last 6 games (+13.00 Units / 217% ROI)

MLB Park Factors: How Ballparks Impact HR Props

Not all home runs are created equal, and neither are all ballparks. Park factors measure how a specific stadium influences offensive production compared to a neutral league-average environment, indexed to 100.

An HR factor of 202 at Coors Field means hitters are roughly twice as likely to go yard there as at an average park. A factor of 52 at T-Mobile Park means the opposite.

For home run prop bettors, the HR column is the number that matters most. It isolates power specifically, independent of hits, walks, or general offense, making it the cleanest single variable for evaluating whether a hitter’s odds are properly priced for tonight’s venue. A slugger at +350 in a 120+ HR park is a fundamentally different bet than the same player at +350 in a pitcher’s paradise like Petco or Oracle.

The 3.5-year average (2023–2026) smooths out single-season variance and wind flukes. Use it as a baseline, then layer in today’s weather, wind direction, and temperature, which are the short-term park factor adjusters that the three-year number can’t capture.

Also tracking: Today’s NRFI picks

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How To Bet Home Run Props

As a bettor focusing on MLB home run prop bets, my approach is systematic, data-driven, and disciplined.

Here’s how I tackle it during the MLB season:

1. Understand the Market

Home run prop bets typically come in two forms: “Will Player X hit a home run?” (Yes/No) or “Over/Under X home runs” for a game or series. Odds are set based on player performance, matchups, and external factors.

My goal is to identify inefficiencies in the lines where the implied probability doesn’t match the actual likelihood.

2. Data Analysis

I rely heavily on statistical models and historical data:

• Player Stats: Look at a batter’s home run rate (HR/AB), ISO (isolated power), fly ball percentage, and recent form. Guys with high fly ball rates and power metrics (Aaron Judge, Pete Alonso) are prime candidates.
• Pitcher Matchups: Analyze the opposing pitcher’s tendencies, HR/9 (home runs per nine innings), fly ball rate allowed, and pitch types. A pitcher who gives up a lot of fly balls or struggles with hard contact is a green flag.
• Ballpark Factors: Adjust for park dimensions and weather. Coors Field or Great American Ball Park boost home run odds, while Oracle Park suppresses them. Check wind direction and temperature; warm, windy days favor hitters.
• Splits: Dig into batter vs. pitcher history (small sample, but useful) and platoon splits (lefty batter vs. righty pitcher). Some hitters crush specific pitch types.

3. Situational Factors

• Lineup Position: Batters higher in the order (1-5) get more plate appearances, increasing their chances. A cleanup hitter (4th) often sees better pitches to drive.
• Game Context: In a high-scoring game script (e.g., weak starting pitchers on both sides), home runs are more likely. Check MLB public betting data and odds movement for clues.
• Fatigue: Late in the season, pitchers might be gassed, or batters might be slumping. Monitor rest days and travel schedules.

4. Finding Value

Sportsbooks aren’t perfect. They overreact to public perception or recent hot streaks.

• Compare implied odds (e.g., +300 implies a 25% chance) to my calculated probability. If I think a player has a 35% chance, but the line suggests 25%, that’s an edge. Our Kalshi edge tool for recognizing +EV HR odds is perfect for this strategy.
• Fade overhyped players, like a streaky hitter with inflated odds, and target undervalued ones, like a consistent power hitter in a good matchup with longer odds.

5. Bankroll Management

• Bet sizing is key. I use a unit system (e.g., 1 unit = 1% of my bankroll) and never chase losses. For home run props, which are high-variance, I keep bets small and consistent, say, 0.5-1 unit per play.
• Spread action across multiple games to diversify risk. Home runs are unpredictable, so volume helps smooth variance.

6. My Daily Process

• Morning: Review starting pitchers, lineups, and weather reports. Cross-reference with my data model.
• Mid-day: Check opening lines and track movement. Early bets often have softer odds.
• Game Time: Monitor live betting if available; sometimes, a pitcher tipping pitches or an injury shifts the odds.

Example:

Say Shohei Ohtani is facing a pitcher with a 1.5 HR/9, a 45% fly ball rate allowed, in a hitter-friendly park with wind blowing out. Ohtani’s HR rate is 1 per 15 AB this season, and he’s +350 to hit a home run. My model estimates a 30% chance (1 HR per 20 AB adjusted for matchup/park), while +350 implies 22%. That’s a value bet, I’d take it.

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Jason Ziernicki

Founder at CLEATZ | jason@cleatz.com | Web | + postsBio ⮌

Jason Ziernicki is the founder of CLEATZ and has worked in the online sports betting industry since 2012. At CLEATZ, he focuses on public betting data, sportsbook line movement, prediction markets and data-driven sports betting tools.

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