MLB Home Run Props: What Actually Predicts Home Runs
We measured 162,494 MLB starts from 2023 to 2026. Here is what actually predicts who will hit a home run tonight — and why the hitter's own power matters far more than his last week, the pitcher, or the wind.
Published April 2026 · Updated September 2026 · 12 min read
1. The Home Run Betting Market
Home run props are the most exciting bet in baseball. A single HR can flip a game, and the moment the ball clears the fence is immediate, unambiguous, and completely detached from the final score. You do not need your team to win. You do not need a bullpen to hold a lead. You just need a batter to make one perfect swing.
That simplicity has made HR parlays enormously popular — and occasionally enormous. A $30 parlay linking several home run props in a single slate recently paid $1.83 million. Payouts like that are real, but they are lottery outcomes: at +300 each, a four-leg parlay pays about 255-to-1, and four legs that each hit one night in five all land together about once in 625 tries.
But HRs are rare. In 2026 the best rate among regular starters was Munetaka Murakami's 26.4% of games; Aaron Judge, Pete Alonso and Kyle Schwarber sat near 25%. A typical starter homers in about 12% of games — roughly 88 of every 100 starts produce no home run at all. The overwhelming base rate is zero.
This is why naive approaches to HR props fail. You cannot simply list the most powerful hitters in baseball and bet them every night. Picking Aaron Judge every game at +300 is not a winning strategy: he goes homerless about three games in four, so at +300 you are paying roughly the fair price for his talent and nothing more.
The correct framing is not: "Will this batter hit a home run tonight?" It is: "Which batter tonight has the highest probability of hitting a home run — and is that probability being underpriced by the sportsbook?" That is a ranking problem. And ranking problems are exactly what machine learning models are built to solve.
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2. Why Most HR Predictions Fail
The failure mode in most public HR prediction approaches is not a lack of effort — it is a structural mismatch between the model type and the problem.
The base rate problem is severe. When 89% of outcomes are zero, any binary classifier trained to predict "will this batter homer?" will learn very quickly that predicting "no" every time achieves 89% accuracy. The model learns the base rate, not the signal. This is why simple binary classifiers trained on batter-game data produce outputs that look accurate in aggregate but are useless for betting: they predict "no HR" for almost every batter, which is often technically correct and always practically worthless.
Season-level statistics are the right starting point, not the problem. A hitter's home run rate and contact quality carry most of what can be known about tonight — far more than his last week. What a season line leaves out is tonight's park, weather and pitcher, and whether his power has genuinely changed this year, which takes longer to see than most bettors assume.
What Shifts the Probability Game-to-Game
These are the game-by-game factors, measured against what the hitter's season already says:
Most public HR prediction sites rank batters by season HR total or average HR rate. Those rankings are not wrong — the hitter's power is the biggest signal there is. What they leave out is tonight's park, weather and pitcher, which is the part a daily model can add.
3. The Hot Hitter Effect — Smaller Than It Looks
An earlier version of this article said batters hitting .300 over their last five games homer at twice the rate of cold hitters. That comparison is real but misleading: hot hitters are mostly good hitters, so they beat cold hitters whether or not the streak means anything. The fair test compares a hot hitter with hitters of the same season-to-date power, using only games before the one being predicted.
So a streak is worth about a point, and a slump in an established slugger is worth nothing. The batting-average version of “hot” is the weakest of all, because it can miss low-average sluggers entirely. The full breakdown, including batter-vs-pitcher history, is in do hot streaks predict home runs?
4. Statcast Features That Drive HR Probability
Alongside the hitter's own home run rate, contact quality from Baseball Savant sits at the top of what our model leans on. Expected isolated power (xISO) synthesizes barrel rate, exit velocity, and launch angle into a single expected power output metric that predicts extra-base production better than any of its component inputs in isolation.
Here is the full Statcast profile that drives HR prediction:
Barrel Rate
Barrel rate is the percentage of a batter's batted balls that qualify as "barreled" — hit at the optimal combination of exit velocity (95+ mph) and launch angle (25-35 degrees) that maximizes the probability of extra-base hits. The league average barrel rate is approximately 7%. Elite power hitters sit at 15% or higher.
Barrel rate is the most direct measurable proxy for a batter's ability to generate home run contact. A batter with a 14% barrel rate is not twice as likely to homer as a batter with a 7% barrel rate — the relationship is nonlinear and depends on park and weather — but barrel rate is the single best Statcast input for HR prop assessment.
Exit Velocity
Exit velocity measures how hard the ball comes off the bat, in miles per hour. Batters averaging 95+ mph on contact are in the power tier. The relationship between exit velocity and HR probability is not linear — it jumps sharply above 100 mph, where even off-angle contact can clear the fence at hitter-friendly parks.
Average exit velocity is more stable than barrel rate as a long-term indicator, but recent exit velocity trends are a useful signal for detecting batters whose contact quality is improving or declining within the season.
Launch Angle
The optimal home run launch angle is 25-35 degrees. Fly ball hitters with a pull tendency generate more HR opportunities than ground-ball hitters, even at equivalent exit velocities, because ground balls and line drives below 15 degrees almost never result in home runs regardless of how hard they are hit.
Launch angle is where intentional swing changes show up first in the data. When a batter deliberately elevates his swing path to generate more fly balls, launch angle shifts before barrel rate and HR totals catch up — which matters because home run totals themselves take about 300 plate appearances to outweigh last season's (see when a home run breakout is real).
Pull Percentage
Pull percentage — the fraction of batted balls hit to the pull side — interacts directly with park factors in a way that matters for HR props. A pull-heavy right-handed hitter at Yankee Stadium, with its famously short 314-foot right porch, is a categorically different bet than the same batter at Oracle Park, where right-center field extends 399 feet.
Our model treats pull percentage as a modifier on top of barrel rate and exit velocity, because the same quality of contact produces different outcomes depending on the direction of the ball and the dimensions of the park. High pull percentage + short porch = elevated HR probability over and above what the Statcast metrics alone would suggest.
Our model ranks every starter by home run probability every day, rebuilt as lineups and weather post. The top three are graded in public every day.
5. The Pitcher Matchup
Not all pitchers allow home runs at equal rates, and the differences between them are large enough to materially shift a batter's HR probability on any given night. A power hitter facing a high-fastball pitcher is in a fundamentally different situation than the same batter facing a sinkerballer working the bottom of the zone.
Fastball Percentage and HR Vulnerability
Fastballs are the easiest pitch to drive for power. They travel on a predictable path, arrive earlier in the zone, and give batters more time to generate bat speed through impact. High fastball percentage pitchers — those who throw four-seamers and sinkers on 60%+ of pitches — allow more home runs per nine innings than pitchers who rely heavily on breaking balls and changeups.
The logic is straightforward: power hitters sit fastball. When a pitcher throws fastballs frequently, the power hitter is getting more looks at his best pitch. Hard-throwing fastball pitchers who challenge power hitters — rather than tunneling off-speed pitches below the zone — are the most exploitable matchups for HR props.
Rolling Pitcher HR Vulnerability
Our model uses barrel rate allowed and HR per nine innings from the opposing pitcher's recent starts — specifically his last seven outings — rather than his full season average. This is an important distinction.
A pitcher who has allowed five home runs across his last three starts is more exploitable today than his season average suggests. He may be tipping pitches, losing command of his secondary offerings, or struggling mechanically in a way that will take two to three weeks to show up in his season-level stats. Keep the size of it in proportion, though: sorted into fifths by home runs allowed, starters ranged only from 10.9% to 12.7% of opposing starts with a homer.
The same sort by the batter's own home run rate ran from 6.9% to 17.4%. A strong power hitter facing the league's stingiest starter is still a better bet than a weak hitter facing its most generous.
The Batter-Pitcher Interaction
Where the two meet, the effect is additive and modest. Among the top fifth of power hitters, home run rates ran from 16.1% against the stingiest starters to 18.7% against the most generous.
Batter-vs-pitcher history adds nothing measurable: hitters who had homered off tonight's starter before went deep 13.4% of the time, slightly below what their own season rates predicted. Use the matchup as a tiebreak between similar hitters, and ignore the head-to-head line.
6. Weather: A Suppressor First
Weather matters, but not in the direction most bettors lean on. We matched 133,420 open-air starts to their first-pitch weather and compared each with what the same ballpark gives up in the same month, so the calendar and the park are taken out. The full tables are in does weather affect home runs?
Wind
Wind blowing in at 10 mph or more cut home runs to 10.3% of starts, against 11.9% for the same ballparks — about 13% fewer. Wind blowing out at the same speed added only about half a point league-wide, partly because the parks where it blows out most already play as hitter-friendly.
Wrigley Field is the exception that built the folklore: starters homered in 16.7% of games with wind blowing out at 10+ mph and 8.3% with it blowing in. At most parks, check the wind for the downside.
Temperature
Warm air is less dense, and a well-struck ball carries a few feet farther for every 10 degrees. The raw numbers look dramatic — 8.9% of starts homered below 55°F against 13.3% at 85°F and up — but most of that is April versus July. Against the same park in the same month, cold games ran about 1.7 points low while hot games ran only about half a point high.
Humidity
Humidity has a counterintuitive effect that most bettors get backwards. Humid air is actually less dense than dry air, because water vapor (H2O, molecular weight 18) is lighter than the nitrogen (28) and oxygen (32) that make up the bulk of dry air. When water vapor displaces heavier gas molecules, overall air density drops slightly — and lower air density means less aerodynamic drag on a batted ball, which means more carry.
The effect is small — a few feet of carry difference between very dry and very humid conditions — but it is real and in the opposite direction from what most people assume. Humid summer games at outdoor parks are slightly more HR-friendly than dry games at equivalent temperature and wind conditions.
Domes and Weather Neutralization
Retractable-roof and fully enclosed domes neutralize weather effects. At parks like Tropicana Field, Rogers Centre, Chase Field (when closed), and Globe Life Field (when closed), HR probability comes down to the batter, the pitcher and the park dimensions. Starters in domed and closed-roof games homered at 11.7%, right on the league rate.
MLB publishes a game's first-pitch weather only about four hours before first pitch, so a weather angle belongs to the last few hours before the game, not the morning.
7. Park Factors for Home Runs
Not all parks are equal. The difference between the most HR-friendly park in baseball and the most suppressive is not marginal — it represents a 69% swing in HR probability for identical batted balls. Our model uses HR-specific park factors rather than general run-scoring factors, because a park can suppress overall run scoring while still being relatively HR-friendly (short porches with deep gaps) or vice versa.
Why Coors Field Is Unique
Coors Field sits at 5,280 feet above sea level. At altitude, air density is measurably lower, which reduces aerodynamic drag on every batted ball. A well-struck fly ball at Coors carries 15-25 feet farther than the same ball at sea level. Combined with Coors's expansive outfield dimensions, this produces the highest HR factor in baseball — 1.45x the league average — despite the park's large outfield surface.
Yankee Stadium's Right Field Porch
Yankee Stadium's 314-foot right field line is the shortest in the American League East and among the shortest in baseball. Right-handed pitchers giving up pull-side fly balls to left-handed batters at Yankee Stadium face a structural disadvantage — balls that would be comfortable outs in most parks become home runs. The park factor of 1.15x reflects this, but the effect is even more pronounced for left-handed power hitters with high pull rates.
Oracle Park's Suppression Effect
Oracle Park (San Francisco) suppresses HRs to 0.86x the league average through a combination of cold temperatures, persistent wind blowing in from McCovey Cove off the Bay, and deep power alleys (399 feet to right-center). A batter who averages 35 HRs per season at a neutral park would project to approximately 30 at Oracle and 40 at Coors under identical conditions. For HR prop purposes, always cross-reference the park before placing a bet on a power hitter.
For a deeper look at how park factors affect both HR props and totals betting, see our MLB park factors and totals betting guide.
8. How Our Model Ranks Batters
Our HR model is gradient-boosted (XGBoost), retrained every day on every starter-game since 2023, and produces a home run probability for every batter on tonight's slate. Its inputs follow the sections above: the hitter's power and contact quality, recent form, the opposing starter and bullpen, park, platoon, lineup slot, and weather once MLB publishes it. The output is a ranked list, not a yes/no call, because HR prediction is a ranking problem.
Why We No Longer Quote a Backtest Here
An earlier version of this page quoted a backtest in which the top-ranked batters homered at more than twice the baseline rate. In 2026 we found that the raw box-score feed stores postponed and suspended games twice, under two dates — which let some games' own results leak into their “prior” history and flattered every backtest built on it. We removed the duplicates and retired those numbers.
Instead of a backtest, the record is public: our top three home run picks are published before first pitch every day and graded the next morning under a rule fixed in advance, on the performance page.
What the Model Does Not Do
The model does not predict certainty. Even the best power hitters in baseball homer in about one start in four, so the batter ranked #1 tonight will go homerless on most of the nights he holds that spot. That is the irreducible variance of a rare event, and it is why a ranking should be read as “likelier than the field,” never as a lock.
9. Practical: Using HR Rankings for Betting
Understanding what drives HR probability is useful. Translating it into a practical betting process requires one additional step: comparing the model's implied probability against the sportsbook's implied probability and identifying where the gap is large enough to bet.
Building Your Shortlist
The top 3-5 batters in the daily HR rankings are your shortlist. These are the batters for whom the model has identified the highest probability combination of factors tonight. Start here, not with a list of all power hitters in baseball.
Cross-reference with the weather page at /mlb-weather for tonight's outdoor parks. The conditions worth acting on are the ones that take home runs away — a cold night or wind blowing in at 10+ mph. Wind blowing out is a real boost mainly at Wrigley Field.
Single HR Props vs. Parlays
Single HR props — player to hit one or more home runs — are typically priced at +250 to +450 odds, implying a probability between 18% and 29%. At +300 (25% implied), you need a true probability above 25% to have a positive expected value at standard juice.
So the question for every name on the shortlist is the same: is the book's implied probability below the model's number for that batter tonight? The ranking alone is not a reason to bet. Two top-ranked batters can carry very different prices, and a well-ranked hitter at a short price can still be a bad bet. Our published record measures how often the top three homer — a hit rate, not a claim of profit.
Parlays
Parlaying two to three top-ranked batters is high-risk, high-reward — mostly risk. A three-leg parlay at +300 per leg pays about 63-to-1. If each leg truly homers one night in five, all three land about once in 125 tickets, so the payout is well short of the risk. Multi-leg HR parlays only pay off over time if every leg is genuinely underpriced, and even then most tickets lose.
Where the Edge Actually Lives
If there is an edge in HR props, it is not in betting every top-ranked batter. It is in the gap between a batter's probability tonight — power, park, pitcher, weather — and the price a book still anchored to his name and his last week has hung. Price every play before betting it.
For a broader look at how to use player prop models across all MLB categories, see our MLB player props guide.
Cold air and wind blowing in are the weather conditions that move home runs most. Check tonight's outdoor parks before placing HR props.
View MLB Weather & Wind10. Frequently Asked Questions
How accurate are MLB home run predictions?
Less accurate than most sites imply. A starter homers in about 12% of games, and even the best sluggers go homerless roughly three games in four. We publish our top three home run picks every day before first pitch and grade them in public, so the hit rate is on the public record.
What is the best stat for predicting home runs?
The hitter’s own power: his home run rate and contact quality such as barrel rate and expected isolated power. Sorted into fifths by season-to-date home run rate, starters ran from 6.9% to 17.4% of games with a homer — a far wider spread than the pitcher, the weather or a hot streak produces.
Does weather affect home runs in baseball?
Yes, mostly by taking them away. Against the same ballpark in the same month, games under 55°F ran about 1.7 points below normal and wind blowing in at 10+ mph cut home runs about 13%. Heat and wind blowing out added only about half a point, except at Wrigley Field.
What is barrel rate and why does it matter for HR props?
Barrel rate is the share of a batter’s batted balls hit at the ideal mix of exit velocity (95+ mph) and launch angle for extra bases. League average is about 7%; elite power hitters barrel 15-20%. It measures home run contact directly and settles far faster than home run totals do.
How often do the best power hitters actually hit home runs?
Less often than their reputation suggests. In 2026 the highest rate among regulars was Munetaka Murakami’s 26.4% of starts, with Aaron Judge, Pete Alonso and Kyle Schwarber near 25%. A typical starter homers in about 12% of games, so even the best go homerless three games in four.
See tonight's HR rankings
Every starter ranked by home run probability, rebuilt through the day as lineups and weather post. The top three are graded in public every day. Compare our numbers against your book's prices before placing HR props.
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