MLB Hit Rates
Retail sportsbooks lean hard on long-shot bets — big odds, thin real chances. The price looks generous because the probability is worse than it feels. Our picks are data-driven and every one of them is graded here, so you can judge a bet by its actual chance of hitting rather than by how the odds are packaged. Where our hit rate beats the market’s, that gap is your leverage.
62.2%
1413–859–4 · n=2,276 · leg hit rate, last 7 days
What each number means
Our picks (legs)
62.2%
1413–859 · every graded straight pick
Market baseline
58.3%
298–213 · how often the favored side wins
When we disagreed
45.1%
96–117 · our rate only when we broke from the market
Long shots
28.6%
783–1954 · -41.7u over 130 priced picks
Straight picks by market
Bars above the line beat the −110 breakeven rate (52.4%); bars below it don’t.
Game markets
baseline 52.4%
Table view
| Label | Value | Context |
|---|---|---|
| Total | 59.6% | 53–36 |
| Moneyline | 59.1% | 55–38 |
| Spread | 51.6% | 48–45 |
Player props
baseline 52.4%
Table view
| Label | Value | Context |
|---|---|---|
| Batter Rbis | 86.5% | 109–17 |
| Pitcher Strikeouts | 63.2% | 48–28 |
| Batter Hits | 62.4% | 595–358 |
| Batter Total Bases | 62.0% | 443–272 |
| Batter Runs | 12.5% | 1–7 |
Over vs. under, by market
The side-mix honesty check — are we leaning one direction more than the results support?
Under Over
Table view
| Label | Under | Over |
|---|---|---|
| Total | 64.2% under (n=55) | 52.8% over (n=38) |
| Batter Hits | 70.4% under (n=203) | 60.3% over (n=750) |
| Batter Rbis | 86.5% under (n=126) | no overs |
| Batter Total Bases | 64.9% under (n=288) | 60.0% over (n=427) |
| Batter Runs | no unders | 12.5% over (n=8) |
| Pitcher Strikeouts | 48.1% under (n=27) | 71.4% over (n=49) |
Does our confidence label mean anything?
If our confidence tiers are honest, this chart should slope up: Strong should hit more than Lean, and Lean more than Slight.
Table view
| Label | Value | Context |
|---|---|---|
| Slight | 55.3% | n=485 |
| Lean | 58.0% | n=776 |
| Strong | 68.7% | n=1015 |
Parlays
Actual win rate by parlay type
Table view
| Label | Value | Context |
|---|---|---|
| RBIs | 68.8% | n=16 |
| Pitcher K's | 42.2% | n=45 |
| Total Bases | 41.7% | n=24 |
| 2-Leg Parlay | 31.0% | n=71 |
| Game Outcome | 29.2% | n=96 |
| Hits | 20.0% | n=20 |
| Game Total | 16.7% | n=24 |
| Runs | 5.9% | n=17 |
| 3-Leg Parlay | 0.0% | n=8 |
| Home Runs | 0.0% | n=21 |
| Same-Game | 0.0% | n=1 |
Actual vs. expected
Expected assumes independent legs (leg rate raised to the average leg count). A leg hit rate and a parlay hit rate are different measurements — three legs at 55% each is roughly a 17% parlay, not 55%.
Expected Actual
Table view
| Label | Expected | Actual |
|---|---|---|
| RBIs | 31.4% expected | 68.8% actual |
| Pitcher K's | 31.0% expected | 42.2% actual |
| Total Bases | 31.1% expected | 41.7% actual |
| 2-Leg Parlay | 38.7% expected | 31.0% actual |
| Game Outcome | 30.5% expected | 29.2% actual |
| Hits | 31.2% expected | 20.0% actual |
| Game Total | 30.5% expected | 16.7% actual |
| Runs | 30.9% expected | 5.9% actual |
| 3-Leg Parlay | 24.1% expected | 0.0% actual |
| Home Runs | 31.6% expected | 0.0% actual |
| Same-Game | 24.1% expected | 0.0% actual |
Methodology
What counts as a "leg" hit rate?
A leg is one graded pick — one side of one market on one game or player prop. The leg hit rate is wins divided by decided legs (wins plus losses; pushes are excluded from both sides).
How is a parlay hit rate different from a leg hit rate?
A parlay only pays out when every leg in it hits. A parlay hit rate is the share of full parlay tickets that won outright, so it is always lower than the leg hit rate that built it.
What is the market baseline / breakeven rate?
At standard −110 odds, a bettor needs to win about 52.4% of the time just to break even before any edge. We show our own hit rate against that line so it can be judged as leverage, not just a percentage.
What is a "long shot" pick?
A long shot is a player-prop pick our model gave less than a 50% chance of hitting before the game. We track these separately by units won or lost against the actual book price, not by win percentage alone.
Why does confidence calibration matter?
Every pick is labeled Slight, Lean, or Strong before the game is played. If that label means anything, Strong picks should hit more often than Lean, and Lean more often than Slight — the chart above shows that comparison directly.