MLB Betting Trends Since 2004: Favorites, Runlines & Totals
MLB betting markets have produced several durable historical patterns since 2004, but the most important lesson is that win rate and betting value are not the same thing. This study compares favorites, underdogs, runlines, home-field results, totals, and heavy-favorite performance to establish a long-term market baseline.
Quick Answer: What Do MLB Betting Trends Since 2004 Show?
| Market Result | Historical Result |
|---|---|
| MLB favorites | 58.2% straight-up win rate |
| MLB home teams | 53.7% straight-up win rate |
| Runline underdogs (+1.5) | 57.1% cover rate |
| Runline favorites (-1.5) | 42.9% cover rate |
| Favorites -200 or higher | 70.5% straight-up win rate |
| Overs vs. unders | 24,107 overs, 24,987 unders, 2,355 pushes |
These figures describe how often each side won or covered in the historical sample. They do not automatically prove profitability because the price attached to each wager still determines break-even rate and ROI.
Dataset and Methodology
The analysis uses ProComputerGambler’s historical MLB market database beginning in 2004. The tables below summarize straight-up moneyline outcomes, runline results, home/road splits, totals results, and posted average totals by season. The seasonal totals table currently runs through 2025. Sample sizes vary by market because not every historical game has an identical graded moneyline, runline, and totals record in the displayed dataset.
For deeper comparisons of moneyline profitability, see MLB Favorites vs. Underdogs Betting Results and MLB Favorite Win Percentage. This page focuses on the broader market structure.
For team-specific historical records rather than league-wide averages, use the MLB team trends archive.
The broad results are useful as a baseline: favorites win more often, home teams hold a modest straight-up advantage, runline underdogs cover more often than runline favorites, and over/under outcomes are close to balanced. The next step is always to compare those frequencies with the price required to bet them.
Runline Favorites vs Underdogs
One of the most interesting structural characteristics of mlb betting markets appears in runline betting.
The runline functions similarly to a point spread in other sports. Favorites must win by two or more runs (-1.5), while underdogs can either win the game outright or lose by exactly one run (+1.5).
Runline Results Since 2004
| Bet Type | Record | Win % |
|---|---|---|
| Runline Favorites (-1.5) | 18,979-25,285 | 42.9% |
| Runline Underdogs (+1.5) | 25,285-18,979 | 57.1% |
The displayed runline sample contains 44,264 graded decisions.
Runline favorites covered 42.9% of games, while +1.5 runline underdogs covered 57.1%.
This result highlights an important reality of baseball games: many games are decided by a single run.
The 42.9% cover rate shows how difficult it is for favorites to clear -1.5 runs. It does not, by itself, establish whether favorite or underdog runlines were profitable because the price attached to each runline also matters.
The practical lesson is to evaluate both the +1.5-run cushion and the attached price rather than treating either side’s cover rate as an automatic edge.
Moneyline Favorites vs Underdogs
The most common wager in baseball is the moneyline, where bettors simply choose which team will win the game.
Since 2004, MLB favorites have won the majority of games.
Moneyline Results Since 2004
| Bet Type | Record | Win % |
|---|---|---|
| Favorites | 30,008-21,514 | 58.2% |
| Underdogs | 21,514-30,008 | 41.8% |
At first glance, betting favorites might appear to be a profitable strategy. However, sportsbooks adjust prices accordingly.
Despite winning 58.2% of games, the broader favorite dataset produced approximately -1.8% ROI when every favorite was bet. See the full MLB favorite win-rate analysis for the profitability breakdown.
This is because sportsbooks increase the price on favorites, forcing bettors to risk more money relative to the potential payout.
In other words:
High win rates do not automatically produce profitable betting strategies.
Home Field Advantage in MLB
Another frequently discussed factor in sports betting is home field advantage.
Historically, MLB home teams have enjoyed a modest edge.
Home Team Performance Since 2004
| Team Type | Record | Win % |
|---|---|---|
| Home Teams | 28,307-24,374 | 53.7% |
| Road Teams | 24,374-28,307 | 46.3% |
Home teams win about 53–54% of MLB games, which aligns closely with historical league averages.
The market also prices home advantage into moneylines, so a 53.7% straight-up win rate is not evidence that blindly betting home teams is profitable.
Home vs Road Favorites
Breaking the results down further reveals similar patterns.
Favorite Performance by Location
| Favorite Type | Record | Win % |
|---|---|---|
| Home Favorites | 20,213-13,998 | 59.1% |
| Road Favorites | 9,784-7,510 | 56.6% |
Home favorites win slightly more often, which makes sense given the combination of team strength and home field advantage.
But again, sportsbooks price these expectations into the betting lines.
Underdog Performance
Underdog results vary significantly depending on whether the team is playing at home or on the road.
Road Underdogs
| Record | Win % |
|---|---|
| 7,180-9,483 | 43.1% |
Road underdogs win far less frequently than favorites, which is expected given the disadvantages of both team strength and travel.
However, when runlines are used instead of moneylines, underdogs become much more competitive because many mlb games remain close.
MLB Totals Market Efficiency
Totals betting — wagering on whether the combined score of both teams will go over or under the posted number — is another extremely popular MLB market.
Since 2004, totals betting results have been very balanced.
Overs vs Unders Since 2004
| Bet Type | Record | Win % |
|---|---|---|
| Overs | 24,107 | |
| Unders | 24,987 | |
| Push | 2,355 |
The displayed totals sample contains 51,449 graded results, including 2,355 pushes.
Among non-push decisions, overs accounted for approximately 49.1% and unders approximately 50.9%.
The narrow split shows that raw over/under outcomes were close to balanced. Profitability still depends on the prices and juice paid, so this result is better treated as a market baseline than proof of efficiency by itself.
Average MLB Totals by Season
Another interesting trend appears when examining how average totals have changed over time.
| Season | Avg Total |
|---|---|
| 2025 | 8.5 |
| 2024 | 8.3 |
| 2023 | 8.7 |
| 2022 | 8.2 |
| 2021 | 8.6 |
| 2020 | 8.8 |
| 2019 | 9.1 |
| 2018 | 8.6 |
| 2017 | 8.9 |
| 2016 | 8.4 |
| 2015 | 7.8 |
| 2014 | 7.8 |
| 2013 | 8.0 |
| 2012 | 8.2 |
| 2011 | 8.1 |
| 2010 | 8.4 |
| 2009 | 8.9 |
| 2008 | 8.9 |
| 2007 | 9.1 |
| 2006 | 9.2 |
| 2005 | 8.9 |
| 2004 | 9.1 |
Several distinct scoring environments appear:
• High offense era (2004-2009)
• Pitching-dominant era (2013-2015)
• Juiced ball era (2017-2019)
• Modern balanced scoring environment
These shifts demonstrate how league-wide conditions influence sportsbook totals.
Large Favorites
Many bettors assume large favorites are overpriced, but historical results show a more nuanced picture.
Favorites -150 or Higher
| Record | Win % |
|---|---|
| 13,945-7,823 | 64.1% |
Favorites -200 or Higher
| Record | Win % |
|---|---|
| 4,831-2,021 | 70.5% |
Large favorites win frequently, but straight-up win percentage alone cannot establish profitability. A -200 favorite needs to win 66.7% just to break even; the -200-or-higher group won 70.5% overall, but the actual return still depends on the distribution of prices within that group.
The takeaway is that heavy-favorite analysis must combine win rate with the break-even probability implied by each moneyline price.
Totals Extremes
Totals also behave differently when the posted number is unusually low or high.
Games With Totals 8 or Lower
| Result | Win % |
|---|---|
| Over | 48.3% |
| Under | 51.7% |
The raw result leans slightly toward the under, but the split alone does not identify a betting edge without the prices and broader sample context.
Games With Totals 10 or Higher
| Result | Win % |
|---|---|
| Over | 50.6% |
| Under | 49.4% |
High totals tend to produce more balanced results.
Divisional Games
Another common belief among bettors is that divisional matchups behave differently because teams are more familiar with each other.
However, historical results suggest otherwise.
Divisional Games
| Result | Record | Win % |
|---|---|---|
| Favorites | 13,111-9,430 | 58.2% |
In this broad straight-up comparison, divisional favorites produced the same 58.2% win rate as favorites overall. That does not prove divisional familiarity has no effect; it means no difference appears in this top-line win-rate comparison.
What These Results Mean for Bettors
Several key lessons emerge from this historical analysis:
1. Runline underdogs covered more often than runline favorites in this sample.
The +1.5-run cushion naturally raises cover frequency; the attached price determines whether that frequency translates into value.
2. Favorites win often, but the price can erase the advantage.
In the broader favorite dataset, a 58.2% straight-up win rate still produced approximately -1.8% ROI when every favorite was bet.
3. Raw over/under outcomes are close to balanced.
The near-even split is useful context, but profitability still depends on the total, price, and situational inputs rather than the side label alone.
4. Home teams have a measurable straight-up advantage, but price determines betting value.
Home teams won 53.7% of games in the sample, but that figure alone does not show whether betting home teams at the listed moneyline was profitable.
What MLB Betting Market History Actually Tells Us
The long-term MLB data is most useful as a market baseline. It shows what broad categories have done historically, but it does not turn those categories into automatic betting systems. Price, timing, sample size, and the specific conditions behind a wager still matter.
For deeper analysis, compare these broad results with MLB betting market efficiency research and the site’s historical baseball betting systems archive, where narrower conditions can be evaluated separately.
Understanding the baseline behavior of the mlb betting market is the first step toward identifying opportunities where the odds may not fully reflect the true probability of an outcome.
MLB Situational Betting Research
Broad market averages are only the starting point. The studies below isolate narrower MLB situations—such as home underdogs, extra-inning games, blowout losses, high-scoring games, and runline pricing—to test whether specific conditions behave differently from the league-wide baseline.
• MLB Home Underdog Betting Results
Analysis of how home underdogs perform straight-up and whether the home field advantage creates betting value.
• MLB Runline Betting Trends
A breakdown of how favorites and underdogs perform against the -1.5 runline spread.
• MLB Teams After Scoring 10+ Runs
Does offensive momentum carry over into the next game?
• MLB Teams After Extra-Inning Games
Testing the popular theory that bullpen fatigue impacts teams following long games.
• MLB Teams After Blowout Losses
Do MLB teams bounce back after losing by five or more runs?
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