Baltimore orioles vs New york yankees match player stats

The baltimore orioles vs new york yankees match player stats for August 20, 2026, offer a useful snapshot of two American League East teams heading into the second game of their series at Oriole Park at Camden Yards. The Yankees enter with a 1-0 series advantage, while the Orioles return home looking to even the matchup.

This game is particularly interesting because the team-level numbers tell two different stories. Baltimore has the better batting average, on-base percentage, and run total, while New York owns a clear advantage in home runs and pitching efficiency. That contrast makes the individual player matchups especially important.

The Yankees arrive at 70-55 overall and 39-28 on the road. Baltimore is 61-65 and 32-31 at home. According to the supplied matchup data, the predictor gives Baltimore a 53.1% edge compared with 46.9% for New York. The betting market, however, lists the Yankees as -121 favorites, with Baltimore at +101.

The most important individual matchup begins on the mound. New York is expected to start right-hander Will Warren, while Baltimore is set to counter with right-hander Chris Bassitt. Warren has the stronger season-long run-prevention profile, although neither pitcher enters with an overwhelming statistical advantage.

For readers searching specifically for player statistics, the key is not simply identifying who has the highest batting average or most home runs. A useful matchup analysis has to connect individual production with pitching, recent form, injuries, team context, and the way those numbers could influence the game.

Table of Contents

Game overview and statistical context

The matchup is scheduled for August 20, 2026, at Oriole Park at Camden Yards. The listed start time is 3:35 AM in Pakistan, corresponding to the evening start in Baltimore.

The Yankees lead the series 1-0 after winning the previous game 3-1. That opening result matters because it gives New York an immediate advantage in the three-game set, but it does not automatically indicate that the Yankees have controlled every aspect of the matchup.

The first game was decided by limited offense and timely execution. That creates an interesting setup for the next contest because both clubs have enough offensive ability to produce a much higher-scoring game.

Here is the supplied statistical picture entering the matchup:

Category	Yankees	Orioles
Record	70-55	61-65
Division position	2nd	5th
Winning percentage	.560	.484
Games behind	5	14.5
Batting average	.229	.237
Runs	554	570
Hits	945	992
Home runs	172	152
OBP	.308	.320
SLG	.407	.398
Team ERA	3.24	4.23
Team WHIP	1.18	1.35
Night record	46-34	35-38

The most revealing part of this table is the difference between offense and pitching.

Baltimore has scored 570 runs compared with 554 for New York despite having fewer home runs. The Orioles also have a higher batting average and better on-base percentage.

New York, however, has a significant pitching advantage. A 3.24 team ERA and 1.18 WHIP compare favorably with Baltimore’s 4.23 ERA and 1.35 WHIP.

That distinction could determine the game.

baltimore orioles vs new york yankees match player stats: pitching matchup

The starting pitching matchup is Will Warren against Chris Bassitt.

Warren enters with an 8-6 record, a 4.42 ERA, and a 1.41 WHIP across 118.0 innings. He has recorded 117 strikeouts while walking 41 batters and allowing 18 home runs.

Bassitt enters with a 4-4 record, a 5.11 ERA, and a 1.62 WHIP over 61.2 innings. He has 40 strikeouts, 25 walks, and six home runs allowed.

At first glance, Warren has the better statistical profile.

Pitcher	W-L	ERA	WHIP	IP	H	K	BB	HR
Will Warren	8-6	4.42	1.41	118.0	125	117	41	18
Chris Bassitt	4-4	5.11	1.62	61.2	75	40	25	6

Why Warren’s workload matters

Warren has accumulated almost twice as many innings as Bassitt. That matters when evaluating the reliability of the numbers.

His 118 innings provide a much larger sample of performance. He has also generated 117 strikeouts, almost exactly matching his innings total.

The concern is the combination of 41 walks and 18 home runs. Warren has shown the ability to miss bats, but traffic and long balls remain obvious areas of risk.

Against a Baltimore lineup capable of producing extra-base hits, Warren cannot afford to turn too many plate appearances into favorable hitting counts.

Why Bassitt is difficult to evaluate from ERA alone

Bassitt’s 5.11 ERA and 1.62 WHIP are concerning, but the relatively small workload deserves attention.

He has pitched only 61.2 innings. That makes his current season line less stable than Warren’s larger sample.

Bassitt also has only six home runs allowed compared with Warren’s 18. That difference suggests the Orioles starter has not been equally vulnerable to the long ball.

The tradeoff is traffic. A 1.62 WHIP means Baltimore cannot expect him to simply cruise through the Yankees lineup.

His challenge will be limiting baserunners before New York’s power hitters get opportunities to drive them home.

The most important Yankees hitters

Ben Rice is the Yankees’ home run leader in the supplied statistics.

He has 33 home runs, a .249 batting average, and 78 RBI.

That combination makes Rice one of the most important power threats in the matchup. His .249 average is not the main reason he stands out. The 33 home runs are what change the way a pitcher has to approach him.

A pitcher facing a hitter with that level of home-run production cannot treat every count equally.

If Bassitt falls behind, Rice becomes particularly dangerous.

Cody Bellinger

Cody Bellinger leads the Yankees in batting average among the supplied team leaders.

His line is:

.259 batting average
.350 OBP
.420 SLG

The .350 OBP is especially useful when evaluating his contribution. Batting average tells us how frequently a player gets a hit, but on-base percentage captures a broader part of offensive value.

Bellinger’s ability to reach base can create opportunities for the Yankees’ power hitters.

However, Bellinger is listed on the 10-day injured list, with an estimated return date of August 22. That is an important limitation when interpreting the Yankees’ batting statistics.

A team can have excellent season-long numbers while its actual lineup on a specific night is weaker because important players are unavailable.

That is one reason season statistics should never be treated as a substitute for the confirmed lineup.

Other Yankees offensive considerations

New York has 172 home runs as a team, 20 more than Baltimore.

That gap is substantial.

The Yankees are not necessarily the more consistent contact team. Their .229 batting average is lower than Baltimore’s .237 mark. But their power profile gives them the ability to change a game quickly.

A single home run can erase several innings of otherwise modest offensive production.

That dynamic becomes even more important when facing a pitcher with a 5.11 ERA and 1.62 WHIP.

The most important Orioles hitter

Pete Alonso leads the Orioles in the supplied offensive statistics.

His line is:

.267 batting average
.360 OBP
.494 SLG
28 home runs
81 RBI

This is arguably the strongest all-around offensive statistical line presented in the matchup data.

Alonso’s .267 batting average is higher than both team’s listed leaders except where another specific statistic is considered. His .360 OBP is also the best among the featured batting leaders, while his .494 slugging percentage shows substantial extra-base impact.

His 81 RBI lead the Orioles and exceed Ben Rice’s 78.

That makes Alonso an important player to watch against Warren.

Why Alonso’s plate appearances matter

The most important question is not simply whether Alonso gets a hit.

It is where his plate appearances occur.

If Baltimore can put runners on base ahead of Alonso, his RBI production becomes much more relevant. If Warren consistently reaches two outs with the bases empty, Alonso’s opportunities to create damage decline.

This is why individual statistics need context.

A player’s RBI total does not tell us exactly how good that player is in every situation, but it does help explain how often his offensive production has translated into runs.

Team offense versus team pitching

The most interesting statistical contrast in this matchup is the Orioles’ offensive edge against the Yankees’ pitching edge.

Baltimore:

.237 batting average
.320 OBP
.398 SLG
570 runs
992 hits
152 home runs

New York:

.229 batting average
.308 OBP
.407 SLG
554 runs
945 hits
172 home runs

Baltimore has 47 more hits and 16 more runs despite hitting 20 fewer home runs.

That tells us something important.

The Orioles’ offensive production has been less dependent on home runs than New York’s.

The Yankees, meanwhile, have produced more slugging power despite having a lower batting average and lower OBP.

This creates two different offensive identities.

Baltimore’s advantage is getting people on base and generating offense through a broader mix of hits and baserunners.

New York’s advantage is the ability to produce significant damage with fewer opportunities.

What the ERA and WHIP numbers reveal

New York’s 3.24 team ERA is the biggest statistical reason to take the Yankees seriously despite Baltimore’s offensive advantages.

The Orioles have a 4.23 team ERA.

That is a difference of 0.99 earned runs per nine innings.

The WHIP gap is also meaningful:

Yankees: 1.18
Orioles: 1.35

A lower WHIP generally indicates that a pitching staff allows fewer hits and walks per inning.

New York’s pitching staff therefore has the stronger baseline entering this matchup.

That does not mean Baltimore’s hitters cannot score.

It means Baltimore likely needs to win individual plate appearances rather than rely on a general pitching weakness across the opposing roster.

Recent form entering the game

The role of the first game

The Yankees’ 3-1 victory in the previous game is important, but it should not be overinterpreted.

A one-game result is a very small sample.

Baltimore’s offense had opportunities but failed to convert effectively in the supplied game context. The Orioles’ broader season numbers show that they can score runs.

The next game therefore becomes less about proving which team is better and more about which team executes better in a specific set of opportunities.

This distinction is important for anyone studying baseball statistics.

Season statistics describe the broader performance level.

Game statistics describe what happened in one night.

Neither should be confused with the other.

The injury factor

Injuries are one of the biggest reasons a season-long statistical comparison can be misleading.

The Yankees list several players on the injured list:

Cody Bellinger
Kervin Castro
Max Fried
Giancarlo Stanton
Clarke Schmidt

The Orioles list:

Samuel Basallo
Blaze Alexander
Felix Bautista
Ryan Helsley
Ryan Mountcastle

Some of these absences affect the starting lineup, while others affect pitching depth or the bullpen.

Max Fried’s absence is particularly relevant to New York’s rotation because it changes the pitching structure around Warren.

Giancarlo Stanton’s absence also removes another established power threat from the Yankees’ offensive options.

Baltimore has its own significant losses, particularly among pitching and established offensive depth.

This is why a useful player-statistics article should distinguish between season totals and the players actually available for the game.

Night-game performance

The Yankees have a 46-34 record in night games.

Baltimore is 35-38.

That creates another small but useful contextual difference.

New York has won 57.5% of its listed night games, while Baltimore has won about 47.9%.

The Yankees therefore have a clear historical edge in the supplied night-game record.

However, this should not be treated as a prediction by itself.

Night-game records include games played against many different opponents, in different ballparks, with different pitchers and lineups.

It is best viewed as supporting context rather than a primary predictive statistic.

Why the matchup predictor favors Baltimore

The supplied matchup predictor gives Baltimore a 53.1% probability and New York 46.9%.

That is a relatively narrow difference.

A 53.1% projection is not a statement that Baltimore is dramatically better.

It means the model sees a small edge.

This is important because the betting market lists New York at -121, while Baltimore is +101.

The two signals therefore point in different directions.

The statistical matchup predictor slightly favors Baltimore.

The market price favors New York.

That disagreement is one of the most interesting aspects of this game.

It suggests that there is no overwhelming consensus based on the available numbers.

How Warren can change the game

Warren’s biggest strength is his strikeout production.

With 117 strikeouts in 118 innings, he has demonstrated an ability to finish plate appearances without relying entirely on balls in play.

That matters against Baltimore because the Orioles have more hits and a higher batting average than New York.

Strikeouts remove the possibility of defensive errors, baserunning events, and many types of balls in play.

The problem is Warren’s 41 walks and 18 home runs allowed.

The ideal version of Warren keeps the bases clean and forces Baltimore to earn its offense.

The dangerous version allows traffic, then gives up a high-impact extra-base hit.

How Bassitt can change the game

Bassitt’s statistical challenge is different.

His 1.62 WHIP suggests that New York should have opportunities to reach base.

But his six home runs allowed are notably lower than Warren’s 18.

If Bassitt can limit the Yankees’ power hitters while allowing singles and minimizing free passes, he could keep Baltimore in the game deep into the contest.

The critical factor is avoiding high-leverage mistakes.

Against a lineup with 172 team home runs, one poorly located pitch can produce a completely different game state.

The power battle

The home-run comparison is simple:

Yankees: 172

Orioles: 152

New York has the advantage by 20 home runs.

But Baltimore’s Pete Alonso has 28 by himself, while New York’s Ben Rice has 33.

That means the individual power matchup is much closer than the overall team totals suggest.

A game between these teams does not require a long string of hits to become dangerous.

One swing can change the score.

That is particularly relevant at Camden Yards, where the environment can reward well-struck balls depending on location and conditions.

The on-base battle

Baltimore’s .320 OBP is better than New York’s .308.

That difference supports the idea that Baltimore has been more successful at creating baserunners.

It also helps explain why the Orioles have scored 570 runs despite hitting fewer home runs.

If Baltimore gets runners on before Alonso and its other power threats, Warren’s walk rate becomes more important.

The Yankees, meanwhile, need to find ways to compensate for their lower team OBP through power and timely hitting.

The slugging battle

New York has a .407 SLG compared with Baltimore’s .398.

The difference is not huge, but it reinforces the home-run advantage.

Baltimore gets on base more often.

New York produces slightly more slugging impact.

That is a classic example of why no single offensive statistic gives a complete answer.

A team can have the better batting average and still lose the slugging comparison.

Another team can have more power while producing fewer overall baserunners.

The matchup becomes interesting because both profiles are capable of winning in different ways.

What to watch in the first three innings

The opening innings should provide an early indication of the game’s shape.

For Warren, the key questions are:

Is he getting ahead in counts?
Is he generating swings and misses?
Is he keeping Baltimore’s first hitters off base?
Can he avoid giving Alonso RBI opportunities?

For Bassitt:

Can he limit walks?
Can he prevent early extra-base hits?
Can he keep Rice from getting into favorable power counts?
Can he reach the middle innings without a large pitch count?

The first three innings will not decide the game, but they can reveal whether either starter is struggling with command.

What to watch in the middle innings

The middle innings often reveal which team’s depth is working.

If Warren exits early, the Yankees will need their bullpen to absorb additional innings.

If Bassitt struggles to complete five innings, Baltimore could be forced to use multiple relievers earlier than planned.

This is where the team ERA difference becomes relevant.

New York’s 3.24 team ERA suggests a stronger overall run-prevention foundation.

Baltimore’s 4.23 ERA leaves less margin for error if Bassitt cannot provide length.

The bullpen question

Bullpen statistics can be difficult to evaluate without knowing exactly which relievers are available on the day.

Recent workload matters.

A reliever who has thrown on consecutive days may not be available for a high-leverage situation even if he is technically on the active roster.

The injuries listed for both teams also affect bullpen depth.

For that reason, the final player statistics after the game should be evaluated alongside bullpen usage rather than simply comparing season ERA.

What the odds suggest

The supplied moneyline is:

Yankees -121
Orioles +101

The run line is:

Yankees -1.5 at +135
Orioles +1.5 at -163

The total is listed at 9 runs:

Over 9 at -120
Under 9 at +100

These numbers reflect a market expectation that New York has a modest advantage, but not a dominant one.

The run line is particularly revealing.

The Yankees are favored on the moneyline, but the +135 price on New York -1.5 indicates that winning by two or more runs is considered considerably less certain than simply winning the game.

That fits the statistical picture.

The two teams have enough offensive and pitching differences to make the outcome difficult to call with confidence.

What could produce a high-scoring game

A higher-scoring result would become more likely if:

Warren’s walks create early baserunners.
Bassitt struggles with command.
Either starter allows multiple extra-base hits.
The Yankees’ power hitters capitalize on mistakes.
Baltimore turns its .320 OBP advantage into runners in scoring position.
Bullpen fatigue becomes a factor.

The total is set at 9, so the market is not expecting an extremely low-scoring pitching duel.

Still, the previous game finished 3-1, showing how quickly a game between these teams can remain below that level.

What could produce another low-scoring game

A lower-scoring result could develop if Warren’s strikeout ability is working and Bassitt limits the Yankees’ home-run threats.

The Yankees’ recent results also point toward a team that has been involved in relatively tight games.

Baltimore has produced more offensive fireworks recently, including a 10-2 victory, but also has losses where its offense struggled.

The range of possible outcomes is therefore wide.

A practical player-statistics checklist

For readers following the game live, the most useful statistics to monitor are not necessarily the final box-score numbers.

Watch these areas:

For Warren

Strikeouts: A strong strikeout rate can neutralize Baltimore’s contact advantage.

Walks: Free baserunners are especially dangerous against a lineup with a high-impact middle of the order.

Home runs allowed: This is Warren’s clearest statistical vulnerability.

Pitches per inning: A high pitch count could shorten his outing.

For Bassitt

WHIP: His season number is 1.62, so limiting baserunners is essential.

Walks: New York’s power becomes more dangerous when runners are already aboard.

Home runs: His season total of six is encouraging relative to Warren’s 18.

Innings: Length could determine how much pressure falls on Baltimore’s bullpen.

For the hitters

OBP: Shows who is consistently creating opportunities.

SLG: Highlights extra-base and power impact.

RBI opportunities: Shows whether baserunners are being converted into runs.

Home runs: The quickest way either lineup can change the game.

How to interpret the final box score

After the game, the box score should be read in context.

Suppose Alonso goes 1-for-4 with no RBI.

That does not necessarily mean he had a poor game. If his one hit started a rally or came against a difficult pitch, the context matters.

Likewise, a pitcher who allows three runs may have pitched better than one who allows two if the defensive and baserunning circumstances were very different.

The most useful postgame analysis combines:

Batting line
Pitching line
Situational hitting
Pitch count
Defensive plays
Bullpen usage
Baserunning
Game leverage

This produces a more accurate explanation than simply identifying the player with the highest batting average.

Statistical comparison at a glance

The overall matchup can be summarized this way:

New York’s biggest advantages

Better overall record
Better road record
More home runs
Better team ERA
Better team WHIP
Stronger night-game record
Current 1-0 series lead

Baltimore’s biggest advantages

Higher batting average
Higher OBP
More hits
More runs
Better listed individual batting line from Pete Alonso
Slightly stronger matchup predictor

This is a genuine contrast rather than a matchup where one team dominates every category.

Why the Yankees can win

New York’s path to victory is fairly clear.

The Yankees need Warren to provide enough innings while limiting walks and home runs.

Offensively, they need their power advantage to compensate for the lower batting average and OBP.

If Rice or another power hitter connects with runners aboard, the Yankees can create multiple runs without needing a large number of hits.

Their biggest structural advantage is pitching.

A 3.24 team ERA gives New York more room for offensive mistakes.

Why the Orioles can win

Baltimore’s path is also clear.

The Orioles need Bassitt to limit the Yankees’ power while their offense uses its higher OBP and batting average to create traffic.

Alonso is a major part of that plan.

If Baltimore gets multiple runners on base before its key run producers come to the plate, the Orioles can turn their offensive strengths into a meaningful scoreboard advantage.

The Orioles also have the matchup predictor slightly favoring them.

That suggests the game is far from a one-sided projection.

The biggest statistical storyline

The biggest storyline is the conflict between New York’s pitching strength and Baltimore’s offensive consistency.

The Yankees have a nearly one-run advantage in team ERA.

Baltimore has a .008 advantage in batting average and a .012 advantage in OBP.

Those differences point in opposite directions.

If the game becomes a contest of baserunners and contact, Baltimore’s offensive profile becomes more valuable.

If it becomes a contest of power and run prevention, New York’s profile becomes more attractive.

That is the central statistical tension of the matchup.

A note about player availability

One of the most important lessons from this matchup is that season statistics should never be copied into a game preview without checking player availability.

Cody Bellinger is listed on the injured list.

Giancarlo Stanton is also listed on the injured list.

Max Fried is unavailable for the Yankees’ rotation.

Baltimore has several injured players as well.

Therefore, the season-long team batting statistics describe what each club has accomplished over the year, not necessarily the exact lineup that will appear in the game.

For readers trying to understand live player performance, the confirmed starting lineup is always more relevant than a season leaderboard alone.

Final statistical perspective

The baltimore orioles vs new york yankees match player stats point toward a competitive game with no single overwhelming statistical advantage.

New York enters with the better record, stronger pitching numbers, more home runs, and the series lead.

Baltimore enters with the better batting average, better OBP, more hits, more runs, and a narrow 53.1% matchup-model advantage.

Will Warren has the stronger season pitching profile than Chris Bassitt, but Warren has also allowed significantly more home runs. Bassitt has the higher ERA and WHIP, yet his six home runs allowed show a different type of risk.

At the plate, Ben Rice represents New York’s leading home-run threat with 33 homers and 78 RBI. Pete Alonso gives Baltimore a balanced offensive presence with a .267 average, .360 OBP, .494 SLG, 28 home runs, and 81 RBI.

The Yankees’ 172 home runs compared with Baltimore’s 152 explain much of New York’s power advantage. Baltimore’s 570 runs compared with New York’s 554, meanwhile, show that the Orioles have generated slightly more total scoring despite having less home-run production.

That is why the matchup cannot be reduced to one statistic.

The most meaningful questions are whether Warren can control Baltimore’s baserunners, whether Bassitt can survive the Yankees’ power threats, whether Alonso can create RBI opportunities, and whether New York can turn its home-run advantage into actual runs.

The previous 3-1 Yankees victory gives New York momentum in the series, but Baltimore still has the statistical profile to respond.

For anyone studying the game through player statistics, the most useful approach is to combine individual production with pitching quality, availability, recent form, and team context. That provides a much clearer picture than relying on batting average, ERA, or home runs alone.

In the end, the numbers suggest a closely balanced matchup with contrasting strengths. New York has the stronger run-prevention foundation and greater power. Baltimore has the stronger contact and on-base profile. The starting pitchers represent different forms of risk, and the outcome may depend on which team is better able to turn its statistical strengths into productive plate appearances.

Frequently Asked Questions

What are the key baltimore orioles vs new york yankees match player stats?

The key individual figures include Will Warren’s 8-6 record, 4.42 ERA, 1.41 WHIP, and 117 strikeouts for New York. Chris Bassitt has a 4-4 record, 5.11 ERA, and 1.62 WHIP for Baltimore. Ben Rice leads the Yankees with 33 home runs, while Pete Alonso leads the Orioles with 28 home runs and 81 RBI.

Who is the Yankees’ leading home-run hitter?

Ben Rice leads the Yankees in the supplied statistics with 33 home runs and 78 RBI. His .249 batting average is also part of his current offensive profile.

Who is the Orioles’ leading hitter?

Pete Alonso leads the Orioles’ supplied batting statistics with a .267 batting average, .360 OBP, and .494 SLG. He also has 28 home runs and 81 RBI.

Which team has the better pitching statistics?

The Yankees have the stronger team pitching numbers. New York has a 3.24 team ERA and 1.18 WHIP, compared with Baltimore’s 4.23 ERA and 1.35 WHIP.

Who is expected to start for the Yankees and Orioles?

Will Warren is the listed probable starter for New York, while Chris Bassitt is the listed probable starter for Baltimore.

Who has the better overall record?

The Yankees have the better record at 70-55, compared with Baltimore’s 61-65. New York also enters the game with a 1-0 lead in the series.