Milwaukee Bucks vs Dallas Mavericks Match Player Stats

The milwaukee bucks vs dallas mavericks match player stats from April 1, 2026, reveal a convincing 123-99 victory for the Milwaukee Bucks at Fiserv Forum in Milwaukee, Wisconsin. Milwaukee won by 24 points, combining efficient three-point shooting, strong ball movement, and effective interior defense to control the game across all four quarters. Ryan Rollins led the Bucks with 24 points and nine assists, while Kyle Kuzma added 20 points. For Dallas, Cooper Flagg recorded 19 points and 10 rebounds, and Brandon Williams contributed 18 points off the bench. Although the Mavericks collected 50 rebounds and 12 steals, their 35% field-goal shooting and 28% accuracy from beyond the arc made it difficult to keep pace with Milwaukee’s offense.

The game provides a useful example of why basketball results cannot be explained by scoring alone. Rebounds, assists, shooting efficiency, defensive stops, and player plus-minus all help explain how one team creates a decisive advantage. Milwaukee finished with 28 assists, made 20 three-pointers, and recorded nine blocks. Dallas, meanwhile, struggled to convert its shooting opportunities into consistent offensive pressure.

This breakdown examines the final score, individual player performances, team statistics, quarter-by-quarter scoring, tactical differences, and the most important lessons from the matchup. All game-specific figures and player highlights in this article are based on the supplied April 1, 2026, box-score data.

Milwaukee Bucks vs Dallas Mavericks Match Player Stats: Game Overview

The matchup between Milwaukee and Dallas ended with the Bucks winning 123-99. The 24-point margin reflected a consistent scoring advantage rather than a narrow contest decided by a final possession.

Milwaukee scored at least 25 points in every quarter and reached 38 points in the opening period. Dallas managed 31 points in the first quarter but could not maintain the same offensive output in the next two periods.

Final Score and Match Details

Match Detail	Information
Game date	April 1, 2026
Home team	Milwaukee Bucks
Away team	Dallas Mavericks
Final score	Milwaukee Bucks 123, Dallas Mavericks 99
Winning team	Milwaukee Bucks
Winning margin	24 points
Venue	Fiserv Forum
Location	Milwaukee, Wisconsin
Attendance	16,414
Milwaukee record displayed	30-45 overall, 17-21 at home
Dallas record displayed	24-52 overall, 10-28 away
Season series	Milwaukee leads 2-0

These details establish the setting for the statistical analysis. Milwaukee entered the game with a displayed home record of 17-21, while Dallas had a displayed away record of 10-28. Those records provide context, but they do not independently explain the result. The shooting and playmaking figures from the game offer a more direct explanation of why the Bucks won.

The attendance of 16,414 also indicates that the game took place before a substantial home crowd. However, attendance alone cannot establish how much the crowd influenced individual performances or the final result.

Why the 24-Point Margin Matters

A 24-point difference is significant because it usually requires a sustained advantage across several possessions. A team can win a close game through a late scoring run, a few successful free throws, or one decisive defensive stop. A margin of this size generally calls for a broader examination of the game.

Milwaukee’s performance featured three especially important advantages:

• Three-point production: The Bucks made 20 shots from beyond the arc, compared with 10 for Dallas.
• Offensive coordination: Milwaukee recorded 28 assists, 10 more than the Mavericks.
• Rim protection: The Bucks blocked nine shots, more than twice Dallas’s four.

These numbers help explain the result without relying on assumptions about motivation, chemistry, or coaching decisions that are not established by the supplied statistics.

The most revealing finding is that Milwaukee did not need to dominate every statistical category. Dallas recorded more steals and offensive rebounds, yet Milwaukee still won comfortably. The difference came from how effectively the teams converted their opportunities into points.

Quarter-by-Quarter Scoring Breakdown

The scoring progression shows how Milwaukee established control early and maintained its advantage throughout the game.

Quarter	Milwaukee Bucks	Dallas Mavericks	Milwaukee Lead
First quarter	38	31	7
Second quarter	27	20	14
Third quarter	25	19	20
Fourth quarter	33	29	24
Final score	123	99	24

The Bucks outscored Dallas in every quarter. That consistency is one of the strongest indicators of their overall performance.

First Quarter: Milwaukee Establishes the Pace

Milwaukee opened with 38 points, while Dallas scored 31. Both teams produced a relatively high-scoring first quarter, but the Bucks created a seven-point advantage immediately.

Scoring 38 points in a single period can result from several factors, including efficient shooting, successful transition opportunities, good spacing, and accurate perimeter shots. The available team statistics support the importance of Milwaukee’s shooting and passing, although the quarter totals alone cannot establish which specific plays produced those 38 points.

Dallas remained competitive offensively in the opening period. Its 31 points suggest that the Mavericks were able to score, even as Milwaukee built an early lead.

The distinction was efficiency. Milwaukee eventually finished with a 45% field-goal percentage, compared with Dallas’s 35%.

Second Quarter: The Bucks Double Their Advantage

Milwaukee scored 27 points in the second quarter, while Dallas added 20. The Bucks increased their lead from seven points to 14 by halftime.

This period mattered because Dallas did not reduce the deficit after its respectable opening quarter. Instead, Milwaukee continued to score at a higher rate.

The second-quarter figures also illustrate why teams must respond to an opponent’s early scoring run. When a team falls behind, it can become tempting to chase the deficit through difficult three-point attempts or rushed possessions. That approach can make a comeback harder if the shots do not fall.

The supplied figures do not establish whether Dallas followed that pattern, so it would be inaccurate to attribute the deficit to a specific tactical decision. What the score confirms is that Milwaukee won the quarter by seven points and entered halftime with greater control of the contest.

Third Quarter: Milwaukee Builds a 20-Point Lead

The Bucks scored 25 points in the third quarter, compared with 19 for Dallas. Their lead increased to 20 points.

This was another important stage of the game because Milwaukee maintained its advantage without needing another 38-point period. The Bucks continued to score while holding Dallas to fewer than 20 points.

The defensive numbers offer useful context. Milwaukee recorded nine blocks over the full game and collected 47 defensive rebounds. Those figures indicate substantial rim protection and defensive rebounding production, although the available data does not specify how many blocks occurred in the third quarter.

Dallas needed to make up ground during this period but instead lost another six points in the overall score comparison.

Fourth Quarter: The Bucks Complete the Win

Milwaukee scored 33 points in the final quarter, while Dallas recorded 29. Both teams produced more points than Dallas had managed in the previous two periods, but the Mavericks could not reduce the gap enough to threaten the final result.

The Bucks’ 33-point finish demonstrated that their offense remained productive late in the game. The Mavericks also improved their scoring output compared with the second and third quarters, but Milwaukee matched and exceeded that production.

The final quarter is particularly useful when evaluating a team’s ability to protect a lead. Milwaukee did not allow Dallas to turn the game into a late comeback, and the final margin reached 24 points.

Key takeaway: Milwaukee won all four quarters. Its advantage was built early, expanded before the fourth quarter, and remained intact until the final buzzer.

Milwaukee Bucks Player Stats and Individual Performances

The Bucks’ individual performances combined scoring, playmaking, rebounding, and defense. Ryan Rollins led the team with 24 points and nine assists, while Kyle Kuzma supplied another 20 points. Jericho Sims led the listed Milwaukee starters with nine rebounds, and Ousmane Dieng provided a productive contribution from the bench.

The available data identifies the leading performers but does not include a complete individual box score with every player’s minutes, field goals, free throws, steals, blocks, and turnovers. The analysis below therefore distinguishes confirmed player highlights from statistics that are available only at team level.

Ryan Rollins: Milwaukee’s Leading Scorer and Playmaker

Ryan Rollins delivered the most prominent statistical performance for Milwaukee, scoring 24 points and recording nine assists. His listed plus-minus was +33, the highest highlighted figure among the players in the supplied data.

Three elements make his performance particularly notable.

First, Rollins led all listed Milwaukee players in scoring. His 24 points accounted for approximately 19.5% of the Bucks’ 123 total points.

Second, his nine assists represented substantial playmaking production. An assist records a pass that directly leads to a made basket under the official scoring rules. It therefore provides information about a player’s contribution beyond personal scoring.

Third, his +33 plus-minus indicates that Milwaukee outscored Dallas by 33 points during the time he was on the court. This does not mean Rollins personally scored 33 more points than his opponents, nor does it mean his individual contribution alone created the team’s 24-point victory.

Plus-minus is influenced by teammates, opponents, lineups, shooting outcomes, and the number of minutes played. Nevertheless, a figure of +33 alongside 24 points and nine assists makes Rollins the central statistical figure in this matchup.

His performance illustrates the value of a guard who can score while also creating opportunities for teammates. When one player contributes to both categories, the defense must account for more than a single offensive threat.

Kyle Kuzma: A Reliable Secondary Scoring Option

Kyle Kuzma scored 20 points for Milwaukee, making him the team’s second-highest scorer among the listed starters.

His total was only four points behind Rollins, giving the Bucks two highlighted starters with at least 20 points. That distribution matters because a team is generally more difficult to defend when its scoring does not depend on one player alone.

If the defense concentrates on the leading scorer, another capable scorer can benefit from the attention. However, the supplied data does not provide Kuzma’s individual shot chart or shooting splits, so it is not possible to determine how many of his points came from three-pointers, midrange attempts, free throws, or shots near the basket.

The reliable conclusion is that Kuzma supplied 20 points within an offense that scored 123 overall. His production helped Milwaukee maintain multiple scoring threats.

Jericho Sims: Rebounding and Interior Presence

Jericho Sims led Milwaukee’s listed starters with nine rebounds.

Rebounding is important because it determines which team gains possession after a missed shot. Defensive rebounds end an opponent’s immediate scoring opportunity, while offensive rebounds create additional chances for the attacking team.

Milwaukee finished with 59 total rebounds, including 47 defensive rebounds and 12 offensive rebounds. Sims’ nine rebounds contributed to that overall production, although the supplied figures do not separate his personal rebounds into offensive and defensive categories.

His contribution is especially relevant when considered alongside Milwaukee’s nine blocks. Both statistics concern activity around the basket, but they measure different things. A block records a defensive deflection of a shot, while a rebound records possession secured after a missed attempt.

Together, the team figures indicate that Milwaukee produced a strong statistical presence in the paint.

AJ Green: A Productive Bench Scorer

AJ Green led Milwaukee’s bench scorers with 17 points.

Bench scoring can be valuable for several reasons. It helps maintain offensive production when starters rest, gives the coaching staff more lineup options, and reduces the pressure on the starting unit to supply nearly all the team’s points.

Green’s 17 points represented approximately 13.8% of Milwaukee’s final total. That is a meaningful contribution in a game in which the Bucks won by 24 points.

The available information does not include Green’s minutes or shooting splits. Consequently, it would be inappropriate to calculate his points per minute or claim that he was especially efficient based solely on his point total.

What can be said with confidence is that Milwaukee received a substantial scoring contribution from the bench, complementing the production of Rollins and Kuzma.

Ousmane Dieng: Rebounding and Playmaking From the Bench

Ousmane Dieng led Milwaukee’s bench players with 10 rebounds and five assists.

His combination of rebounding and passing stands out because the two statistics represent different types of value. Rebounds help a team secure possession, while assists indicate involvement in scoring plays.

Dieng’s 10 rebounds were one more than Sims’ nine rebounds among the listed starters. His five assists also gave Milwaukee another playmaking contributor beyond Rollins.

These figures support the view that Milwaukee’s bench contributed in several ways rather than relying exclusively on points.

However, the supplied information does not provide Dieng’s individual plus-minus, minutes, or shooting efficiency. His full impact cannot be quantified from rebounds and assists alone.

Milwaukee’s Statistical Leaders at a Glance

Statistical Category	Player	Recorded Total
Points	Ryan Rollins	24
Points among other listed starters	Kyle Kuzma	20
Assists	Ryan Rollins	9
Rebounds among listed starters	Jericho Sims	9
Bench points	AJ Green	17
Bench rebounds	Ousmane Dieng	10
Bench assists	Ousmane Dieng	5
Highlighted plus-minus	Ryan Rollins	+33

This table captures the principal Milwaukee performances identified in the supplied data. It should not be interpreted as a complete player leaderboard for every possible statistical category because individual defensive statistics and complete player shooting lines were not supplied.

Dallas Mavericks Player Stats and Individual Performances

Dallas finished with 99 points, 24 fewer than Milwaukee. Despite the defeat, several Mavericks produced individual performances worth examining, particularly Cooper Flagg and Brandon Williams.

Flagg led Dallas’s listed starters with 19 points and 10 rebounds. Williams led the bench with 18 points. Ryan Nembhard recorded four assists, giving Dallas a playmaking contribution from its starting lineup.

These individual totals show that Dallas had productive players, even though the team struggled to match Milwaukee’s overall efficiency.

Cooper Flagg: Dallas’s Leading Starter

Cooper Flagg finished with 19 points and 10 rebounds, recording a double-double.

A double-double occurs when a player reaches at least 10 in two of the five standard statistical categories: points, rebounds, assists, steals, or blocks. Flagg’s combination of scoring and rebounding met that threshold.

His 19 points represented approximately 19.2% of Dallas’s 99-point total. That made him the team’s leading scorer among the listed starters.

His 10 rebounds also represented a meaningful contribution to a Dallas team that collected 50 rebounds overall. Rebounding can help a team compensate for poor shooting by creating additional possessions, but those opportunities must still be converted into points to influence the final result.

Flagg’s performance highlights an important distinction between individual production and team success. A player can record a double-double while his team loses by a substantial margin. Individual statistics describe what a player contributes in particular categories, whereas the final score reflects the combined results of both teams’ possessions.

The available data does not include Flagg’s shooting splits, minutes played, turnovers, or personal plus-minus. His overall efficiency and complete offensive impact therefore cannot be assessed from the supplied figures alone.

Brandon Williams: The Leading Scorer From Dallas’s Bench

Brandon Williams scored 18 points, making him Dallas’s leading bench scorer.

His total was only one point below Flagg’s 19, demonstrating that the Mavericks received a substantial scoring contribution from a reserve player.

Bench scoring is particularly important when a team is trailing. Additional production from substitutes can help maintain offensive pressure while starters rest. However, scoring alone does not establish whether a bench unit performed well defensively or whether its possessions were efficient.

Williams’ 18 points accounted for approximately 18.2% of Dallas’s total. That was a meaningful share of the Mavericks’ offensive production, but it was not enough to close the gap created by Milwaukee’s stronger shooting.

The figures do not establish whether Williams scored primarily through three-pointers, drives, midrange shots, or free throws. His precise shooting efficiency should therefore not be inferred from his points alone.

Ryan Nembhard: Dallas’s Leading Listed Starting Playmaker

Ryan Nembhard recorded four assists, the highest assist total among Dallas’s listed starters.

Assists are a useful way to evaluate a player’s involvement in team offense, but they do not capture every pass that creates an advantage. A pass that forces a defensive rotation, creates an open shot, or sets up a later pass may be tactically valuable without being credited as an assist.

Dallas finished with 18 assists as a team, compared with Milwaukee’s 28. The difference of 10 assists is one of the clearest statistical gaps in the game.

Nembhard’s four assists show that he contributed to Dallas’s playmaking, but the available figures do not establish how many of Milwaukee’s baskets came directly from defensive breakdowns or how the teams organized their half-court offenses.

The broader takeaway is that Dallas generated fewer credited assists overall. That gap, combined with its lower field-goal percentage, suggests that the Mavericks did less with their scoring opportunities than the Bucks.

Dallas’s Other Important Bench Contributions

Dallas also received contributions from players including Dwight Powell, Tyler Smith, Moussa Cisse, John Poulakidas, AJ Johnson, and Marvin Bagley III, all listed among the team’s bench players.

The supplied data specifically identifies Moussa Cisse’s plus-minus as +1. That figure means Dallas outscored Milwaukee by one point during Cisse’s time on the court, according to the plus-minus definition provided.

This is a useful reminder that a player’s plus-minus does not have to match the team’s final result. Dallas lost by 24 points overall, but a player can still finish with a positive plus-minus if the team performs better than its opponent during that player’s minutes.

The available information does not include complete individual statistics for these bench players. It would therefore be misleading to assign them specific point totals, shooting percentages, or defensive contributions that have not been provided.

Dallas’s Statistical Leaders at a Glance

Statistical Category	Player	Recorded Total
Points among listed starters	Cooper Flagg	19
Rebounds among listed starters	Cooper Flagg	10
Assists among listed starters	Ryan Nembhard	4
Bench points	Brandon Williams	18
Highlighted plus-minus	Moussa Cisse	+1

The distinction between listed starters and bench players matters here. The supplied information identifies Dallas’s leading starter and bench scorer, but it does not establish a complete ranking of every player’s performance in every category.

Milwaukee Bucks vs Dallas Mavericks Match Player Stats: Team Comparison

Individual performances explain who produced the most points or rebounds. Team statistics explain why one side won.

Milwaukee finished ahead in shooting percentage, three-point production, assists, total rebounds, defensive rebounds, and blocks. Dallas recorded more steals and offensive rebounds, while both teams made the same number of free throws.

The following table brings those differences together.

Team Statistic	Milwaukee Bucks	Dallas Mavericks
Total points	123	99
Field goals made	41	34
Field-goal attempts	92	96
Field-goal percentage	45%	35%
Three-pointers made	20	10
Three-point attempts	54	36
Three-point percentage	37%	28%
Free throws made	21	21
Free-throw attempts	26	28
Free-throw percentage	81%	75%
Total rebounds	59	50
Offensive rebounds	12	14
Defensive rebounds	47	36
Assists	28	18
Turnovers	16	14
Steals	7	12
Blocks	9	4
Personal fouls	19	19

Percentages are reproduced from the supplied box-score data and rounded to whole numbers.

Field-Goal Efficiency: Milwaukee Made Better Use of Its Attempts

Milwaukee made 41 of 92 field-goal attempts, while Dallas made 34 of 96.

The Bucks therefore made seven more field goals despite taking four fewer shots. Their listed field-goal percentage was 45%, compared with Dallas’s 35%.

This is one of the most important differences in the matchup.

Field-goal percentage measures the proportion of field-goal attempts that result in made baskets. It does not assign extra value to three-pointers, so it should be considered alongside three-point shooting and other scoring statistics.

Even with that limitation, the gap between the two teams is substantial. Milwaukee converted a larger share of its shots and generated more successful field goals with fewer attempts.

For Dallas, the combination of 96 attempts and 34 makes shows that a relatively high volume of shooting did not translate into equivalent scoring production.

The data does not reveal whether missed attempts were heavily contested, rushed, or taken from particular areas of the floor. Those details would require a shot chart or play-by-play review.

Three-Point Shooting: The Biggest Scoring Difference

Milwaukee made 20 three-pointers from 54 attempts, while Dallas made 10 from 36 attempts.

The Bucks therefore made twice as many three-point shots.

Because each successful three-pointer is worth three points, Milwaukee scored 60 points from beyond the arc. Dallas scored 30 points from that distance.

That creates a 30-point difference in three-point scoring, larger than the final 24-point margin.

This does not mean three-point shooting alone explains every aspect of the game. The teams also differed in two-point scoring, free-throw production, and other aspects of play. However, the perimeter scoring gap is a major part of the explanation.

Milwaukee’s 37% three-point percentage was higher than Dallas’s 28%. The Bucks also attempted 18 more three-pointers.

Those two facts must be considered together. Milwaukee did not simply shoot more threes. It made more of them and converted them at a higher rate.

A useful way to evaluate this difference is to distinguish shooting volume from shooting efficiency:

• Volume: Milwaukee attempted 54 three-pointers.
• Conversion: Milwaukee made 20 of those attempts.
• Dallas comparison: The Mavericks attempted 36 and made 10.

The Bucks’ additional makes created a substantial scoring advantage. Dallas would have needed either more successful perimeter shots, better production from two-point range, or greater scoring efficiency in other areas to offset that difference.

Assists: Milwaukee Shared the Offensive Workload

Milwaukee recorded 28 assists, compared with Dallas’s 18.

The difference of 10 assists suggests that the Bucks had more made baskets credited to a teammate’s pass. This is consistent with a team offense that produced more successful field goals and more perimeter scoring.

However, assists are not a complete measure of teamwork. They depend on whether a made basket qualifies as an assist under the official scoring rules. A player may create an excellent scoring opportunity without receiving an assist if the final play does not meet those criteria.

Even with that limitation, the difference is informative.

Milwaukee combined 28 assists with 41 made field goals. Dallas recorded 18 assists with 34 made field goals. The Bucks therefore generated more assisted baskets in absolute terms and had a higher assist total relative to their made field goals.

This pattern is consistent with effective ball movement, although the box score alone cannot establish the exact passing sequences or offensive system used.

Rebounding: Dallas Won the Offensive-Rebound Count

Milwaukee collected 59 rebounds, while Dallas recorded 50.

The Bucks held a nine-rebound advantage overall. Most of that difference came from defensive rebounds, where Milwaukee recorded 47 compared with Dallas’s 36.

Dallas, however, collected 14 offensive rebounds, two more than Milwaukee’s 12.

This distinction matters because total rebounds combine two different types of possession.

Offensive rebounds allow a team to recover its own missed shot and attempt to score again. Defensive rebounds generally end the opponent’s possession after a missed field goal or free throw.

Dallas’s offensive-rebound advantage shows that the Mavericks created opportunities to recover missed shots. It does not prove that they converted those extra opportunities into enough points to change the result.

Milwaukee’s defensive-rebound advantage, meanwhile, indicates that the Bucks collected more rebounds on the defensive end. This helped them secure possession after missed shots and limited Dallas’s overall rebounding advantage.

The lesson is that rebounding should be evaluated by type, not just by the total.

A team can win the offensive-rebound count but still lose the overall rebounding battle if its opponent secures substantially more defensive boards. That is precisely what the supplied figures show here.

Turnovers: Dallas Had Fewer, but Still Lost

Milwaukee recorded 16 turnovers, compared with Dallas’s 14.

Turnovers occur when a team loses possession without completing a field-goal attempt that leads to a rebound. They can result from steals, inaccurate passes, offensive fouls, or other violations.

At first glance, Dallas’s lower turnover total might suggest an advantage. However, the difference was only two possessions, and turnovers do not tell the full story of offensive efficiency.

The Mavericks shot 35% from the field, compared with Milwaukee’s 45%. They also made 10 fewer three-pointers and recorded 10 fewer assists.

Those differences were much larger than the turnover gap.

The game demonstrates why one favorable statistic should not be interpreted in isolation. Dallas protected the ball slightly better by the turnover count, but Milwaukee made substantially better use of its shooting opportunities.

It is also important to avoid assuming that every turnover directly produced points for the opponent. Establishing that relationship would require possession-by-possession data.

Steals: Dallas Created More Defensive Disruptions

Dallas recorded 12 steals, while Milwaukee had seven.

A steal is credited when a defender gains possession from an opponent through a defensive action. Steals can create fast-break opportunities, disrupt offensive rhythm, and force teams to reorganize their possessions.

Dallas’s five-steal advantage is a genuine positive in the box score.

However, the Mavericks still lost by 24 points. Their higher steal total did not compensate for the difference in shooting, assists, rebounding, and blocks.

This is a useful example of the difference between creating defensive events and winning the overall game.

A steal can be valuable, but its ultimate impact depends partly on what happens next. If the resulting possession does not produce a score, the defensive play may not translate into a meaningful change in the scoreboard.

The supplied team statistics do not indicate how many points either team scored directly after turnovers or steals. Any precise claim about transition scoring would therefore require additional evidence.

Blocks: Milwaukee Protected the Rim More Effectively

Milwaukee recorded nine blocks, compared with Dallas’s four.

That five-block difference is a major defensive distinction in the supplied data.

Blocks can discourage opponents from attempting shots near the basket, interrupt scoring opportunities, and sometimes create changes of possession. They do not automatically count as rebounds or steals, and not every blocked shot leads to a missed possession for the defending team.

Nevertheless, nine blocks indicate that Milwaukee recorded substantial shot-blocking production.

When considered alongside 47 defensive rebounds, the figures suggest that the Bucks made it difficult for Dallas to finish possessions efficiently around the basket and then secured many of the resulting defensive rebounds.

The available information does not identify which players recorded each block or where those attempts occurred. It would be inaccurate to assign all nine blocks to a particular Milwaukee player or to claim that every block came near the rim.

Free Throws: Both Teams Made 21

Milwaukee made 21 free throws from 26 attempts, while Dallas made 21 from 28 attempts.

The Bucks had a higher listed free-throw percentage at 81%, compared with Dallas’s 75%. However, both teams made the same number of free throws.

This is an important distinction because it shows that free throws were not the primary source of Milwaukee’s 24-point advantage.

The bigger differences came from field-goal production, particularly three-point shooting, along with the Bucks’ higher assist total and greater defensive-rebound production.

Free-throw percentages can be useful indicators of conversion accuracy, but the number of attempts also matters. In this matchup, Dallas attempted two more free throws without making more of them.

The figures support a clear conclusion: Milwaukee’s scoring advantage was driven more by its field-goal production than by the total number of successful free throws.

Understanding Player Plus-Minus in the Bucks-Mavericks Game

Plus-minus is one of the most misunderstood statistics in basketball. It measures the difference between a team’s points scored and points allowed while a particular player is on the court.

For example, if a team scores 40 points and allows 25 while a player is on the floor, that player records a plus-minus of +15 for that period of play.

The statistic does not measure how many points the player personally scores. It reflects the team’s scoring margin during the player’s time on the court.

Ryan Rollins’s +33 Plus-Minus

Ryan Rollins recorded a highlighted plus-minus of +33, the strongest figure identified among the supplied Milwaukee player statistics.

This means the Bucks outscored Dallas by 33 points during Rollins’s time on the floor. It is an impressive result, particularly when considered alongside his 24 points and nine assists.

However, his +33 figure is not the same as Milwaukee’s final winning margin of 24 points.

The difference exists because plus-minus is calculated over a player’s individual minutes, whereas the final margin includes the entire game. Players enter and leave the court at different times, and each lineup experiences different scoring runs.

Rollins’s figure suggests that Milwaukee performed particularly well during his minutes. It does not establish that he alone caused the team’s victory.

A more complete assessment would combine plus-minus with his minutes, shooting efficiency, turnovers, defensive contributions, and the performance of his teammates during the same stretches.

Moussa Cisse’s +1 Plus-Minus

Moussa Cisse recorded a highlighted plus-minus of +1 for Dallas.

That means the Mavericks outscored Milwaukee by one point during his time on the court. The figure is not inconsistent with Dallas losing the game by 24 points.

A player may spend time on the court during a relatively successful stretch even when the team performs poorly overall. Plus-minus captures the net result of those specific minutes rather than the entire game.

It is also a team-dependent measure. A player can record a positive figure while making a modest individual contribution, or a negative figure while scoring efficiently, depending on how the surrounding lineup performs.

For this reason, Cisse’s +1 should be interpreted as a narrow indicator of lineup results, not definitive proof of his individual effectiveness.

How to Read Plus-Minus Correctly

When evaluating plus-minus, keep three principles in mind:

1. Consider playing time. A player who spends more minutes on the court has more opportunities to experience scoring runs in either direction.
2. Compare it with individual statistics. Points, assists, rebounds, shooting percentages, and turnovers help explain what a player contributed.
3. Avoid treating it as proof of causation. Teammates, opponents, substitutions, and shooting outcomes all influence the number.

For this matchup, Rollins’s combination of scoring, assists, and plus-minus makes his performance especially noteworthy. Cisse’s positive figure offers a different perspective on Dallas’s individual contributions despite the team’s defeat.

Neither number should be interpreted in isolation.

What the Statistics Reveal About Milwaukee’s Winning Performance

The most useful analysis connects several statistics rather than treating every category as equally important.

Milwaukee’s victory was built on superior shooting, stronger passing production, and a substantial defensive-rebounding advantage. These strengths outweighed Dallas’s higher steal count and small advantage in offensive rebounds.

1. Milwaukee Created a Major Perimeter Scoring Advantage

The Bucks made 20 three-pointers, while Dallas made 10.

That difference translated into 30 additional points from three-point baskets before accounting for the teams’ production from other scoring methods.

The Bucks also converted 37% of their three-point attempts, compared with 28% for the Mavericks.

This combination of volume and accuracy was particularly damaging for Dallas. Milwaukee did not depend exclusively on making a small number of difficult shots. It attempted 54 three-pointers and converted 20 of them.

For analysts, this is a reminder to evaluate three-point shooting through both attempts and makes. A team may have a high three-point percentage on a small number of attempts without generating enough total points to create a large advantage.

Milwaukee had both a substantial volume and a higher conversion rate.

2. The Bucks Converted More Field-Goal Attempts

Milwaukee made seven more field goals despite attempting four fewer shots.

The difference in field-goal percentage was 10 percentage points when using the rounded figures supplied for the game.

This is important because missed shots represent scoring opportunities that were not converted. Although offensive rebounds can extend possessions, they do not guarantee that the next attempt will be successful.

Dallas’s 35% field-goal percentage indicates that the team struggled to convert its attempts into baskets. The available figures do not identify whether that difficulty came from defensive pressure, shot selection, poor shooting, or a combination of factors.

What can be established is that Milwaukee was more successful at turning its field-goal attempts into points.

3. Passing Production Favored Milwaukee

The Bucks recorded 28 assists, compared with Dallas’s 18.

This difference fits the wider offensive picture. Milwaukee scored more points, made more field goals, and made twice as many three-pointers.

Assists do not tell the whole story of offensive quality, but they provide a useful measure of how often made baskets were directly linked to a teammate’s pass.

The figures support the conclusion that Milwaukee generated more assisted scoring. They do not, by themselves, reveal whether the Bucks used more pick-and-roll plays, isolation possessions, cuts, or other specific offensive actions.

Those tactical details would require a video review or play-by-play analysis.

4. Defensive Rebounding Helped Milwaukee Control Possessions

Milwaukee collected 47 defensive rebounds, while Dallas recorded 36.

This 11-rebound difference helped Milwaukee finish more defensive possessions with the ball.

Dallas actually recorded two more offensive rebounds, so the Mavericks were not completely unsuccessful at recovering their own misses. However, the overall rebounding count favored Milwaukee by nine.

The distinction shows why rebound totals need context. Offensive rebounds can extend attacks, but defensive rebounds are equally important because they end an opponent’s immediate opportunity to score.

Milwaukee’s higher defensive-rebound total was one of the clearest signs of its control over the defensive glass.

5. Milwaukee Produced More Blocks Without Winning Every Defensive Category

The Bucks recorded nine blocks and seven steals. Dallas recorded four blocks and 12 steals.

This comparison shows that the teams generated different types of defensive events.

Dallas was more successful in the steals category, while Milwaukee recorded more blocks. The Bucks also collected more defensive rebounds and allowed fewer points.

The most reasonable interpretation is that Milwaukee’s defensive performance was more effective overall in this particular game, even though Dallas led in steals.

A complete defensive evaluation would require additional information, including opponent shooting by location, contested shots, defensive assignments, and points allowed per possession.

The box score establishes the statistical differences, but it does not provide enough information to attribute every defensive outcome to a particular player or tactical scheme.

What Went Wrong for Dallas?

Dallas’s defeat cannot be explained by one statistic alone. Its shooting difficulties, lower assist total, and defensive-rebounding deficit collectively created a difficult path to victory.

Poor Shooting Efficiency Increased the Scoring Challenge

Dallas made 34 of 96 field-goal attempts. Milwaukee made 41 of 92.

The Mavericks attempted more shots but made fewer baskets. That is a particularly important disadvantage when facing an opponent that is converting shots at a higher rate.

Dallas’s three-point shooting made the problem more pronounced. Ten successful three-pointers produced 30 points from beyond the arc, while Milwaukee’s 20 successful attempts produced 60.

The 30-point difference in three-point scoring exceeded the final margin of defeat. That makes perimeter shooting the most prominent scoring distinction in the team statistics.

However, the comparison should not be interpreted as proof that Dallas should simply have attempted more three-pointers. The Mavericks’ percentage was already lower, and additional attempts would not necessarily have resulted in additional makes.

A better analysis would examine shot quality, shooting location, defensive pressure, and the expected value of each attempt. Those details are not included in the supplied figures.

Dallas Did Not Generate as Many Assists

The Mavericks recorded 18 assists, 10 fewer than Milwaukee.

This difference is consistent with the gap in made field goals and points. Dallas produced fewer successful baskets overall and had fewer baskets credited to teammate passes.

It is possible for a team to generate effective offense without a high assist total, particularly when individual players create shots through isolation or drives. Therefore, a low assist total should not automatically be interpreted as selfish play or poor chemistry.

The figures do, however, show that Milwaukee had the stronger combination of assisted scoring and shooting production in this matchup.

The Defensive Glass Was a Weak Point

Dallas recorded 36 defensive rebounds, compared with Milwaukee’s 47.

This difference suggests that Milwaukee collected more defensive rebounds overall. Securing the ball after a missed shot limits an opponent’s opportunity to extend the possession.

Dallas’s 14 offensive rebounds were a positive figure, but they did not compensate for Milwaukee’s greater total and defensive-rebounding production.

A more detailed review would examine each team’s offensive-rebound percentage, which measures the share of available offensive rebounds a team collects. Calculating that percentage accurately requires the relevant rebound opportunities, not simply the raw offensive-rebound totals.

The available data is sufficient to compare the teams’ recorded totals, but not to establish every aspect of their rebounding efficiency.

Individual Scoring Could Not Offset Milwaukee’s Team Production

Flagg scored 19 points, and Williams added 18. Those were meaningful contributions, but Milwaukee had Rollins at 24 points, Kuzma at 20, and Green at 17.

The Bucks therefore had three highlighted scorers who each reached at least 17 points, while Dallas’s leading listed starter and bench scorer recorded 19 and 18, respectively.

This comparison helps explain the importance of contributions across the lineup. Milwaukee received scoring from its leading guard, another starting scorer, and a bench player.

The supplied information does not include every player’s complete scoring total, so these figures should not be treated as a comprehensive comparison of every rotation member. Nevertheless, the identified performances demonstrate that Milwaukee had several productive scoring options.

How to Analyze a Basketball Box Score Like an Expert

A box score contains more information than the final score, but its value depends on how the numbers are interpreted.

The following process can help readers evaluate future NBA games without drawing conclusions from isolated statistics.

Step 1: Start With the Final Score and Quarter Progression

Identify the winning team, winning margin, and scoring pattern across all four quarters.

Ask whether the game was close throughout, whether one team built an early lead, or whether the advantage developed late.

In this matchup, Milwaukee won every quarter. That establishes that the result was supported by consistent scoring advantages rather than a single winning period.

Step 2: Compare Shooting Percentage and Scoring Volume

Look at field goals made and attempted, then examine three-point shooting and free throws.

These figures answer different questions:

• Field-goal percentage shows how often a team converted its field-goal attempts.
• Three-point statistics show how effectively a team scored from beyond the arc.
• Free-throw statistics show how many points came from the foul line and how accurately those attempts were converted.

In the Bucks-Mavericks game, Milwaukee led in field-goal percentage and three-point production. Both teams made 21 free throws.

This makes perimeter scoring and overall field-goal efficiency more central to the result than free-throw volume.

Step 3: Examine Rebounds by Type

Do not stop at total rebounds.

Separate offensive rebounds from defensive rebounds to understand whether a team extended its own possessions or secured the ball after the opponent missed.

Milwaukee led total rebounds 59-50 and defensive rebounds 47-36. Dallas led offensive rebounds 14-12.

That combination gives a clearer picture than the total alone.

Step 4: Evaluate Playmaking and Ball Security Together

Compare assists and turnovers.

Assists help describe the creation of successful scoring opportunities, while turnovers show how often a team lost possession without completing a shot.

Milwaukee had 28 assists and 16 turnovers. Dallas had 18 assists and 14 turnovers.

Dallas committed two fewer turnovers, but Milwaukee recorded 10 more assists. This is a useful example of why both figures should be examined together rather than judging offensive quality by turnovers alone.

Step 5: Review Defensive Statistics in Context

Steals, blocks, and rebounds provide different information about defensive performance.

A steal indicates that a defender gained possession from an opponent. A block indicates that a shot was deflected. A defensive rebound indicates that the defending team secured the ball after a missed attempt.

In this game, Dallas led in steals, while Milwaukee led in blocks and defensive rebounds.

The combined figures favor Milwaukee’s overall defensive results, but a complete analysis would also examine shooting allowed and points conceded during different lineups.

Step 6: Use Individual Statistics to Explain Team Results

Identify each team’s leading scorer, rebounder, and playmaker. Then examine whether the team’s statistical strengths align with those individual performances.

Rollins led Milwaukee in scoring and assists. Flagg led Dallas’s listed starters in scoring and rebounding. Green supplied 17 points from Milwaukee’s bench, while Williams led Dallas’s bench with 18.

These details help readers understand the individual contributions behind the final result.

However, avoid assuming that the leading scorer necessarily played the best overall game. A complete assessment should consider efficiency, defense, turnovers, playing time, and the player’s role.

Step 7: Separate Confirmed Facts From Interpretation

This final step is essential.

The box score confirms that Milwaukee made 20 three-pointers and won by 24 points. It does not, by itself, confirm that Dallas had poor chemistry, that one coach made a specific tactical mistake, or that a particular player was responsible for every defensive breakdown.

Reliable basketball analysis distinguishes observed statistics from explanations that require additional evidence.

That distinction makes an article more useful to readers because it avoids presenting speculation as established fact.

Historical Context: The Season Series Between Milwaukee and Dallas

The supplied matchup information indicates that Milwaukee led the season series 2-0 following the April 1, 2026, game.

The previous matchup took place on November 11, when Milwaukee defeated Dallas 116-114. That game was much closer than the April meeting, with the Bucks winning by just two points.

A second scheduled matchup on January 26 was postponed, according to the supplied data. The April 1 game therefore provides the next listed result in the season series.

Comparing the Two Recorded Results

Matchup	Milwaukee Bucks	Dallas Mavericks	Winning Margin
November 11	116	114	Milwaukee by 2
April 1, 2026	123	99	Milwaukee by 24

The comparison reveals a significant difference in the final margins.

In November, Dallas stayed close enough to make the game a two-point contest. In April, Milwaukee won by 24 points.

The Bucks scored seven more points in the April matchup than in the November meeting. Dallas, meanwhile, scored 15 fewer points.

These differences help explain the larger margin in April, although the scores alone cannot establish why the teams performed differently. Player availability, lineups, shooting performance, and other game conditions would need to be examined before drawing broader conclusions about changes between the meetings.

The season-series record is useful context, but two results are not enough to establish long-term superiority between the franchises. A wider evaluation would require more games and information about the teams’ performances throughout the season.

Roster Information and Player Availability

The supplied starting lineups and bench lists identify the players associated with the April 1 matchup.

Dallas Mavericks Listed Starters

• Khris Middleton
• Daniel Gafford
• Cooper Flagg
• Max Christie
• Ryan Nembhard

The listed Dallas bench included Dwight Powell, Tyler Smith, Moussa Cisse, Brandon Williams, John Poulakidas, AJ Johnson, and Marvin Bagley III.

Milwaukee Bucks Listed Starters

• Kyle Kuzma
• Myles Turner
• Jericho Sims
• Gary Trent Jr.
• Ryan Rollins

The listed Milwaukee bench included Taurean Prince, Pete Nance, Alex Antetokounmpo, Ousmane Dieng, AJ Green, and Andre Jackson Jr.

These lists establish the roster information provided for the game. They do not include complete individual statistics for every player.

The supplied data also notes that one player was listed as inactive with a left-shoulder issue. Because the player is not identified in that note, it would be inappropriate to attribute the designation to a specific individual.

Player availability can influence basketball analysis, particularly when a missing player changes a team’s rotation or removes a major scoring option. However, an availability note should not be used to explain the final result unless the player’s identity, status, and likely role are established.

For the same reason, the listed starting lineups should be treated as supplied game data rather than evidence of any broader roster situation outside this matchup.

Important Statistical Limitations to Keep in Mind

A strong box-score analysis explains what the numbers establish while acknowledging what they cannot prove.

The supplied statistics provide a detailed comparison of the teams, but some individual performance measures are missing.

Individual Shooting Percentages Are Not Fully Available

The team field-goal, three-point, and free-throw totals are provided. However, the individual shooting splits for Rollins, Kuzma, Flagg, Williams, and the other players are not included.

As a result, it is not possible to calculate each player’s true shooting percentage or effective field-goal percentage accurately.

Effective field-goal percentage adjusts field-goal percentage to account for the extra value of three-pointers. True shooting percentage incorporates field goals, three-pointers, and free throws into a broader estimate of scoring efficiency.

Both measures can be useful, but they require the relevant individual shooting data.

Playing Time Is Not Included

Minutes played are necessary for evaluating how much a player contributed relative to the time spent on the court.

For example, 20 points in 20 minutes represents a different scoring rate from 20 points in 38 minutes. Neither figure automatically proves superior overall performance, but playing time provides essential context.

Because individual minutes are not supplied here, the players’ points per minute and other playing-time-adjusted statistics cannot be calculated reliably.

Advanced Defensive Metrics Are Missing

Steals, blocks, and rebounds provide useful defensive information, but they do not capture every aspect of defense.

A player can force a difficult shot without recording a steal or block. Another player may make a rotation that prevents an open basket without receiving credit in the traditional box score.

Defensive rating, matchup data, opponent shooting percentages, and video review can provide additional context. Those measures are not included in the supplied statistics.

The Box Score Cannot Explain Every Coaching Decision

The scoring progression and team totals establish the statistical outcome. They do not identify every offensive set, defensive adjustment, substitution decision, or timeout strategy.

A tactical explanation should be supported by play-by-play data or game footage rather than invented to make the article sound more authoritative.

This distinction is important for readers who want a trustworthy analysis rather than a collection of confident but unsupported claims.

Frequently Asked Questions

1. What was the final score of the Milwaukee Bucks vs Dallas Mavericks game on April 1, 2026?

The Milwaukee Bucks defeated the Dallas Mavericks 123-99 at Fiserv Forum in Milwaukee, Wisconsin. Milwaukee won by 24 points after outscoring Dallas in all four quarters.

2. Who was the top scorer in the Bucks vs Mavericks matchup?

Ryan Rollins led Milwaukee with 24 points. Kyle Kuzma added 20 points, while Cooper Flagg was Dallas’s leading listed starter with 19 points. Brandon Williams led the Mavericks’ bench with 18 points.

3. How many points and rebounds did Cooper Flagg record?

Cooper Flagg recorded 19 points and 10 rebounds, according to the supplied game statistics. Those totals gave him a double-double, meaning he reached at least 10 in two statistical categories.

4. Which team had better three-point shooting?

Milwaukee had the stronger three-point performance. The Bucks made 20 of 54 attempts, approximately 37%, while Dallas made 10 of 36 attempts, approximately 28%. Milwaukee scored 60 points from three-pointers, compared with Dallas’s 30.

5. How many assists did Ryan Rollins record?

Ryan Rollins recorded nine assists, the highest individual assist total highlighted in the supplied data. Milwaukee finished with 28 team assists, compared with Dallas’s 18.

6. What was Ryan Rollins’s plus-minus in the game?

Ryan Rollins recorded a plus-minus of +33. This means Milwaukee outscored Dallas by 33 points during his time on the court. It does not mean he personally scored 33 points more than the opposing team or that his individual contribution alone determined the final result.

Conclusion

The April 1, 2026, meeting between Milwaukee and Dallas ended in a 123-99 victory for the Bucks, with the statistical breakdown revealing several clear reasons for the result.

Milwaukee’s three-point shooting was the most prominent scoring advantage. The Bucks made 20 three-pointers, twice Dallas’s total of 10, and finished with a 45% field-goal percentage compared with the Mavericks’ 35%.

Ryan Rollins led Milwaukee with 24 points and nine assists, while Kyle Kuzma contributed 20 points. AJ Green added 17 points from the bench, and Ousmane Dieng recorded 10 rebounds and five assists.

For Dallas, Cooper Flagg recorded 19 points and 10 rebounds, while Brandon Williams contributed 18 points off the bench. The Mavericks also recorded more steals and offensive rebounds, demonstrating that they had some positive statistical results despite the defeat.

The decisive differences were Milwaukee’s shooting efficiency, 28 assists, 47 defensive rebounds, and nine blocks. These strengths outweighed Dallas’s smaller advantages in steals and offensive rebounds.

The game also illustrates why individual statistics should be evaluated in context. Rollins’s +33 plus-minus highlights Milwaukee’s strong results during his minutes, but no single statistic fully explains a team victory. Shooting, playmaking, rebounding, defense, and lineup performance all contribute to the final outcome.

Ultimately, the numbers show that Milwaukee created a more effective overall scoring performance and maintained its advantage throughout the game. Dallas produced several noteworthy individual performances, but its lower shooting accuracy and smaller assist total made it difficult to keep pace with the Bucks.