This article walks through why the San Antonio Spurs lost Game 5 to the New Orleans Pelicans using the official box score, play-by-play, and shot chart as primary evidence. The goal is to give a clear, reproducible explanation of the decisive possessions and the season-context guidance you should use before updating predictions. You will find a short summary, a box-score decomposition, a play-by-play walkthrough of late-game swings, a shot-chart inspection, and practical steps to separate noise from signal when updating a spurs pelicans prediction.

Spurs turnovers in late possessions directly led to Pelicans transition points that swung the game.

Pelicans offensive rebounds and free-throw chances extended scoring runs at key moments.

Shot-chart clusters show New Orleans converted in high-value areas while San Antonio missed in the same zones.

Quick summary: what happened in Game 5 and why it matters

Final score and immediate takeaways

The New Orleans Pelicans beat the San Antonio Spurs 104-95 in San Antonio on January 25, 2026, a result shown in the official box score and game page, and that final margin is the starting point for a possession and efficiency breakdown Basketball-Reference box score, and the NBA box score NBA box score.

Directionally, three proximate causes stand out in the box score and play-by-play: a spike in Spurs turnovers that led to transition points, offensive rebound and second-chance differentials that extended a few Pelicans runs, and location-based shooting advantages for New Orleans late in the game visible on the shot chart NBA game page. For an alternate game page view see the NBA game center NBA game center.

Those three elements combined to produce the nine-point final margin, and the immediate implication for short-term forecasting is modest: treat this game as evidence of specific matchup frictions but weight season-level profiles when adjusting a spurs pelicans prediction.

Practice evidence-based forecasting with FundedPlays Challenges

Track game-level evidence like turnovers, offensive rebounds, and late-game lineups to improve short-term forecasts, and consider practicing disciplined prediction techniques on a funded sports prediction challenge platform to test adjustments without real-money stakes.

Explore FundedPlays Challenges

How this single game fits into the broader season context

This result is a useful data point but not a definitive signal by itself; use the teams season profiles to separate repeatable edges from one-off variance when updating models Spurs season page.

For short-term picks, prioritize rate stats that are stable across the season such as turnover percentage and offensive rebounding rate rather than single-game shooting percentages.

Keeping the evidence from this game in the model is valuable, but do not overweight isolated shooting swings when you update a spurs pelicans prediction.

Box score decomposition: possessions, turnovers, rebounds and free throws

How possessions are estimated from box score categories

To decompose the margin you start by converting the box score into possession estimates using a standard approximation, where possessions equal field goal attempts plus turnovers plus free-throw attempts times a conversion factor less offensive rebounds in some formulas; the official box score provides the raw fields needed for that computation Basketball-Reference box score.

Using those fields clarifies whether the Spurs lost because they had fewer possessions, converted at a lower rate, or both in the decisive stretches.

In this game, turnovers created clear possession swings that favored New Orleans, while offensive rebounding and free-throw attempts gave the Pelicans extra scoring chances at key moments according to the official box score Basketball-Reference box score.

For a simple inline example, map a late-quarter Spurs turnover to a Pelicans fast break that appears on the play-by-play and then count that as an immediate possession and likely higher-quality shot, widening the effective scoring gap.

Quarter splits in the box score show when those advantages clustered, allowing you to attribute the margin to specific periods rather than aggregate season differences.

Minimalist annotated shot chart for spurs pelicans prediction showing Pelicans rim make clusters and late game three point makes on a dark branded court background

The official play-by-play shows the possession-by-possession sequence in the fourth quarter where a short Spurs scoring drought coincided with two Pelicans runs that reversed control; those sequences are traceable to specific possessions and can be followed in the game log Play-by-play log.

One run began after a turnover and a timeout, and the Pelicans converted the following possessions into free throws and high-efficiency attempts, which is visible in the minute-by-minute play-by-play entries.

Why did the Spurs lose Game 5?

The Spurs lost because turnovers created transition points, the Pelicans gained extra possessions through offensive rebounds and free throws, and New Orleans hit high-value shots late when matchups and rotations favored them; combine those single-game findings with season profiles before adjusting predictions.

Do you want to step through the possession that produced the first swing in the fourth quarter by following the play-by-play entry where a turnover led directly to two Pelicans points and a substitution pattern change?

The role of timeouts and lineup changes in the decisive stretch

Timeouts and immediate lineup adjustments preceded several sequences that favored New Orleans, with the play-by-play marking substitutions that changed matchup balance in ways the Spurs did not fully correct before the next possession, according to the play-by-play record Play-by-play log. The ESPN gamecast also provides a complementary play-by-play view ESPN play-by-play.

Those snapshots are useful because they isolate whether the issue was execution on a given possession or a coaching match-up decision that produced repeated problems.

Shot-chart evidence: where the buckets came and where they did not

Location-based efficiency: rim, midrange, three-point

The shot chart for this contest shows the spatial pattern of makes and misses, which makes it straightforward to see whether New Orleans generated points predominantly at the rim or from distance; consult the contest shot chart to confirm location-based claims Shot chart.

In practice, the Pelicans converted a number of efficient rim attempts and hit enough perimeter shots late to sustain a run, while the Spurs had clusters of misses in high-value zones during the same stretches.

Minimalist 2D vector timeline with circular play nodes substitution markers and a highlighted decisive stretch illustrating a spurs pelicans prediction

Mapping those location outcomes to defensive assignments suggests the Spurs struggled to consistently create rim pressure without conceding open perimeter looks that the Pelicans capitalized on, a pattern that the play-by-play and shot map make visible together Shot chart.

Turnovers, transition points, and how New Orleans converted them

Turnover timing and the resulting easy points

Spurs turnovers in key moments led directly to Pelicans transition opportunities and a higher conversion rate on those possessions; the box score and play-by-play together allow you to map those turnovers to immediate scoring outcomes Basketball-Reference box score.

Late-game turnovers are worth extra attention because they are higher-leverage events; the play-by-play identifies when those miscues happened and what the Pelicans did next to turn them into points Play-by-play log.

Funded Plays Challenges

Explore FundedPlays Challenges

Transition scoring rates compared to half-court possessions

Comparing the Pelicans transition conversion rate after Spurs turnovers to their half-court efficiency in the same game shows whether the margin came mostly from easy baskets or from sustained half-court advantages; the play-by-play entries provide the necessary sequence data for that check Play-by-play log.

That differentiation matters for prediction because transition points driven by turnovers are often repeatable if a defensive pattern persists, while a single hot shooting night from distance is more likely to regress.

Coaching choices, rotations and substitution patterns that mattered

Which lineups produced the biggest positive or negative runs

Play-by-play substitution markers and minute allocations in the box score show which lineups were on the court during the Spurs scoring droughts and Pelicans runs, allowing direct attribution of positive and negative stretches to specific groupings Play-by-play log.

Identifying which small lineup combinations produced defensive breakdowns or offensive stagnation clarifies whether the issue is personnel fit or execution in tight minutes.

Timeout usage and in-game adjustments

Timeouts were used before and after some of the decisive possessions, and the play-by-play shows whether the immediate adjustments improved matchups; several mid-quarter timeouts preceded lineup changes that the Pelicans exploited in subsequent possessions Play-by-play log.

Frame these choices as tradeoffs because coaches must balance matchup response with rotation balance and fatigue management.

What this game means for short-term predictions and how to separate noise from signal

Use team season profiles to contextualize single-game variance

To avoid overreacting, combine the single-game takeaways with each team season profile, especially pace, turnover rate, offensive rebounding rate, and shooting splits, which are available on the season pages and help isolate long-term tendencies from one-night variance Pelicans season page.

Reproduce the main checks from box score and logs

Turnover timing
Offensive rebound rate
Shot location balance

Use the referenced box score and play-by-play to fill items

Which metrics to overweight when adjusting a prediction

When tuning a short-term spurs pelicans prediction, overweight stable rate stats such as turnover percentage and offensive rebounding rate and underweight single-game shooting rates that are known to revert toward season means. See how Funded Plays evaluations work here for related methodology.

Practical rule: if a team shows persistent turnover problems across multiple recent games and the matchup creates pressure, give that factor more weight than a single game three-point hot streak.

Player-level takeaways: who gained and who lost matchup advantage

Leading contributors by role

The box score identifies the players who produced the most direct value in scoring, rebounding, and playmaking, and the play-by-play shows which contributors were involved in the decisive sequences, so tie individual stat lines to the possessions they influenced in the logs Basketball-Reference box score.

Focus on role impact such as primary ball-handlers who turned the ball over in transition or interior defenders who allowed repeated rim entries rather than on isolated shot totals.

Matchup winners and losers

The log highlights which role players shifted matchup advantage when they entered the game, and those shifts often align with the runs that produced the final margin according to the play-by-play entries Play-by-play log.

Use that information to track whether a particular matchup advantage is likely to persist in the next meeting based on projected minutes and likely matchups.

Bench impact and depth: how second units influenced the margin

Bench scoring and defensive impact

Compare bench minutes and scoring contributions in the box score to see whether the Spurs second unit was outscored or failed to generate stops during pivotal runs; the box score provides the minute and scoring breakdowns needed for that comparison Basketball-Reference box score.

When bench rotations produce net negative runs, the starter-minutes allocation that follows can compound the problem late in the game.

Rotational depth differences exposed

Play-by-play substitution patterns show whether the Spurs shortened the rotation or left certain matchups unaddressed, which can reveal depth disadvantages that matter for back-to-back scheduling and the next meeting Play-by-play log.

If bench minutes are limited and the opponent exploits that with productive second-unit scoring, expect that to be a repeatable concern until rotation minutes change.

Statistical decomposition: possession efficiency and rate stats to watch

Possessions, points per possession and conversion rates

Compute possessions from the box score fields and then derive points per possession for each team; that rate decomposition isolates whether the margin came from fewer possessions or lower conversion on similar volume, and you can find the raw numbers in the official box score Basketball-Reference box score.

Step 1, collect FGA, TO, FTA, ORB from the box score. Step 2, estimate possessions with a standard formula. Step 3, divide points by possessions to get points per possession for both teams and compare the difference.

Which rate stats best explain the margin

Turnover percentage, offensive rebound rate, and free-throw rate typically explain short-term swings; check those rates before you change your model priors for future spurs pelicans matchups Shot chart.

A practical check is to recompute these rates across the last three games to see if Game 5 is consistent with a trend or an outlier.

Common analysis mistakes and how to avoid them when reading a single game

Confusing variance for trend

Avoid treating one game shooting or a single hot stretch as a definitive trend; confirm that similar patterns appear in multiple games or in season profiles before making a large adjustment to a spurs pelicans prediction Spurs season page.

Use small-sample diagnostics such as rolling three-game averages to reduce false signals caused by random variation.

Overweighting isolated statistics

Do not overweight raw counts like points in garbage time or single-game rebound totals without checking pace and opponent context; cross-check with the play-by-play and season rates to ensure you are not misled by low-leverage counting stats Pelicans season page.

Simple cross-checks prevent changing a prediction based on non-repeatable events.

Practical scenarios and what to watch in the next meeting

Short list of actionable indicators to monitor

Watch these indicators before the next Spurs versus Pelicans game: turnover trends over the last three games, offensive rebound rate for both sides, minutes for the primary matchup players, three-point location splits from recent contests, and recent substitution patterns in late quarters as shown in play-by-play logs Play-by-play log.

If a key player is trending toward higher turnover rates or the Pelicans keep generating offensive rebounds against similar frontcourts, those are repeatable edges to fold into a short-term model.

How to adjust a short-term prediction before tipoff

Use a simple checklist: confirm rotation and health, check three-game rolling rates for turnovers and offensive rebounds, and inspect the most recent shot charts for persistent location advantages; if two or more indicators favor one team, shift your model slightly rather than making a large move. The article checklist is available in the blog index simple checklist.

When in doubt, maintain the prior and await confirmation from subsequent games.

Conclusion: clean recap and how to adjust your spurs pelicans prediction

One-paragraph recap tied to the evidence

Game 5 in San Antonio ended 104-95 for New Orleans, and the decisive factors supported by the box score, play-by-play, and shot chart were Spurs turnovers that led to transition points, Pelicans offensive rebounds and free-throw chances that extended runs, and location-based shooting advantages late in the game visible on the shot map Basketball-Reference box score.

Final disciplined guidance for short-term prediction adjustments

Adjust a spurs pelicans prediction by weighting repeatable rate stats such as turnover percentage and offensive rebounding more than isolated shooting outcomes, and use the short checklist from this article to keep updates proportional to the evidence rather than to a single result Spurs season page.

What were the main statistical reasons the Spurs lost Game 5?

Turnovers that led to transition points, offensive rebound differentials that gave the Pelicans extra chances, and location-based shooting advantages late in the game were the main factors.

Should I change my next Spurs vs Pelicans pick based on this single game?

Not drastically; use this game to update priors for repeatable rates like turnover percentage and offensive rebound rate, and avoid overreacting to single-game shooting swings.

Where can I verify the sequences and stats used in this breakdown?

Verify the official box score, play-by-play log, and shot chart from the referenced game sources to reproduce the checks.

Use the included checklist and references to reproduce the core checks yourself before making model adjustments. Treat this game as informative but not dispositive; confirm trends over multiple meetings before making sizeable prediction changes.