How Starting Pitchers Are Evaluated Before a Game

Why Starting Pitching Matters So Much

In modern baseball, starting pitchers typically face the opposing lineup two or three times through the order. That means they control roughly 50-70% of the game's defensive action. The quality of the starting pitcher affects how many runs the opposing team scores, which innings the game becomes competitive, and when the bullpen enters the picture.

A dominant starter can effectively shorten the game by keeping the opposing offense off balance. A struggling starter can put his team in a hole before the bullpen is ready to contribute. This leverage is why starting pitcher matchups carry so much weight in game predictions.

But evaluating starters is not as simple as looking at their ERA or win-loss record. Those numbers reflect both skill and circumstance. To predict future performance, you need to separate what the pitcher controls from what he does not.

Skill Versus Recent Results

One of the most common mistakes in pitcher evaluation is overweighting recent results. A pitcher who has given up 12 runs in his last two starts looks terrible on the surface. But the underlying data might tell a different story.

When Bad Outings Are Misleading

Consider a pitcher whose recent starts show an elevated ERA but whose peripheral stats remain strong. If his strikeout rate, walk rate, and ground ball rate are all consistent with his career norms, the poor results may be due to factors outside his control. Perhaps he faced a string of elite offenses. Perhaps his defense committed errors behind him. Perhaps several soft contact balls found holes in the infield.

In these cases, the poor results are more likely to be noise than signal. A predictive model would give less weight to the recent ERA and more weight to the underlying skill indicators.

When Good Outings Are Misleading

The opposite scenario is equally important. A pitcher who has posted a 1.50 ERA over his last five starts looks untouchable. But if his strikeout rate has declined, his walk rate has increased, or his exit velocity allowed has spiked, the good results may not continue. Sometimes pitchers get lucky with sequencing, where baserunners are stranded at unusually high rates. Sometimes defense makes extraordinary plays. These factors tend to even out over time.

The predictive approach is to trust the underlying metrics more than the headline numbers. For more on which metrics are most predictive, see What Metrics Matter Most in MLB Predictions.

Pitch Mix and Arsenal Analysis

Every starting pitcher has a unique arsenal of pitches. Understanding how a pitcher uses these pitches, and how they match up against the opposing lineup, adds significant value to pre-game evaluation.

Primary and Secondary Offerings

Most pitchers rely on one or two primary pitches that they throw the majority of the time. A fastball-slider pitcher attacks hitters differently than a sinker-changeup pitcher. The movement profile, velocity, and location patterns of these pitches determine how effective they are against different types of hitters.

Evaluating a starter means understanding not just that he has a slider, but how effective that slider is. What is its spin rate? What is its horizontal and vertical movement? How often does it generate swings and misses? These details matter for matchup analysis.

Platoon Considerations

Most pitchers perform differently against left-handed and right-handed hitters. A right-handed pitcher with a devastating slider might dominate same-side hitters but struggle against lefties who can see the spin better. Conversely, a pitcher with an elite changeup might neutralize opposite-handed hitters but be vulnerable to same-side power.

Before a game, evaluating the opposing lineup's handedness composition helps assess how well the starter's arsenal matches up. A lineup stacked with left-handed hitters facing a right-hander with platoon issues is a different situation than one with a balanced lineup.

Matchup Context

No pitcher performs in a vacuum. The opposing lineup, the ballpark, and the game situation all affect expected performance.

Opposing Lineup Quality

Some lineups are elite. Others are replacement-level. Facing the 2024 Dodgers lineup is not the same as facing the 2024 Athletics lineup. Adjusting expectations based on opponent quality is essential for accurate prediction. A starter who has posted great numbers against weak competition may struggle when facing a top offense, even if his stuff remains the same.

Ballpark Effects

Park factors affect pitching outcomes significantly. A fly ball pitcher in Coors Field faces different conditions than the same pitcher in Oracle Park. Home run rates, hit rates, and run totals all vary by stadium. A thorough pre-game evaluation accounts for where the game is being played and how the park tends to affect the type of pitches the starter throws.

Times Through the Order

Research has consistently shown that pitchers perform worse the third time through the lineup. Hitters adjust. They recognize pitch patterns, sit on certain locations, and time up velocity. Starters who dominate the first two times through may struggle when facing the lineup for the third pass. This is one reason bullpen usage has increased in modern baseball.

Rest, Workload, and Scheduling

Physical factors affect pitcher performance in ways that are sometimes overlooked. Understanding rest patterns and workload history adds context to any evaluation.

Days of Rest

Most starting pitchers work on four or five days of rest. Extra rest can sometimes improve performance, particularly for pitchers coming off heavy workloads. Short rest, while rare for starters, tends to degrade performance. The arm needs time to recover between outings.

Seasonal Workload

Pitchers who have thrown significantly more innings than usual by a certain point in the season may experience fatigue effects. This is especially relevant in the second half of the season and into October. A pitcher who has exceeded his career-high innings total by August is a different evaluation than one operating well within his normal workload.

Recent Pitch Counts

A starter coming off a 120-pitch complete game will not be fully recovered on regular rest. Similarly, a pitcher who has averaged 95+ pitches over his last several starts may show signs of wear. Pitch count history provides context for how fresh a pitcher is likely to be.

Putting It All Together

Evaluating a starting pitcher before a game requires synthesizing multiple streams of information. The process might look like this:

First, examine the underlying skill metrics. Is the pitcher's strikeout rate, walk rate, and ground ball rate consistent with past performance? Are there signs of improvement or decline?

Second, consider the matchup context. How does the pitcher's arsenal match up against this specific lineup? Are there platoon advantages or disadvantages? What about the ballpark?

Third, account for physical factors. Is the pitcher on normal rest? Has his workload been manageable? Are there any injury concerns or velocity changes?

Fourth, weight recent performance appropriately. Strong or weak recent outings may be meaningful, but they should not override underlying skill indicators without good reason.

Finally, integrate this evaluation with the overall game prediction, which also includes the opposing starter, bullpen quality, offensive strength, and situational factors. For the complete framework, see How MLB Games Are Predicted.