Predictive Pitching Metrics

Best metrics that indicate sustainable success for starting pitchers

(Written in January 2025)

---

Metrics and advanced analytics are invaluable tools for evaluating player performance,

particularly when assessing pitchers. The way we combine and apply these metrics can

significantly impact our understanding of a player’s potential for sustainable success. In this

analysis, I have compiled a comprehensive list of pitching metrics that I believe best indicate the

core components of a pitcher’s ability. These metrics are categorized into two key areas:

command and effectiveness. With command, I look at how effectively a pitcher is able to control

the strike zone and limit walks; while effectiveness, in this context, refers to the quality of

contact a pitcher allows.

It is important to recognize that success metrics for pitchers vary between starters and

relievers. For example, relievers like Josh Hader and Edwin Díaz, known for their high-velocity

arsenal, tend to allow more walks, especially when behind in counts, as they prioritize quickly

transitioning to the next batter and not giving a good pitch to hit. In contrast, starting pitchers

with less velocity such as Kyle Hendricks and Trevor Williams rely on superior command to

maintain efficiency and go deeper into games, which is crucial for long-term success.

In this analysis, I will outline each metrics significance, and why I feel it is important for

evaluating pitching performance, as well as examples of under the radar players who excel in

each area. It is strictly based on performance statistics, and independent of a player's mechanics

or arsenal. This comprehensive approach offers a robust framework for assessing pitchers and

identifying the key attributes that contribute to sustainable success in Major League Baseball.

COMMAND

First Pitch Strike Percentage

First-pitch strikes are critical, and the data supports this. According to Jerry Weinstein of

Weinstein Baseball, the expected runs scored after a first-pitch strike is less than half of that

following a first-pitch ball (.029 vs. .069). Additionally, a batter's wOBA drops significantly

when behind in the count (0-1), to .361, compared to .393 when ahead (1-0). Of course, as with

any statistic, there are notable flaws—such as hits allowed positively impact a pitcher's

first-pitch strike percentage. However, just 5.9% of first-pitch strikes resulted in hits over the last

5 seasons. In 2024, the MLB average for first-pitch strikes was 62.5%. An example of a pitcher

who frequently gets ahead leading to his success is Joe Ryan of the Minnesota Twins. Ryan

throws a first pitch strike 70.4% of the time—good for 3rd best among qualified arms. Ryan also

only gave up 15 hits all year on the first pitch, 12 of which were singles, supporting the idea that

it is only a minor flaw. Aided by his frequency of getting ahead, Joe finished the season in the

top 10% in xERA and walk percentage as well as top 15% in batting average allowed and top

20% in strikeout percentage.

Walk Percentage

Although it’s a simple statistic, walk rate plays a significant role in evaluating pitcher

performance. On average, around 30% of all walks score, and the rate is even higher for leadoff

walks. By minimizing walks, pitchers not only reduce their pitch count but also increase their

ability to go deeper into games, allowing starters to pitch longer and relievers to be used more

frequently. George Kirby exemplified this, posting the lowest walk rate among all qualified

pitchers at just 3.0%, far below the league average of 7.9%. This efficiency helped him log the

9th most innings in the league, as his ability to limit walks kept his pitch counts lower. As a

team, the Mariners had the lowest walk rate in the league at 6.1%, which certainly contributed to

them allowing the fewest runs in MLB. In contrast, the White Sox, who had the highest walk rate

at 9.9%, gave up the third-most runs this season. This highlights the impact of walk rate on both

individual pitcher performance and overall team success.

Whiff Rate

Whiff rate is a crucial indicator in evaluating a pitcher’s ability to generate swings and misses.

On its own, it may not tell the full story, but it’s an excellent predictive metric for future success.

A high whiff rate suggests that a pitcher possesses swing-and-miss stuff, the ability to avoid

barrels, and a greater potential to produce favorable outcomes. Even if the pitcher’s results aren’t

consistently ideal, a strong whiff rate often signals that better results could be on the horizon.

Some of the best pitchers in the game are at the top of the leaderboard in whiff rate, thus why

they are some of the best in the game. Garrett Crochet, Dylan Cease, Jack Flaherty, Cole Ragans,

and Tarik Skubal round out the top 5, demonstrating the importance of the metric. One

under-the-radar pitcher who exemplifies this is Ryan Pepiot of the Tampa Bay Rays. Pepiot

boasts an impressive 29.9% whiff rate, placing him in the 82nd percentile, and he ranks 12th

among all qualified pitchers in this category. His ability to generate swings and misses positions

him as a potential breakout candidate with significant upside after only just completing one full

season as a starter. This is also reflected in his expected stats, where he ranks in the top half of

the league in both xBA and xERA. These metrics further suggest that Pepiot’s underlying

performance supports the idea that his swing-and-miss stuff could translate into stronger overall

results moving forward.

Chase Rate

A high chase rate is a valuable indicator for a pitcher’s success, as it often correlates with lower

quality of contact. When a pitcher can induce swings at pitches outside the strike zone, it often

leads to more swing-and-miss outcomes or weak contact. In 2024, the league-wide chase contact

percentage was just 55.8%, while the strike zone contact percentage was much higher at 82.2%.

Among all pitches swung at outside the zone, 43.9% resulted in a whiff, and only 18.3% were

classified as hard hits. In contrast, pitches thrown in the zone saw a much lower whiff rate of

17.4%, and a higher hard-hit percentage of 43.8%. Clearly, the data shows that generating chases

outside the zone can significantly increase a pitcher’s chances of success. One pitcher who

exemplifies this ability is left-hander Christopher Sánchez of the Philadelphia Phillies. In 2024,

Sánchez led all qualified pitchers in chase rate with a remarkable 36.4%, well above the league

average of 28.5%. While Sánchez may not yet be a household name, his 2024 campaign was

fairly impressive, as he posted a solid 3.32 ERA over 31 starts. But what really stands out are his

excellent contact metrics: he finished in the 95th percentile in Ground Ball%, the 86th percentile

in Barrel%, and the 82nd percentile in Hard Hit%. Additionally, he limited walks, ranking in the

84th percentile for BB%. Sánchez’s ability to generate chases outside the zone, leading to weak

contact, underscores how chase rate can be a strong predictor of future success.

EFFECTIVENESS

xFIP

I prefer xFIP over FIP because it offers a more accurate prediction of future performance rather

than simply reflecting on past results. The key advantage of xFIP is how it normalizes a pitcher’s

home run rate, which can be influenced by external factors like park dimensions and weather

conditions. By adjusting for these variables, xFIP provides a clearer picture of a pitcher’s true

capabilities, less impacted by bad luck or fluctuating circumstances. Additionally, xFIP focuses

solely on what a pitcher can control—strikeouts, walks, and home runs—without factoring in

defense. For example, Sonny Gray had the second-lowest xFIP among qualified pitchers at 2.82,

which is notably lower than his FIP of 3.12. This suggests that some of his results were likely

influenced by the aforementioned external factors such as park factors or bad luck. Gray posted a

3.8 WAR, but had his home runs given up occurred in different parks or during different weather

conditions, his xFIP suggests his WAR could have potentially been higher. Gray’s performance

was also bolstered by his strong strikeout rate (91st percentile) and walk rate (84th percentile),

both of which contributed to his low xFIP. Similar to Gray, the Cy Young winners in both

leagues, Chris Sale and Tarik Skubal, finished 1st and 3rd in xFIP, respectively, further

demonstrating how this metric can be a reliable indicator of success.

xwOBA

xwOBA is a valuable tool for predicting the quality of contact that pitchers allow. Unlike wOBA

which only relies on past results, xwOBA removes the impact of defense, recognizing that

neither the batter nor the pitcher can control what happens after the ball leaves the bat. It focuses

on the quality of contact a pitcher gives up, rather than the actual outcome, which makes it a

strong predictive metric. Over time, xwOBA provides a more accurate reflection of a pitcher's

performance. For example, if a pitcher allows a line drive with an exit velocity of 110 mph, but it

happens to be hit directly at the third baseman for an out, xwOBA will reflect this as a harsher

outcome than a blooper with a high launch angle and low exit velocity that falls in no man's land

for a hit. The key takeaway is that pitchers have little control over the final result once the ball

leaves their hand. Instead, the focus should be on generating weak contact, and xwOBA helps to

highlight this by adjusting for the randomness of outcomes, offering a clearer picture of a

pitcher's true performance. A great example of this in 2024 was lefty Justin Steele of the Chicago

Cubs. Steele finished 4th among qualified pitchers with an xwOBA of .258, significantly lower

than the league average of .312. His performance was supported by his placement in the 94th

percentile for Barrel%, 89th percentile for Average Exit Velocity, and 88th percentile for Hard

Hit Percentage. Steele's ability to induce weak contact was reflected in his low xwOBA, which

makes this stat so useful for predicting the type of contact a pitcher is likely to give up in the

future.

SIERA

SIERA is similar to xFIP, but the key difference is how they account for balls in play. Like ERA, SIERA estimates the number of runs a pitcher should expect to allow based on their ability to

generate weak contact, particularly through ground balls and pop-ups. In contrast, xFIP focuses

primarily on the number of home runs a pitcher is expected to allow, based on their fly ball rate

and the league’s average home run rate. Both metrics are valuable for evaluating a pitcher’s

performance because they isolate factors the pitcher can control—such as strikeouts, walks, and

batted-ball outcomes—while eliminating external influences like defense and park factors.

However, SIERA gives a more complete picture of a pitcher’s overall skill set because it

accounts for a wider range of batted-ball outcomes, not just home runs. In 2024, Pablo Lopez

posted a SIERA of 3.46, ranking 9th among qualified pitchers. He finished in the upper half of

the league in several key categories that contribute to SIERA, including Ground Ball Rate, Hard

Hit Rate, Strikeout Rate, and was in the 90th percentile for Walk Rate. Additionally, Lopez

ranked 8th in the American League for home runs allowed, 6th in strikeouts, 5th in earned runs

allowed, and 2nd in hits allowed. His undervalued 2024 campaign was clearly reflected in his

SIERA, which is why I find it useful as a predictive statistic. It provides a solid foundation for

understanding how a pitcher might perform across various other subcategories.