Looking at ERA alone? xERA shows who’s actually pitching. See the gaps.

Pitching, not just the scoreboard, tells the real story about how pitchers are performing. When you evaluate this list through the lens of advanced metrics like xERA, strikeout-minus-walk rate, and contact quality, several names look different than their ERA alone would suggest. In fact, seven of the ten on this list have ERAs that are significantly inflated relative to their underlying performance, with gaps often exceeding two runs. This isn’t merely bad luck; it’s a group of pitchers whose underlying skills indicate they’ve been fortunate—for a while.

Here are the ten pitchers, ranked by their similarity to a foul-line predictor of true performance:

10. Colin Rea, Chicago
Colin Rea has an ERA of 4.74, but the underlying data tells a starker story: a 5.48 xERA and a cushion of 0.74 runs not yet paid back. His 8.6% K-BB% is below average, and 41.6% of contact against him is hard-hit. In other words, his surface results have been buoyed, while the underlying indicators point to mediocrity across the board.

9. Eric Lauer, Los Angeles / Toronto
Eric Lauer sits with an ERA of 4.84, and an xERA of 5.06, a relatively tight gap. The more telling issue is his 6.4% K-BB%, which suggests he isn’t missing many bats, leaving outcomes highly dependent on contact quality and luck. The underlying performance suggests mostly earned runs, with a portion remaining to be settled.

8. Jameson Taillon, Chicago
Jameson Taillon stands out for having the best K-BB% on this list at 12.5%—he can miss bats—yet hitters are barreling 14.3% of the balls in play against him, the second-highest rate on the list. His ERA is 5.19, while his xERA is 5.48, indicating strong strike throwing is offset by heavy contact when bats connect.

7. Zac Gallen, Arizona
In eighteen starts totaling 92 innings, Zac Gallen carries a 6.36 ERA with a nearby 6.27 xERA. There’s little to explain away here: a 6.8% K-BB% and 44.4% hard-hit contact. The scoreboard and the underlying metrics align in this case—he’s been both unlucky and hittable when contact is made.

6. Steven Matz, Tampa Bay
Steven Matz can show some swing-and-miss with a 9.6% K-BB%, but contact quality hurts him: hitters barrel 13.0% of the time, and his 6.28 ERA sits in line with a 5.81 xERA. It’s one of those difficult combinations where solid peripherals still translate into elevated runs allowed.

5. Simeon Woods Richardson, Minnesota / Toronto
Simeon Woods Richardson’s K-BB% is -0.4%—he’s walked more than he’s struck out. He sits at a 6.40 ERA against a 5.92 xERA, with a 1.751 WHIP and just one win in ten starts. There’s little mystery here: he has performed poorly across the board, with little to disguise.

4. Zack Littell, Washington
Zack Littell has a 5.02 ERA but seven wins that mask the true performance. His 6.52 xERA is notably higher, and his 7.0% K-BB% combined with 46.4% hard-hit contact suggests he’s living on borrowed time. Consistent, hard-hit contact points to an expectant regression.

3. Randy Vásquez, San Diego
Randy Vásquez is highlighted as a notable deception: a 4.71 ERA on top of a 7.12 xERA. That implies a 2.41-run gap, underscored by opponents hitting 47.3% of contact hard. It’s not run prevention; it’s a fuse burning, and the underlying numbers indicate impending trouble if those patterns don’t flip.

2. Tomoyuki Sugano, Colorado
Tomoyuki Sugano has eight wins and a 4.80 ERA, yet a 7.07 xERA sits well above. Hitters barrel 14.0% of their contact against him, and 44.6% is hard-hit. While Coors Field inflates ERA, the underlying contact quality signals that the true performance is closer to the higher xERA than the surface ERA.

1. Merrill Kelly, Arizona
Merrill Kelly tops the list with the worst underlying pitching. He carries a 7.77 xERA, a 4.7% K-BB%, and a 14.5% barrel rate—the highest in the group. His 5.71 ERA with six wins serves as a cushion for now, but the underlying data point to a significant performance gap and poor underlying effectiveness.

Takeaways
– ERA can be misleading when not viewed through advanced metrics. Some pitchers are performing better or worse than their traditional ERA would indicate.
– A few names on this list show signs of potential regression based on higher xERA, elevated contact quality, or poor strikeout efficiency.
– For teams evaluating pitcher performance, focusing on xERA, K-BB%, and contact quality provides a clearer picture of sustainability and risk than ERA alone.

This assessment emphasizes the importance of looking beyond the scoreboard. By weighing underlying indicators such as xERA, strikeout-minus-walk rate, and contact quality, you gain a more accurate view of which pitchers are truly producing and which are merely benefiting from favorable outcomes.