Arizona Diamondbacks vs. St. Louis Cardinals Prediction – July 23, 2026
The Arizona Diamondbacks head to St. Louis for a Thursday afternoon showdown against the Cardinals, and this one shapes up to be a genuine toss-up. With the WP Baseball Predictor assigning a 51.5% win probability to the Cardinals and just a 48.5% edge to Arizona, the model sees no dominant favourite — making the Diamondbacks +1.5 run line the value play heading into first pitch.
Starting Pitcher Matchup: Pfaadt vs. McGreevy
The pitching matchup sits at the heart of this preview, and the advanced numbers reveal a modest but meaningful edge for the home side.
Brandon Pfaadt (Arizona Diamondbacks)
Brandon Pfaadt takes the mound for Arizona carrying an xFIP of 4.38. Expected Fielding Independent Pitching strips out the noise of defence and batted-ball luck, giving us a cleaner read on a pitcher's true performance level. Pfaadt's mark suggests he is a slightly below-average starting option by this metric, and in a road environment against a Cardinals lineup that carries a team wOBA of .306, he will need to work efficiently to keep Arizona competitive through the middle innings.
Michael McGreevy (St. Louis Cardinals)
McGreevy counters with an xFIP of 4.07 — a full 31 points better than Pfaadt's mark. While neither arm grades out as an ace, McGreevy's figure indicates he is the more reliable option on the mound today. Pitching at home with a Cardinals defence behind him, McGreevy has the metrics to keep Arizona's offence — which also posts a team wOBA of .306 — from breaking through consistently. This starting pitcher edge is a primary driver behind the Cardinals' slim win probability advantage in the WP model.
Team Metrics: Evenly Matched Offences, Cardinals Hold Pitching Edge
Beyond the starting pitching duel, the broader team statistics paint a picture of two very similar ballclubs:
- Diamondbacks: Team wOBA .306 | Team FIP 4.52 | Team ERA 4.21
- Cardinals: Team wOBA .306 | Team FIP 4.21 | Team ERA 4.12
The offensive production is essentially identical, with both clubs sitting at a .306 wOBA. The separation comes on the pitching side, where St. Louis holds a cleaner team FIP (4.21 vs. 4.52) and a lower team ERA (4.12 vs. 4.21). These margins are thin, but they consistently favour the Cardinals and explain why the WP model leans St. Louis — even if only slightly.
Injury Report: Diamondbacks Carrying More Concern
Arizona's injury situation is notably heavier heading into this contest and could influence roster depth and bullpen availability.
Diamondbacks Injuries
- Zac Gallen – Elbow (15-Day IL): The veteran arm's absence removes a significant rotation piece, increasing pressure on Pfaadt to go deep into games.
- Lourdes Gurriel Jr. – Thigh (10-Day IL): An offensive contributor sidelined at a critical stretch.
- Yordin Chalas – Undisclosed (7-Day IL)
- Patrick Forbes – Elbow (Out)
- Aramis Garcia – Undisclosed (7-Day IL)
Cardinals Injuries
- JoJo Romero – Abdomen (15-Day IL)
- Skylar Hales – Undisclosed (7-Day IL)
- Ethan Young – Undisclosed (7-Day IL)
Arizona's longer injury list — particularly the loss of Gallen from the rotation — represents a real structural disadvantage. St. Louis's absences are notable but less roster-disrupting overall.
Dark Horse Home Run Picks
🔴 Corbin Carroll (Diamondbacks)
Carroll has the athleticism and bat speed to catch a McGreevy pitch in the zone and drive it out to right-center. Keep an eye on him to provide Arizona's biggest offensive moment.
🔴 Nelson Velázquez (Cardinals)
Velázquez has the raw power to punish a mistake from Pfaadt. If Arizona's starter leaves anything elevated in the zone, Velázquez is capable of making him pay in a big way.
WP Baseball Predictor Final Pick
The Cardinals hold the edge in starting pitching metrics and team pitching depth, but the razor-thin win probability split (51.5% vs. 48.5%) makes laying a full run line risky. The WP model's official pick is Diamondbacks +1.5, capturing value on Arizona staying within striking distance even in a potential loss. In a game this close, backing the underdog on the run line is a smart, data-driven approach.