
Mariners vs Yankees Prediction, Picks & Odds — Thursday, July 10
#Team | ERA | OBP | OPS | SO |
---|---|---|---|---|
1
|
3.30 | .293 | .648 | 729 |
2
|
3.45 | .301 | .672 | 793 |
3
|
3.46 | .300 | .679 | 762 |
4
|
3.49 | .308 | .683 | 800 |
5
|
3.57 | .317 | .685 | 794 |
#Team | W/L | $ | HM $ | AW $ |
---|---|---|---|---|
1
|
54-39 | 1268 | 1114 | 154 |
2
|
55-38 | 1103 | 939 | 164 |
3
|
45-47 | 1071 | 180 | 891 |
4
|
59-35 | 1031 | 748 | 283 |
5
|
42-49 | 967 | -258 | 1225 |
#Player | AVG |
---|---|
1 Aaron Judge | .360 |
2 Jacob Wilson | .335 |
3 Jonathan Aranda | .327 |
4 Jeremy Pena | .322 |
5 Jake Meyers | .308 |
#Player | HR |
---|---|
1 Cal Raleigh | 36 |
2 Aaron Judge | 34 |
3 Shohei Ohtani | 31 |
4 Kyle Schwarber | 29 |
5 Eugenio Suarez | 29 |
#Player | RBI |
---|---|
1 Seiya Suzuki | 77 |
2 Aaron Judge | 77 |
3 Cal Raleigh | 76 |
4 Eugenio Suarez | 75 |
5 Pete Alonso | 75 |
#Player | R |
---|---|
1 Shohei Ohtani | 88 |
2 Aaron Judge | 83 |
3 Elly De La Cruz | 69 |
4 Kyle Tucker | 67 |
5 Pete Crow-Armstrong | 67 |
#Name | Team | W/L | $ |
---|---|---|---|
1 Cal Quantrill | MIA | 10-7 | 1009 |
2 Robbie Ray | SF | 15-4 | 896 |
3 Jackson Jobe | DET | 9-1 | 826 |
4 Andrew Abbott | CIN | 12-4 | 819 |
5 Sonny Gray | STL | 14-4 | 720 |
#Name | Team | O/U | % |
---|---|---|---|
1 Yusei Kikuchi | LAA | 13-6 | 68.4 |
2 Luis Severino | ATH | 12-6 | 66.7 |
3 Kevin Gausman | TOR | 12-6 | 66.7 |
4 Eduardo Rodriguez | AZ | 11-4 | 73.3 |
5 Brandon Pfaadt | AZ | 11-6 | 64.7 |
#Player | Wins |
---|---|
1 Max Fried | 11 |
2 Tarik Skubal | 10 |
3 Framber Valdez | 10 |
4 Freddy Peralta | 10 |
5 Jacob deGrom | 9 |
#Player | ERA |
---|---|
1 Paul Skenes | 1.94 |
2 Tarik Skubal | 2.02 |
3 Zack Wheeler | 2.17 |
4 Hunter Brown | 2.21 |
5 Max Fried | 2.27 |
#Player | SV |
---|---|
1 Robert Suarez | 26 |
2 Josh Hader | 25 |
3 Carlos Estevez | 25 |
4 Jeff Hoffman | 22 |
5 Andres Munoz | 21 |
#Player | SO |
---|---|
1 Garrett Crochet | 151 |
2 Tarik Skubal | 148 |
3 Zack Wheeler | 148 |
4 MacKenzie Gore | 138 |
5 Logan Webb | 133 |
#Name | W/L | % | $ |
---|---|---|---|
1 Stu Scheurwater | 14-3 | 82.4 | 670 |
2 Paul Clemons | 14-4 | 77.8 | 775 |
3 Nestor Ceja | 13-3 | 81.2 | 895 |
4 Laz Diaz | 13-6 | 68.4 | 456 |
5 Charlie Ramos | 12-4 | 75.0 | 549 |
#Name | O/U | % | AVG |
---|---|---|---|
1 Tom Hanahan | 12-4 | 75.0 | 10.8 |
2 Lance Barrett | 12-4 | 75.0 | 10.3 |
3 Shane Livensparger | 12-5 | 70.6 | 9.8 |
4 Adrian Johnson | 12-6 | 66.7 | 9.6 |
5 Andy Fletcher | 12-7 | 63.2 | 10.2 |
#Team | ERA | OBP | OPS | SO |
---|---|---|---|---|
1
|
3.30 | .293 | .648 | 729 |
2
|
3.45 | .301 | .672 | 793 |
3
|
3.46 | .300 | .679 | 762 |
4
|
3.58 | .293 | .671 | 889 |
5
|
3.78 | .303 | .706 | 778 |
#Team | W/L | $ | HM $ | AW $ |
---|---|---|---|---|
1
|
54-39 | 1268 | 1114 | 154 |
2
|
55-38 | 1103 | 939 | 164 |
3
|
45-47 | 1071 | 180 | 891 |
4
|
59-35 | 1031 | 748 | 283 |
5
|
50-43 | 625 | -199 | 824 |
#Player | AVG |
---|---|
1 Aaron Judge | .360 |
2 Jacob Wilson | .335 |
3 Jonathan Aranda | .327 |
4 Jeremy Pena | .322 |
5 Jake Meyers | .308 |
#Player | HR |
---|---|
1 Cal Raleigh | 36 |
2 Aaron Judge | 34 |
3 Junior Caminero | 22 |
4 Riley Greene | 22 |
5 Spencer Torkelson | 21 |
#Player | RBI |
---|---|
1 Aaron Judge | 77 |
2 Cal Raleigh | 76 |
3 Riley Greene | 72 |
4 Taylor Ward | 61 |
5 Junior Caminero | 58 |
#Player | R |
---|---|
1 Aaron Judge | 83 |
2 Cal Raleigh | 63 |
3 Byron Buxton | 60 |
4 Bobby Witt Jr. | 56 |
5 Vladimir Guerrero Jr. | 56 |
#Name | Team | W/L | $ |
---|---|---|---|
1 Jackson Jobe | DET | 9-1 | 826 |
2 Framber Valdez | HOU | 13-5 | 583 |
3 Shane Baz | TB | 12-6 | 578 |
4 Ben Lively | CLE | 7-2 | 574 |
5 Tyler Anderson | LAA | 10-7 | 565 |
#Name | Team | O/U | % |
---|---|---|---|
1 Yusei Kikuchi | LAA | 13-6 | 68.4 |
2 Luis Severino | ATH | 12-6 | 66.7 |
3 Kevin Gausman | TOR | 12-6 | 66.7 |
4 Gavin Williams | CLE | 11-6 | 64.7 |
5 Jose Berrios | TOR | 11-8 | 57.9 |
#Player | Wins |
---|---|
1 Max Fried | 11 |
2 Tarik Skubal | 10 |
3 Framber Valdez | 10 |
4 Jacob deGrom | 9 |
5 Hunter Brown | 9 |
#Player | ERA |
---|---|
1 Tarik Skubal | 2.02 |
2 Hunter Brown | 2.21 |
3 Max Fried | 2.27 |
4 Jacob deGrom | 2.29 |
5 Garrett Crochet | 2.39 |
#Player | SV |
---|---|
1 Josh Hader | 25 |
2 Carlos Estevez | 25 |
3 Jeff Hoffman | 22 |
4 Andres Munoz | 21 |
5 Emmanuel Clase | 19 |
#Player | SO |
---|---|
1 Garrett Crochet | 151 |
2 Tarik Skubal | 148 |
3 Hunter Brown | 129 |
4 Carlos Rodon | 127 |
5 Jack Flaherty | 117 |
#Name | W/L | % | $ |
---|---|---|---|
1 Nestor Ceja | 10-0 | 100.0 | 887 |
2 Doug Eddings | 9-2 | 81.8 | 836 |
3 Marvin Hudson | 9-2 | 81.8 | 790 |
4 Carlos Torres | 9-4 | 69.2 | 695 |
5 Paul Clemons | 8-1 | 88.9 | 748 |
#Name | O/U | % | AVG |
---|---|---|---|
1 Gabe Morales | 9-3 | 75.0 | 9.9 |
2 Andy Fletcher | 8-5 | 61.5 | 10.5 |
3 Edwin Moscoso | 7-2 | 77.8 | 9.8 |
4 Brian Walsh | 7-3 | 70.0 | 11.5 |
5 Shane Livensparger | 7-3 | 70.0 | 10.9 |
#Team | ERA | OBP | OPS | SO |
---|---|---|---|---|
1
|
3.49 | .308 | .683 | 800 |
2
|
3.57 | .317 | .685 | 794 |
3
|
3.66 | .306 | .688 | 857 |
4
|
3.68 | .309 | .684 | 801 |
5
|
3.68 | .300 | .680 | 698 |
#Team | W/L | $ | HM $ | AW $ |
---|---|---|---|---|
1
|
42-49 | 967 | -258 | 1225 |
2
|
53-40 | 937 | 847 | 90 |
3
|
49-44 | 404 | 708 | -304 |
4
|
55-38 | 371 | 210 | 161 |
5
|
49-43 | 313 | 385 | -72 |
#Player | AVG |
---|---|
1 Freddie Freeman | .299 |
2 Michael Busch | .296 |
3 Josh Naylor | .296 |
4 Trea Turner | .294 |
5 Brendan Donovan | .294 |
#Player | HR |
---|---|
1 Shohei Ohtani | 31 |
2 Kyle Schwarber | 29 |
3 Eugenio Suarez | 29 |
4 Pete Crow-Armstrong | 25 |
5 Seiya Suzuki | 25 |
#Player | RBI |
---|---|
1 Seiya Suzuki | 77 |
2 Eugenio Suarez | 75 |
3 Pete Alonso | 75 |
4 Pete Crow-Armstrong | 70 |
5 James Wood | 69 |
#Player | R |
---|---|
1 Shohei Ohtani | 88 |
2 Elly De La Cruz | 69 |
3 Kyle Tucker | 67 |
4 Pete Crow-Armstrong | 67 |
5 Juan Soto | 66 |
#Name | Team | W/L | $ |
---|---|---|---|
1 Cal Quantrill | MIA | 10-7 | 1009 |
2 Robbie Ray | SF | 15-4 | 896 |
3 Andrew Abbott | CIN | 12-4 | 819 |
4 Sonny Gray | STL | 14-4 | 720 |
5 Griffin Canning | NYM | 12-4 | 695 |
#Name | Team | O/U | % |
---|---|---|---|
1 Eduardo Rodriguez | AZ | 11-4 | 73.3 |
2 Brandon Pfaadt | AZ | 11-6 | 64.7 |
3 German Marquez | COL | 11-6 | 64.7 |
4 Spencer Schwellenbach | ATL | 10-6 | 62.5 |
5 Jake Irvin | WAS | 10-7 | 58.8 |
#Player | Wins |
---|---|
1 Freddy Peralta | 10 |
2 Zack Wheeler | 9 |
3 Matthew Boyd | 9 |
4 Sonny Gray | 9 |
5 Nick Pivetta | 9 |
#Player | ERA |
---|---|
1 Paul Skenes | 1.94 |
2 Zack Wheeler | 2.17 |
3 Matthew Boyd | 2.52 |
4 Cristopher Sanchez | 2.59 |
5 Logan Webb | 2.62 |
#Player | SV |
---|---|
1 Robert Suarez | 26 |
2 Trevor Megill | 21 |
3 Emilio Pagan | 19 |
4 Kyle Finnegan | 18 |
5 Ryan Helsley | 18 |
#Player | SO |
---|---|
1 Zack Wheeler | 148 |
2 MacKenzie Gore | 138 |
3 Logan Webb | 133 |
4 Dylan Cease | 129 |
5 Paul Skenes | 125 |
#Name | W/L | % | $ |
---|---|---|---|
1 Stu Scheurwater | 10-1 | 90.9 | 689 |
2 Charlie Ramos | 9-2 | 81.8 | 696 |
3 John Tumpane | 9-4 | 69.2 | 657 |
4 Jim Wolf | 8-4 | 66.7 | 675 |
5 Bill Miller | 7-3 | 70.0 | 604 |
#Name | O/U | % | AVG |
---|---|---|---|
1 Bill Miller | 8-2 | 80.0 | 11.2 |
2 Clint Vondrak | 8-5 | 61.5 | 12.1 |
3 Adrian Johnson | 7-2 | 77.8 | 10.4 |
4 Brennan Miller | 7-3 | 70.0 | 10.3 |
5 Ben May | 7-4 | 63.6 | 8.7 |
MLB betting stats offer deep insights into how teams perform not just on the diamond β but in relation to oddsmakersβ expectations. With a 162-game season and daily betting opportunities, knowing how to use metrics like ATS, O/U, and situational splits can be the difference between blind betting and sharp strategy.
Hereβs a breakdown of the key stats on this page and how to use them for more profitable baseball betting.
What it means: In MLB, ATS typically refers to runline betting β where a team must win by 2+ runs (β1.5) or lose/win by fewer than 2 runs (+1.5).
How to use it: A team like the Rays could be 60-45 ATS, indicating theyβve consistently beaten the runline. Underdogs that win outright or keep games close often offer ATS value.
π Runline stats are essential when deciding whether to bet a favorite straight up or lay the β1.5.
π Use the latest MLB odds to compare runline prices and spot market inefficiencies.
What it means: Tracks how often games go Over or Under the posted total runs.
How to use it: Team tendencies β like high-powered lineups or unreliable bullpens β directly influence totals. If the Rockies are 68-40 to the Over, it often signals offensive firepower or Coors Field factor.
π Factor in ballpark effects, pitching matchups, and weather when betting totals.
π Learn more with our MLB betting guide.
What it means: Outright win-loss records.
How to use it: Great for evaluating moneyline betting opportunities. Teams might be profitable SU without being elite β especially with plus-money value. For example, the Orioles may be 55-50 SU but +10 units due to frequent underdog wins.
π Use SU stats alongside profit/loss metrics to gauge value beyond win totals.
What it means: Tracks performance based on location.
How to use it: Some teams dominate at home but collapse on the road. If the Padres are 35-20 ATS at home but 20-40 away, location should strongly influence your wager.
π Ballpark familiarity, travel, and lineup depth often shift performance drastically between venues.
What it means: Shows how teams fare against divisional or league opponents.
How to use it: Divisional matchups are common and often tight. A team with a strong ATS record vs. its division may be particularly effective at exploiting familiar opponents.
π Use this when betting series between rivals or when playoff races heat up late in the season.
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Baseball is a grind β but with the right stats and bonus strategy, your bets can go the distance.