
Tigers vs Twins Prediction, Picks & Odds — Saturday, August 16
#Team | ERA | OBP | OPS | SO |
---|---|---|---|---|
1
|
3.44 | .297 | .665 | 1012 |
2
|
3.56 | .302 | .663 | 1053 |
3
|
3.61 | .305 | .682 | 1062 |
4
|
3.63 | .305 | .688 | 967 |
5
|
3.71 | .304 | .692 | 1111 |
#Team | W/L | $ | HM $ | AW $ |
---|---|---|---|---|
1
|
78-44 | 2624 | 1356 | 1268 |
2
|
73-51 | 1836 | 1641 | 195 |
3
|
58-65 | 1249 | 166 | 1083 |
4
|
59-63 | 1227 | 598 | 629 |
5
|
69-53 | 1219 | 1018 | 201 |
#Player | AVG |
---|---|
1 Aaron Judge | .333 |
2 Jeremy Pena | .317 |
3 Jonathan Aranda | .316 |
4 Jacob Wilson | .312 |
5 Xavier Edwards | .306 |
#Player | HR |
---|---|
1 Cal Raleigh | 46 |
2 Kyle Schwarber | 43 |
3 Shohei Ohtani | 43 |
4 Aaron Judge | 39 |
5 Junior Caminero | 35 |
#Player | RBI |
---|---|
1 Kyle Schwarber | 101 |
2 Cal Raleigh | 100 |
3 Pete Alonso | 100 |
4 Aaron Judge | 91 |
5 Riley Greene | 90 |
#Player | R |
---|---|
1 Shohei Ohtani | 117 |
2 Aaron Judge | 95 |
3 Juan Soto | 87 |
4 Elly De La Cruz | 86 |
5 Fernando Tatis Jr. | 84 |
#Name | Team | W/L | $ |
---|---|---|---|
1 Cal Quantrill | MIA | 13-11 | 1019 |
2 Tomoyuki Sugano | BAL | 15-8 | 901 |
3 Jose Quintana | MIL | 13-5 | 828 |
4 Sonny Gray | STL | 18-7 | 828 |
5 Jackson Jobe | DET | 9-1 | 826 |
#Name | Team | O/U | % |
---|---|---|---|
1 Yusei Kikuchi | LAA | 18-8 | 69.2 |
2 Luis Severino | ATH | 15-8 | 65.2 |
3 Jacob deGrom | TEX | 15-9 | 62.5 |
4 Casey Mize | DET | 14-7 | 66.7 |
5 Brandon Pfaadt | AZ | 14-9 | 60.9 |
#Player | Wins |
---|---|
1 Freddy Peralta | 14 |
2 Max Fried | 13 |
3 Garrett Crochet | 13 |
4 Carlos Rodon | 12 |
5 Nick Pivetta | 12 |
#Player | ERA |
---|---|
1 Paul Skenes | 2.13 |
2 Tarik Skubal | 2.42 |
3 Cristopher Sanchez | 2.45 |
4 Hunter Brown | 2.45 |
5 Matthew Boyd | 2.46 |
#Player | SV |
---|---|
1 Robert Suarez | 33 |
2 Carlos Estevez | 31 |
3 Andres Munoz | 29 |
4 Trevor Megill | 29 |
5 Josh Hader | 28 |
#Player | SO |
---|---|
1 Zack Wheeler | 195 |
2 Tarik Skubal | 190 |
3 Garrett Crochet | 188 |
4 Dylan Cease | 171 |
5 Logan Webb | 168 |
#Name | W/L | % | $ |
---|---|---|---|
1 Paul Clemons | 18-6 | 75.0 | 946 |
2 Carlos Torres | 17-6 | 73.9 | 835 |
3 Laz Diaz | 17-7 | 70.8 | 761 |
4 Stu Scheurwater | 16-5 | 76.2 | 644 |
5 CB Bucknor | 16-6 | 72.7 | 791 |
#Name | O/U | % | AVG |
---|---|---|---|
1 Tom Hanahan | 16-6 | 72.7 | 10.2 |
2 Ryan Additon | 15-6 | 71.4 | 10.0 |
3 Lance Barrett | 15-7 | 68.2 | 9.8 |
4 Shane Livensparger | 15-8 | 65.2 | 9.3 |
5 Chris Conroy | 15-9 | 62.5 | 10.2 |
#Team | ERA | OBP | OPS | SO |
---|---|---|---|---|
1
|
3.44 | .297 | .665 | 1012 |
2
|
3.63 | .305 | .688 | 967 |
3
|
3.73 | .319 | .694 | 1009 |
4
|
3.77 | .300 | .692 | 1168 |
5
|
3.80 | .304 | .692 | 1069 |
#Team | W/L | $ | HM $ | AW $ |
---|---|---|---|---|
1
|
73-51 | 1836 | 1641 | 195 |
2
|
59-63 | 1227 | 598 | 629 |
3
|
69-54 | 1036 | 596 | 440 |
4
|
68-56 | 515 | 1097 | -582 |
5
|
68-56 | 390 | 248 | 142 |
#Player | AVG |
---|---|
1 Aaron Judge | .333 |
2 Jeremy Pena | .317 |
3 Jonathan Aranda | .316 |
4 Jacob Wilson | .312 |
5 Maikel Garcia | .301 |
#Player | HR |
---|---|
1 Cal Raleigh | 46 |
2 Aaron Judge | 39 |
3 Junior Caminero | 35 |
4 Taylor Ward | 29 |
5 Riley Greene | 28 |
#Player | RBI |
---|---|
1 Cal Raleigh | 100 |
2 Aaron Judge | 91 |
3 Riley Greene | 90 |
4 Taylor Ward | 90 |
5 Junior Caminero | 85 |
#Player | R |
---|---|
1 Aaron Judge | 95 |
2 Vladimir Guerrero Jr. | 82 |
3 Cal Raleigh | 81 |
4 Julio Rodriguez | 80 |
5 Brent Rooker | 79 |
#Name | Team | W/L | $ |
---|---|---|---|
1 Tomoyuki Sugano | BAL | 15-8 | 901 |
2 Jackson Jobe | DET | 9-1 | 826 |
3 Eric Lauer | TOR | 11-3 | 793 |
4 Jacob Lopez | ATH | 10-5 | 736 |
5 Lucas Giolito | BOS | 13-6 | 721 |
#Name | Team | O/U | % |
---|---|---|---|
1 Yusei Kikuchi | LAA | 18-8 | 69.2 |
2 Luis Severino | ATH | 15-8 | 65.2 |
3 Jacob deGrom | TEX | 15-9 | 62.5 |
4 Casey Mize | DET | 14-7 | 66.7 |
5 Kevin Gausman | TOR | 14-9 | 60.9 |
#Player | Wins |
---|---|
1 Max Fried | 13 |
2 Garrett Crochet | 13 |
3 Carlos Rodon | 12 |
4 Joe Ryan | 12 |
5 Tarik Skubal | 11 |
#Player | ERA |
---|---|
1 Tarik Skubal | 2.42 |
2 Hunter Brown | 2.45 |
3 Garrett Crochet | 2.48 |
4 Joe Ryan | 2.72 |
5 Jacob deGrom | 2.76 |
#Player | SV |
---|---|
1 Carlos Estevez | 31 |
2 Andres Munoz | 29 |
3 Josh Hader | 28 |
4 Jeff Hoffman | 27 |
5 Kenley Jansen | 23 |
#Player | SO |
---|---|
1 Tarik Skubal | 190 |
2 Garrett Crochet | 188 |
3 Hunter Brown | 164 |
4 Carlos Rodon | 164 |
5 Bryan Woo | 153 |
#Name | W/L | % | $ |
---|---|---|---|
1 Nestor Ceja | 11-1 | 91.7 | 964 |
2 Laz Diaz | 11-1 | 91.7 | 944 |
3 Ryan Blakney | 11-2 | 84.6 | 841 |
4 Marvin Hudson | 11-4 | 73.3 | 901 |
5 Carlos Torres | 11-4 | 73.3 | 873 |
#Name | O/U | % | AVG |
---|---|---|---|
1 Gabe Morales | 10-5 | 66.7 | 9.2 |
2 Shane Livensparger | 9-3 | 75.0 | 11.3 |
3 Mike Muchlinski | 9-5 | 64.3 | 10.1 |
4 Alfonso Marquez | 9-5 | 64.3 | 9.7 |
5 Chad Whitson | 8-1 | 88.9 | 11.3 |
#Team | ERA | OBP | OPS | SO |
---|---|---|---|---|
1
|
3.56 | .302 | .663 | 1053 |
2
|
3.61 | .305 | .682 | 1062 |
3
|
3.71 | .304 | .692 | 1111 |
4
|
3.72 | .315 | .698 | 1039 |
5
|
3.79 | .320 | .697 | 1051 |
#Team | W/L | $ | HM $ | AW $ |
---|---|---|---|---|
1
|
78-44 | 2624 | 1356 | 1268 |
2
|
58-65 | 1249 | 166 | 1083 |
3
|
69-53 | 1219 | 1018 | 201 |
4
|
64-60 | 621 | 325 | 296 |
5
|
69-53 | -17 | -51 | 34 |
#Player | AVG |
---|---|
1 Xavier Edwards | .306 |
2 Will Smith | .306 |
3 Freddie Freeman | .299 |
4 Ketel Marte | .298 |
5 Nico Hoerner | .294 |
#Player | HR |
---|---|
1 Kyle Schwarber | 43 |
2 Shohei Ohtani | 43 |
3 Juan Soto | 30 |
4 Pete Alonso | 28 |
5 Pete Crow-Armstrong | 27 |
#Player | RBI |
---|---|
1 Kyle Schwarber | 101 |
2 Pete Alonso | 100 |
3 Seiya Suzuki | 86 |
4 Christian Yelich | 86 |
5 James Wood | 80 |
#Player | R |
---|---|
1 Shohei Ohtani | 117 |
2 Juan Soto | 87 |
3 Elly De La Cruz | 86 |
4 Fernando Tatis Jr. | 84 |
5 Kyle Schwarber | 83 |
#Name | Team | W/L | $ |
---|---|---|---|
1 Cal Quantrill | MIA | 13-11 | 1019 |
2 Jose Quintana | MIL | 13-5 | 828 |
3 Sonny Gray | STL | 18-7 | 828 |
4 Griffin Canning | NYM | 12-4 | 695 |
5 Robbie Ray | SF | 17-8 | 687 |
#Name | Team | O/U | % |
---|---|---|---|
1 Brandon Pfaadt | AZ | 14-9 | 60.9 |
2 Jake Irvin | WAS | 14-9 | 60.9 |
3 Sonny Gray | STL | 14-10 | 58.3 |
4 MacKenzie Gore | WAS | 13-10 | 56.5 |
5 Jesus Luzardo | PHI | 13-10 | 56.5 |
#Player | Wins |
---|---|
1 Freddy Peralta | 14 |
2 Nick Pivetta | 12 |
3 Brandon Pfaadt | 12 |
4 Jesus Luzardo | 11 |
5 Cristopher Sanchez | 11 |
#Player | ERA |
---|---|
1 Paul Skenes | 2.13 |
2 Cristopher Sanchez | 2.45 |
3 Matthew Boyd | 2.46 |
4 Zack Wheeler | 2.71 |
5 Yoshinobu Yamamoto | 2.84 |
#Player | SV |
---|---|
1 Robert Suarez | 33 |
2 Trevor Megill | 29 |
3 Emilio Pagan | 25 |
4 Edwin Diaz | 24 |
5 Ryan Helsley | 21 |
#Player | SO |
---|---|
1 Zack Wheeler | 195 |
2 Dylan Cease | 171 |
3 Logan Webb | 168 |
4 Paul Skenes | 166 |
5 MacKenzie Gore | 165 |
#Name | W/L | % | $ |
---|---|---|---|
1 Stu Scheurwater | 11-2 | 84.6 | 800 |
2 Charlie Ramos | 11-3 | 78.6 | 871 |
3 John Tumpane | 11-6 | 64.7 | 775 |
4 Jim Wolf | 10-4 | 71.4 | 835 |
5 Will Little | 9-5 | 64.3 | 748 |
#Name | O/U | % | AVG |
---|---|---|---|
1 Bill Miller | 11-2 | 84.6 | 11.8 |
2 Clint Vondrak | 10-6 | 62.5 | 12.4 |
3 Ryan Wills | 9-2 | 81.8 | 10.9 |
4 Tom Hanahan | 9-4 | 69.2 | 9.8 |
5 Chris Conroy | 9-7 | 56.2 | 9.9 |
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.