
Blue Jays Prediction, Picks & Best Bet vs the Red Sox for September 25
#Team | ERA | OBP | OPS | SO |
---|---|---|---|---|
1
|
3.45 | .295 | .669 | 1316 |
2
|
3.61 | .305 | .677 | 1402 |
3
|
3.64 | .301 | .670 | 1392 |
4
|
3.68 | .311 | .696 | 1351 |
5
|
3.72 | .316 | .693 | 1329 |
#Team | W/L | $ | HM $ | AW $ |
---|---|---|---|---|
1
|
96-63 | 2151 | 1180 | 971 |
2
|
77-82 | 1959 | -56 | 2015 |
3
|
86-73 | 1534 | 250 | 1284 |
4
|
91-68 | 1501 | 1570 | -69 |
5
|
87-72 | 636 | 922 | -286 |
#Player | AVG |
---|---|
1 Aaron Judge | .328 |
2 Jacob Wilson | .313 |
3 Bo Bichette | .311 |
4 Trea Turner | .305 |
5 Jeremy Pena | .304 |
#Player | HR |
---|---|
1 Cal Raleigh | 60 |
2 Kyle Schwarber | 56 |
3 Shohei Ohtani | 54 |
4 Aaron Judge | 51 |
5 Junior Caminero | 44 |
#Player | RBI |
---|---|
1 Kyle Schwarber | 132 |
2 Cal Raleigh | 125 |
3 Pete Alonso | 123 |
4 Riley Greene | 111 |
5 Junior Caminero | 109 |
#Player | R |
---|---|
1 Shohei Ohtani | 144 |
2 Aaron Judge | 133 |
3 Juan Soto | 119 |
4 Francisco Lindor | 113 |
5 Kyle Schwarber | 110 |
#Name | Team | W/L | $ |
---|---|---|---|
1 Lucas Giolito | BOS | 18-8 | 995 |
2 Quinn Priester | MIL | 17-6 | 966 |
3 Trevor Rogers | BAL | 13-4 | 948 |
4 Robbie Ray | SF | 22-10 | 930 |
5 Eric Lauer | TOR | 12-3 | 849 |
#Name | Team | O/U | % |
---|---|---|---|
1 Yusei Kikuchi | LAA | 21-12 | 63.6 |
2 Jacob deGrom | TEX | 18-12 | 60.0 |
3 Jose Berrios | TOR | 18-12 | 60.0 |
4 Sonny Gray | STL | 18-13 | 58.1 |
5 Jose Soriano | LAA | 18-13 | 58.1 |
#Player | Wins |
---|---|
1 Max Fried | 19 |
2 Garrett Crochet | 18 |
3 Carlos Rodon | 17 |
4 Freddy Peralta | 17 |
5 Bryan Woo | 15 |
#Player | ERA |
---|---|
1 Paul Skenes | 1.97 |
2 Tarik Skubal | 2.21 |
3 Hunter Brown | 2.43 |
4 Yoshinobu Yamamoto | 2.49 |
5 Cristopher Sanchez | 2.57 |
#Player | SV |
---|---|
1 Carlos Estevez | 41 |
2 Robert Suarez | 40 |
3 Andres Munoz | 38 |
4 Jeff Hoffman | 32 |
5 Aroldis Chapman | 32 |
#Player | SO |
---|---|
1 Garrett Crochet | 255 |
2 Tarik Skubal | 241 |
3 Jesus Luzardo | 216 |
4 Paul Skenes | 216 |
5 Logan Webb | 216 |
#Name | W/L | % | $ |
---|---|---|---|
1 Laz Diaz | 22-9 | 71.0 | 995 |
2 Paul Clemons | 21-8 | 72.4 | 1023 |
3 Bill Miller | 21-10 | 67.7 | 874 |
4 Adam Hamari | 21-10 | 67.7 | 725 |
5 Mike Muchlinski | 20-10 | 66.7 | 733 |
#Name | O/U | % | AVG |
---|---|---|---|
1 Alfonso Marquez | 19-9 | 67.9 | 9.8 |
2 Shane Livensparger | 19-10 | 65.5 | 9.2 |
3 Dan Bellino | 18-9 | 66.7 | 9.6 |
4 Ben May | 18-10 | 64.3 | 10.0 |
5 Tom Hanahan | 18-11 | 62.1 | 9.6 |
#Team | ERA | OBP | OPS | SO |
---|---|---|---|---|
1
|
3.45 | .295 | .669 | 1316 |
2
|
3.68 | .311 | .696 | 1351 |
3
|
3.72 | .316 | .693 | 1329 |
4
|
3.75 | .307 | .700 | 1228 |
5
|
3.87 | .305 | .701 | 1383 |
#Team | W/L | $ | HM $ | AW $ |
---|---|---|---|---|
1
|
86-73 | 1534 | 250 | 1284 |
2
|
91-68 | 1501 | 1570 | -69 |
3
|
87-72 | 584 | 403 | 181 |
4
|
85-74 | 527 | 352 | 175 |
5
|
89-69 | 486 | 731 | -245 |
#Player | AVG |
---|---|
1 Aaron Judge | .328 |
2 Jacob Wilson | .313 |
3 Bo Bichette | .311 |
4 Jeremy Pena | .304 |
5 George Springer | .303 |
#Player | HR |
---|---|
1 Cal Raleigh | 60 |
2 Aaron Judge | 51 |
3 Junior Caminero | 44 |
4 Riley Greene | 36 |
5 Jo Adell | 36 |
#Player | RBI |
---|---|
1 Cal Raleigh | 125 |
2 Riley Greene | 111 |
3 Junior Caminero | 109 |
4 Aaron Judge | 109 |
5 Vinnie Pasquantino | 108 |
#Player | R |
---|---|
1 Aaron Judge | 133 |
2 Cal Raleigh | 109 |
3 Julio Rodriguez | 105 |
4 George Springer | 102 |
5 Jose Ramirez | 101 |
#Name | Team | W/L | $ |
---|---|---|---|
1 Lucas Giolito | BOS | 18-8 | 995 |
2 Trevor Rogers | BAL | 13-4 | 948 |
3 Eric Lauer | TOR | 12-3 | 849 |
4 Jason Alexander | HOU | 10-2 | 847 |
5 Jackson Jobe | DET | 9-1 | 826 |
#Name | Team | O/U | % |
---|---|---|---|
1 Yusei Kikuchi | LAA | 21-12 | 63.6 |
2 Jacob deGrom | TEX | 18-12 | 60.0 |
3 Jose Berrios | TOR | 18-12 | 60.0 |
4 Jose Soriano | LAA | 18-13 | 58.1 |
5 Casey Mize | DET | 17-10 | 63.0 |
#Player | Wins |
---|---|
1 Max Fried | 19 |
2 Garrett Crochet | 18 |
3 Carlos Rodon | 17 |
4 Bryan Woo | 15 |
5 Tarik Skubal | 13 |
#Player | ERA |
---|---|
1 Tarik Skubal | 2.21 |
2 Hunter Brown | 2.43 |
3 Garrett Crochet | 2.59 |
4 Max Fried | 2.86 |
5 Bryan Woo | 2.94 |
#Player | SV |
---|---|
1 Carlos Estevez | 41 |
2 Andres Munoz | 38 |
3 Jeff Hoffman | 32 |
4 Aroldis Chapman | 32 |
5 Josh Hader | 28 |
#Player | SO |
---|---|
1 Garrett Crochet | 255 |
2 Tarik Skubal | 241 |
3 Hunter Brown | 206 |
4 Bryan Woo | 198 |
5 Carlos Rodon | 198 |
#Name | W/L | % | $ |
---|---|---|---|
1 Laz Diaz | 14-3 | 82.4 | 1207 |
2 Adam Hamari | 14-4 | 77.8 | 1114 |
3 Nestor Ceja | 13-2 | 86.7 | 1189 |
4 Doug Eddings | 13-4 | 76.5 | 1092 |
5 Carlos Torres | 13-6 | 68.4 | 995 |
#Name | O/U | % | AVG |
---|---|---|---|
1 Alfonso Marquez | 13-5 | 72.2 | 9.9 |
2 Gabe Morales | 13-5 | 72.2 | 9.4 |
3 Lance Barrett | 11-6 | 64.7 | 8.8 |
4 Shane Livensparger | 10-5 | 66.7 | 10.4 |
5 Edwin Moscoso | 10-5 | 66.7 | 8.9 |
#Team | ERA | OBP | OPS | SO |
---|---|---|---|---|
1
|
3.61 | .305 | .677 | 1402 |
2
|
3.64 | .301 | .670 | 1392 |
3
|
3.79 | .305 | .687 | 1286 |
4
|
3.82 | .297 | .699 | 1221 |
5
|
3.82 | .305 | .698 | 1433 |
#Team | W/L | $ | HM $ | AW $ |
---|---|---|---|---|
1
|
96-63 | 2151 | 1180 | 971 |
2
|
77-82 | 1959 | -56 | 2015 |
3
|
87-72 | 636 | 922 | -286 |
4
|
81-78 | 438 | 487 | -49 |
5
|
94-65 | 362 | 999 | -637 |
#Player | AVG |
---|---|
1 Trea Turner | .305 |
2 Nico Hoerner | .301 |
3 Alec Burleson | .293 |
4 Freddie Freeman | .293 |
5 Sal Frelick | .291 |
#Player | HR |
---|---|
1 Kyle Schwarber | 56 |
2 Shohei Ohtani | 54 |
3 Juan Soto | 43 |
4 Pete Alonso | 37 |
5 Michael Busch | 31 |
#Player | RBI |
---|---|
1 Kyle Schwarber | 132 |
2 Pete Alonso | 123 |
3 Juan Soto | 105 |
4 Christian Yelich | 102 |
5 Shohei Ohtani | 101 |
#Player | R |
---|---|
1 Shohei Ohtani | 144 |
2 Juan Soto | 119 |
3 Francisco Lindor | 113 |
4 Kyle Schwarber | 110 |
5 Fernando Tatis Jr. | 108 |
#Name | Team | W/L | $ |
---|---|---|---|
1 Quinn Priester | MIL | 17-6 | 966 |
2 Robbie Ray | SF | 22-10 | 930 |
3 Janson Junk | MIA | 10-6 | 791 |
4 Cade Cavalli | WAS | 7-2 | 780 |
5 Randy Vasquez | SD | 17-9 | 725 |
#Name | Team | O/U | % |
---|---|---|---|
1 Sonny Gray | STL | 18-13 | 58.1 |
2 Logan Webb | SF | 18-15 | 54.5 |
3 Eduardo Rodriguez | AZ | 17-10 | 63.0 |
4 Jesus Luzardo | PHI | 17-13 | 56.7 |
5 Freddy Peralta | MIL | 17-13 | 56.7 |
#Player | Wins |
---|---|
1 Freddy Peralta | 17 |
2 Jesus Luzardo | 15 |
3 Matthew Boyd | 14 |
4 Sonny Gray | 14 |
5 Brady Singer | 14 |
#Player | ERA |
---|---|
1 Paul Skenes | 1.97 |
2 Yoshinobu Yamamoto | 2.49 |
3 Cristopher Sanchez | 2.57 |
4 Freddy Peralta | 2.68 |
5 Andrew Abbott | 2.80 |
#Player | SV |
---|---|
1 Robert Suarez | 40 |
2 Emilio Pagan | 30 |
3 Trevor Megill | 30 |
4 Raisel Iglesias | 28 |
5 Edwin Diaz | 27 |
#Player | SO |
---|---|
1 Jesus Luzardo | 216 |
2 Paul Skenes | 216 |
3 Logan Webb | 216 |
4 Dylan Cease | 215 |
5 Cristopher Sanchez | 204 |
#Name | W/L | % | $ |
---|---|---|---|
1 Stu Scheurwater | 13-5 | 72.2 | 969 |
2 D.J. Reyburn | 12-3 | 80.0 | 1092 |
3 Charlie Ramos | 12-4 | 75.0 | 944 |
4 Bill Miller | 12-5 | 70.6 | 1078 |
5 Jim Wolf | 12-5 | 70.6 | 1021 |
#Name | O/U | % | AVG |
---|---|---|---|
1 Doug Eddings | 11-3 | 78.6 | 11.1 |
2 Ryan Wills | 11-3 | 78.6 | 10.8 |
3 Bill Miller | 11-6 | 64.7 | 10.5 |
4 Clint Vondrak | 11-7 | 61.1 | 12.2 |
5 Chris Conroy | 11-7 | 61.1 | 10.6 |
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.