MLB Betting Trends

MLB Betting Trends

Betting Angles and Trends

Michael Rathburn

 

My goal with this article each week is to look at a segment of baseball handicapping data and the results from a Vegas perspective. This will be helpful not only in your handicapping, but your DFS play as well. I’m also going to point out any observations that I found during the week in which you can learn from in the future.

 

Last week I hit every major league team with a short capsule of their trends in the first week and many of them have carried through week 2 especially the Mariners and Rays. I have bet the Rays every game this season with the exception of the Astros series. This team is for real and still represents value in the market. The Mariners are the same, but I like their offense more than their pitching.

 

Week 2 was much different so I decided to dig into the totals and see what is happening.

 

It has been a wild week where the pitching has been unpredictable and runs are being scored in boat loads.  That was my gut feel, but when I dug into the data; there was confirmation.

 

Week 1 (93 games March 20-April 3)

 

Home Team Total – 4.2

Road Team Total – 3.9

Favorite Team Total – 4.4

Dog Team Total – 3.7
Average Total – 8.1

Average Runs per game – 8.6

Road Team Runs – 4.0

Home Team Runs – 4.6

 

Over/Under – 45/47/1 (push)

Favorite/Dog – 51/42

Home/Road – 51/42

 

Week 2 (87 games April 4-April 10)

Home Team Total – 4.3

Road Team Total – 4.2

Favorite Team Total – 4.6

Dog Team Total – 3.9

Average Total – 8.5

Average Runs per game – 10.2  

Road Team Runs – 5.2

Home Team Runs – 5.0

 

Over/Under 47/36 (higher percentage of games went over in week 2)

Favorite/Dog 55/32 (higher percentage of games won by favorites in week 2)

Home/Road 48/39 (same percentage as week 2)

 

You can see the huge jump in average runs per game and road team runs. This was also attributed to games at Coors and Camden Yards this week vs. none last week. But still, this is a significant bump in runs scored and it was reflected in DFS play with many starting pitchers getting blown up.

 

There were two games in Kansas City that had a total of 10. KC is normally viewed as a pitchers’ park with totals never higher than 9, but Vegas has adjusted run totals in Mariners games but at least 1 run upward.

 

Teams that have also seen higher than normal game totals – Astros, Angels (5 out of 6 went under), Athletics (10 home games avg total 8.6; 7 out of 10 went UNDER).

 

The A’s are interesting because the high game totals were based on the perception that their starting pitching was not good but the park will always be an extreme pitchers’ park based on the amount of foul territory. They allowed 3.2 runs in the 10 games at home with 5 games of 2 runs or less. They were dogs in 7 out of 10 games and won 6 of them. Keep an eye on the A’s at home when they are dogs moving forward.

 

The next step is to look at games in buckets. I put the games into 8 categories (O=Over, U=Under, F=Favorite, D=Dog, H=Home, R=Road)

 

Here is how often each winning scenario happened so far through 2 weeks.

 

OFH (Over/Favorite/Home) – 28

OFR (Over/Favorite/Road) – 24

UFH (Under/Favorite/Home) – 39

UFR (Under/Favorite/Road) – 13

 

The numbers skew towards favorites which is to be expected, but also towards the under at home.

 

ODH (Over/Dog/Home) – 18

ODR (Over/Dog/Road) – 22

UDH (Under/Dog/Home) – 12

UDR (Under/Dog/Road) – 19

 

Even though it is only a sample size of one week, we can see the trends starting to take shape. Betting baseball is tough because once the money line starts to creep over -150, it becomes a risky proposition. When looking at taking underdogs, you want to find home dogs in the +100-150 range with totals of 8 or less. This is also a good strategy to look at in DFS when you research for the SP2 or a GPP pitcher that will be under-owned.

 

I like to also look at the distribution by individual game totals

 

6.5 – (9 total); 5/4 under; 5/4 dog; 6/3 road (Small sample size, but trend here is taking road dogs in low total games)

7 – (25); 16/9 over

7.5 – (26); 14/12 over

8 – (29); 17/12 under

8.5 – (40); 21/19 over

9 – (29); 16/13 under

9.5 – (13); 7/6 under

10+ – (9); 6/3 over

 

Sometimes when you mine data, there is not enough of a story to tell. That is the case when I look at the totals and over/under. The one thing that does stick out is the high number of overs in games with a total of 7.

 

Next week, I will jump back into the team trends.

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