MLB Daily

Today is March 28th (Sunday) so with MLB officially opening on April 1st, there are 4 days left of games with no relevance. We need to shift gears from team previews to getting ready for team analysis and player analysis. It is always good to have an understanding or context about what should happen, but then there is the truth of what happened which is where we need to get our thoughts and minds thinking as the season opens.

Get the spring training results and performances out of your head immediately! Using data from the spring or correlating that data to your handicapping is a fatal flaw for early season wagering. Spring training is exactly what its title implies. It is a training period to get players ready for the 162 games daily grind that is an MLB season. Players have not yet had their adrenalin raised to the levels of the season. They have not played in games where the results matter in the standings. Most of them have yet to face the pitching quality of an everyday major leaguer so the results that have been obtained are truly meaningless. Here is a good example of what I mean. Baseball-Reference has spring training stats like many other places, however, they have a column OppQual. This column represents the average quality of opponent faced in spring training. The value 10 is that of an MLB regular. The value 8 is that of a AAA player. The value 7 is that of a AA player and 5 is that of a high A player. Most people do not account for the level of player faced when looking at results, so this could be eye-opening for some. The chart is of hitters but there is a chart for pitchers as well.

I chose to list the top 20 in hits for the spring which also should show high batting averages. The 3rd column after the player’s name is OppQual. Notice there is not one 10! There is only one above 8! The majority of this data is based on many MLB regular starters batting against non-regular MLB level talent. We have all seen and heard about Shohei Ohtani’s success, but look at what he has faced. He has faced opponents with an average of 5.9 OppQual which is not much higher than an A minor leaguer! Please do not get fooled. Do not evaluate what has happened in spring and correlate it to the 2021 season.

The data we should be using is from the last month of the prior season or projections of 2021. They will be more accurate for the first few weeks until we get enough data to rely on. Team batting data I use once there are 7 games into the season, so we don’t have long to shift into gear to get the right data we are looking for. Starting pitchers take longer (30 days) but we can use specific information to help us. Relief pitchers are a team stat as well, and only need 14 days to get going. We need to be ready to accumulate from day one.

We can not use data from day one that will allow us to be successful for day two, but over the first week, we can use data that will help us from week 1 to week 2. MLB is a daily grind for a handicapper too. We need to be shifted from passing the days with team previews to hunting and accumulating data we can use to make money. The start of a new season is invigorating, exciting, and fresh. It is also truth-telling in the sense that your life has just taken a turn regarding the daily commitment level required to comprehend, project, and acquire the data required for analysis of the sport. It is unrelenting. It is every day. MLB originating is not for everyone. You can enjoy the sport, make bets as you like, but make sure you know where you stand. Follow an originator or be one yourself, but know what you are getting yourself into.

MLB 2021 starts on April 1st. There are 30 teams that play 162 games each so there are 4860 games to be played. The key is to remember like no other sport MLB is a daily grind. You don’t have to bet every game and there is another slate of games tomorrow. It is exciting when MLB opens the season. We wait all winter to have MLB back. The first tip is not to lose all your money in the first weeks of the season. Every season takes on its own identity. Some seasons require underdog betting, others first five innings, then others a need to be the run line. Each season requires an adjustment for the person making the bets, so don’t bet so much that you don’t have money to wager in September as it will only be April!

Tip #2 is no matter whether a team played well in Spring Training or played poorly, those games didn’t count. Throw the records out! Do not let Spring Training influence the regular season. This is true of teams and players! Hot teams are now 0-0 and all players will have no innings pitched and no official at-bats. STL Matt Carpenter is 1-33 batting .030 and BOS Bobby Dalbec has 7 HRs this spring! The KC Royals are 14-7 and the TB Rays are 8-15. None of this matters, not even a little bit! Do not get influenced by this. It is a better practice to always use the last 30 days even when it goes back to last season! Those are real games with MLB quality players and pitchers playing every inning.

Tip#3 pay attention to COLD weather situations. As teams break from warm Florida and Arizona, they often find their home cities to be rather cold. It is not uncommon to see 40-degree weather for a week or two. This matters! The chart below shows the impact of cold weather and hot weather on baseball. It is simple, less than 49 degrees equals less offense, therefore less scoring.

Tip#4 There is no more important time for regression to the mean than the beginning of the season for starting pitchers. I am using the terminology of “regression to the mean”. This is copied directly from a Google search. “In statistics, regression toward (or to) the mean is the phenomenon that if a variable is extreme on its first measurement, it will tend to be closer to the average on its second measurement—and if it is extreme on its second measurement, it will tend to have been closer to the average on its first.” Think in terms of outliers. Going in a direction more extreme than another, the outlier is not the mean (average bar). Humans are not machines and have progression and regression toward the mean. If we could gauge those “outliers”, then we could bet on those opportunities they present. The beginning of the season presents us with starting pitchers establishing their mean averages. The regression to the mean indicates we need to identify the starting pitcher’s good, medium, and poor starts. In his first 3 starts, he should have one of each. It could carry into his 4rth start but usually, a pitcher hits all the levels in his 1st 3 starts. This is a HUGE edge.

Tip#5 Keep an eye on pitch counts. Starters will throw 110-90 pitches per game in a season. However, in the beginning, they may not be ramped up to that level so they’re only allowed to throw 60-90 pitches in a game. Try to identify those pitchers prior to their games. It is important to know if a starting pitcher is going to throw 5-6 innings or only 4-5 innings. An average pitch count per inning is 15. If you take 15 pitches times the number of innings, you can approximate the number of innings a pitcher will throw. This is helpful knowledge for “In-Game” wagering spots. For example, a pitcher might be at 45 pitches through only 2 innings, yet he has not allowed a run. He is 15 pitches over the average so he will likely not throw 6 innings. 6 innings is an average based on 6 innings x 15 pitches to get 90 pitches thrown. Based on this knowledge, we can assume the opponent will have a good chance to get to the bullpen quicker than expected, thus they will have an edge later in the game, which might be something we want to wager on.

Tip#6 Streaks are something to ride anytime but during the start of a season, they seem to be more defining than later. How many times does a team start 10-0 or close to that? Or a team doesn’t win their first game until they have played 8 games. The point here is not to guess when the streak is going to end but to play on the streak until it does end. We can make money in the middle of streaks and need to back off, but still, ride the streak once it gets to be an extreme outlier. An example of this would be to see a team go 9-0 to start a season. We can make money from games 3 through 5 or 6. The sportsbook will start to ramp up their lines on the streaking teams, so we need to capitalize in the middle of the streaks and not pay the extra prices tacked on later!

Tip#7 Do not use trends this early. Trends should be compiled from current season data and not from historic data. Since there is no data, no trend analysis should come into play. An example is not to worry about how a team hits left-handed pitching at the start of the season. The data if used is would be from season past and not relevant to 2021. Later in the season, this trend of information can be useful.

Every season projects a certain way before spring training starts. There are “battles” for positions, veterans who are brought to compete for jobs, and young talent looking to make their own path. As spring training settles in and there is only a week until opening day, I made a list based on Roster Resource of players who project to make the team. These are the interesting ones in my mind. The American League headlines with veterans Matt Harvey (BAL), Mike Foltynewicz (TEX), and Julio Teheran (DET). There are young players too like 1B Bobby Dalbec (BOS), Andrew Vaughn (CHW). The National League list has Aaron Sanchez (SFG), Matt Moore (PHI) as veterans, It has young players like 2B Jazz Chisholm and 2B Jonathan India (CIN).

Opening Day is 8 days away on April 1st! Time to be getting excited for sure. There are so many dynamic young players, 95+ pitchers, and quality managers. There were great off-season moves to excite fan bases in cities like San Diego, Chicago, and Toronto. This could be an amazing season! We need to follow closely the news and notes now that we are coming to the end of games that don’t count in the records books.

Unfortunately, there are injuries we have to deal with. I have compiled a list of them where some are impactful and others not so much. I have left off players that should not impact teams much at all.

There are still position battles left. We need to consider the position, the team, and the situation too. For example, DET has Boyd, Teheran, Skubal as for sure starting pitchers that have made the rotation. They also have Turnbull who will be on IL so they really only have a rotation spot left. Again, the Tigers will use lots of pitchers so is there much meaning to the opening day roster? The answer is not really.

The ATL Braves are trying to figure their #5 starter. It will be easy to align the staff when Soroka comes back, but they need to pick one from Wilson, Ynoa, or Toussaint. The NYM, PHI, and WSN will also have to fill out their rotations. Keep an eye on things that will delay starts like with DET Spencer Turnbull having Covid. It is not only his missed time but his build back up we need to see be right.

We need to look at situations that become created for someone else. An example of this is OF Harrison Bader. He will miss 6 weeks so Justin Williams and Lane Thomas could get some playing time early in the season. OF George Springer may not be ready for opening day. He is an impact on the offense and on the team series with NYY.

I will go look to update this again in a couple days.

As the market continues to move, the season wins total lines are moving around too. I have seen some of the books go to a season win percentage as well instead of season win totals. It is important to know what you are wagering as well. This market is not for the person who wants a quick turn around. The bets pay off roughly 6 or 7 months after you make them! Anyway, There are still a few I like so I will list them.

Boston Red Sox Las Vegas odds 80.5 Play OVER

Chicago White Sox Las Vegas odds 91.5 Play UNDER

*Kansas City Royals Las Vegas odds 72.5 Play OVER

Oakland A’s Las Vegas odds 87.5 Play UNDER

Atlanta Braves Las Vegas odds 91 Play UNDER

*St. Louis Cardinals Las Vegas odds 85 Play UNDER

*= Favorite plays

The NL Central will be won by a team at or around .500 and I have MIL as the best team in the division. STL is the largest Vegas line. This is an appealing situation! The BOS Red Sox are the 9th best offense in MLB over 2019-2020. Their issue was pitching in 2020. They have their manager back, and their #1 pitcher Rodriguez. They also signed Garret Richards. I expect this team to be way more competitive this season. The KC Royals are a team that made some intriguing off-season moves plus they have solid young starters. This is a team on the rise. OAK may not be the best team in the AL West! I do not like HOU either. I like LAA and their win total is 83.5 which means OAK should be in that same area. The CHW are a hype machine! They have not done anything yet, and everyone thinks they are the 2nd best team in the AL. The NL East is a division where all the teams will beat each other up. ATL is the outlier high so they become an Under wager.

Yes, BABIP is simple when it comes to what it is. It is batting average on balls in play. The league average is around .300. In 2020, the average was .297. A batting average equivalent was .245. To a degree, the specific number is useless because we need to know the context meaning of the stat. Why is BABIP important to handicapping a baseball game?

The answer is in regression to the mean and defining BABIP in another way. Let’s define it so we can use it. A batted ball in most cases does not have an aim from a batter. There are occasions when batters are trying to directionally aim where they hit the ball, but most times the ball comes off the bat in any direction. A pitcher tries to affect where the batter hit the ball too. They pitch inside or outside, up or down intending to miss the large part (barrel) of the bat thus the batter makes weak contact. We see this in pitch sequences over and over. BABIP is an average on balls hit in play. It is random, where batters hit the ball, thus we can interestingly use this stat.

I used to think this was a stat for the quality of batters, however, it really is not. If a batter does not control where he hits the ball then he cannot control his BABIP either. This is where we can use it. All players will not have the same success as the rest when they hit the ball somewhere. Some will hit groundballs to fielders, or flyballs to fielders more often or less often. Over the course of a huge number of at-bats, the BABIP for all players would be very close. Over the course of shorter terms, we can see the variations in BABIP from player to player. These are the outliers we are looking for! Oh, yeah. We are going to use BABIP for pitcher performance too!

Pitchers have opposing hitter data like avg. or GB% etc., and they have a BABIP. A normal BABIP we identified was .297 or around .300 so we are using this number as the mean average. What if we see a pitcher with a BABIP of .385? Does this mean the pitcher is not good? What if his BABIP was .245? Does this mean the pitcher was excellent? The answers are exactly the opposite of what you might think. The better over the mean average like .385 from above means the pitcher is unlucky. The balls batted against him are not being hit to fielders. It does not mean the pitcher is a poor pitcher, and because he has been unlucky, we know that this temporary, and his BABIP will sink closer to the average. He should then see some games where balls are hit to fielders thus evening out his overall BABIP. Let’s say this another way. The pitcher has been unlucky to earn a .385 BABIP, thus he should be getting more outs above the mean average to compensate for the .385, therefore he will see better results and we can bet on that! It applies the same way when below the average. If a pitcher has a BABIP of .245, he has been very lucky having most of the balls put in play hit to fielders. His luck will change with time to get closer to the mean average of .300, which means he will see a worse performance. We can bet on that too! We have now found a way in which we can predict a spot where either good or bad performance can be expected. We need to use this with caution. This is not how we make wagers but we can use it as data to influence our thinking. It is a supporting data point to improve a narrative you have or disprove one, it is not a valid enough data point to stand alone to make a wager.

BABIP helps identify pitchers who will perform a certain positively or negatively. When combined with other data points, BABIP is a strong influencer. We need to look at the hard-hit rate as well. The higher the hard-hit rate is, there is the chance the BABIP will be above the mean too. If a ball travels more than 95mph off the bat, it is a hard hit. The fielders have less chance to get to (range) these balls as they were hard hit past them. These are scenarios where there is a logical reason for the poor BABIP performance and it is not an outlier. Anyway, the point is to understand the luck of where a batted ball is hit; whether at a fielder or not, and over time will even out creating opportunities in predictive outcomes.

A MLB season consists of 162 games for each team. Each team in a division plays the other division rivals 19 times each. The season starts in late March or Early April and regular season games end in September or early October making the season 7 or 8 months long. MLB has the most difficult standard of making the post season of any sport. It allows only division winners plus two wild card teams. The back story about the season, games, and opponents is important because we must understand and value (not underestimate) the nature of the game being played as a daily grind. Their are 81 away games so players and coaches will travel to multiple cities. They stay in nice places mind you so it mitigates wear on the body in the sense of sleep derivation or dealing with rough conditions.

The grind brings into play the importance of current performance and current conditions. Teams and players will go through periods of time when they are above their mean average and below, thus will have extended winning streaks and losing streaks. When handicapping this is vital knowledge. There many “old pros” who want accumulated data to ensure and verify the data is as accurate as possible. MLB is not the sport for that. Shorter trends in performance are more valuable than longer ones! Look at it this way. Let’s say SF Giants have a .440 winning percentage and we are in June. They have just come off a series where they lost 8 or their last 10 games. We hare handicapping their next game and they play COL who has a winning percentage of .400. COL has won 6 of their last 10 games. When comparing the teams, do we use the season long information or would it be more accurate to only include the shorter term data?

The answer has two parts. The overall team performance is something we need and utilizing the winning percentage accomplishes that. I use BaseRuns win/loss percentage (another subject for another time). We can give the team a base strength this way. Now comes the hard part. We do NOT analyze the players that way. We want to capture and use the nuances of the season to our advantage. We do this but analyzing data by time periods for players. Starting pitchers is last 30 days. The reason is using his last 5-7 starts will provide us the info we need to then compare to his season to date results giving us the ability to use the performance variations to our advantage. When looking a hitting data, I use last 7 days. I know that seems very short and it is, just remember we don’t care what this hitter did in April because we are handicapping a game in June. His April is gone and will not in anyway effect the outcome today. Seven games has been the right target to capture enough data to make it real yet still capture those variations we are looking for. I only use the same time period for relief pitchers. They do not throw everyday, but they do throw 3 or 4 times and week. Each area can have above and below performance outliers. The hitting maybe doing above average whereas the starting pitching may be below average for example.

We need to identify streaks not only the obvious winning and losing ones. Our edge will be getting on the streaks whether the team/player is going good/bad as soon as we see the variations. The sportsbooks take time to get their lines adjusted to these outlier performance variations. We want to ride the streak! Play on above-average performance and play against below-average performances. DO NOT think you can predict when the variations will stop. You can miss an opportunity if quit riding the streaks too early. Keep in mind the sportsbooks will gain knowledge and adjust the betting line to reflect streaks too. The longer one goes, the more juice to bet into there will be. Performance variations are expected and a normal part of an MLB season. They are our friends. Treat them well and they will reward you.

The last look at velocity year over year changes in spring training was 03/09. I took another look into this morning. A couple of new guys on the list and a couple dropped off the list. Interesting to note there are more dramatic changes in velocity gains than in losses. Newly acquired Mike Foltynewicz of the Texas Rangers is one of those. In ATL last season, he could not keep his job. Ultimately he was released. He is known for be a hard thrower with a career avg. of 96 mph. He could not velocity up over 91 mph last season and became expendable due to getting hit. It is possible TEX found a gem here because this spring he is averaging 94 mph and a gain of 3.4 mph! LAA Shohei Ohtani looks to be in a similar position. He has gone from 93.8 avg. fastball to 97 this spring. He has also hit well! The list is below.

Umpires can have an effect on MLB games. Each one has his own strike zone thus there will be trends regarding walks and strikeouts. Just like looking into any trends, it is important to weigh it accordingly. I have seen plays solely based on Umpire trends which is ridiculous. No more so than basing a play/wager on any other trend. We do want to ride streaks such as winning and losing streaks, or hot scoring offenses or cold ones, so we must be good at identifying trends and streaks.

Gamblers look to find any edge they can get. It should be no surprise that umpires have gimbling stats! Their stats include Home Team wins and losses, average total, walks, strikeouts, and more depending on where you get the data from. The chart below is a sample form last year.

The premise of ANY trend should be to validate or further solidify reasoning that supports a position in the game. For example, let’s say you like Over 9.5 runs in a game. You find that Cory Blaser is the Umpire. He has an avg. total runs scored 10.36 in his games. This trend is supporting your Over premise. We cannot just take this information and play over based on the total trend for the umpire. Keep in mind, these trends do not show what games he was part of. We do not know if he was in hitter-friendly stadiums or if he was part of some kind of crazy scoring games that skew the data. We can look to see if there is justification for runs being scored due to his strike zone. This is the important part.

A small strike zone means less balls in the strike zone and more balls out of it therefore there should be more walks. The more guys on base creates more scoring opportunities hence there should be a higher total. This works opposite as well. The larger a strike zone is the more strikes thrown thus more strikeouts. This creates less guys on base and lowers the scoring opportunities. These are logical reasonings for the total average which in turn creates legitimacy to repeatable future strike zones, thus consistency in totals markets for this umpire.

A couple of thoughts. One, do not ever make any wager solely based on a trend no matter what that trend is. Two, a trend only has value if there is some reasoning to it which can make it repeatable for a reason. For example, Team A might have won 6 Weds day games in a row. Is that a repeatable/reliable trend? Maybe? Look deeper. Wednesday are get away days. It means teams tend to play early day games so they can fly out to their next city that night and play a game on Thursday night. An origination or manager may be very good at motivating his team in these games. They might be specific “go after” to win type games where the organization has identified to attack these spots to win more games. If you can find reasoning like this, then yes these are repeatable and reliable trends. However, more often than not, you will not be able to support the trend with legitimate analysis. Three, make sure you know if you are betting a streak or a trend. Baseball is a game of streaks over the course of 162 games. We need to ride streaks. Do NOT blindly ride trends!