Too many baseball bettors are complaining that they lose too often while building their handicapping strategy on ancient statistics. This is like driving a horse and buggy and complaining that it takes you too long to get to work.
If you’re still comparing pitchers using ERA, or if you’re stuck analyzing hitters through their batting average alone, you’re going to lose more often. The industry has long since moved on from the beloved and boring stats of the 60s and 70s.
This post introduces the most valuable modern stats for people placing bets on baseball. You may luck out and win here and there by analyzing things stats like Quality Starts, but you’re working uphill. Follow the stats in this post and let go of your old back-of-the-baseball-card numbers.
What’s Wrong with the Old Stats?
For the most part, the old-school statistics aren’t bad or wrong, they’re just less accurate than figures worked out in the past few decades by baseball math nerds much smarter than you or me.
Take ERA, for example. A pitcher’s earned run average is a total of their earned runs divided by innings pitched multiplied by 9. All this does is give you a statistical average of how many runs a pitcher gives up across an average nine innings.
First off, I take issue with the concept of “earned runs.” This gives the pitcher credit for the defense behind him. Obviously, the pitcher has no influence on how the outfield plays, but that goes right into the ERA formula without a hint of irony.
People are absolutely stuck on ERA. It’s an important enough problem that I’ve been thinking about adding “following the wrong stats” to our post “The Top 9 Sports Betting Mistakes to Avoid.” Turn on a pro baseball game, and you’ll see this useless ERA stat more often than anything, besides maybe batting average.
Speaking of batting average – this is also a terrible way to handicap batting performances. A player’s batting average gives equal weight to a home run and a single. A player’s batting average completely ignores the value of a walk – which is significant.
According to batting average, a player who goes 1 for 4 with two walks that led to runs and a massive grand slam in the bottom of the ninth is just as valuable as a guy who went 1-4 with a meaningless infield hit in the first inning. They’re both .250 hitters if you go off batting average alone.
Was Bryce Harper’s .309 batting average figure in 2021 make him significantly less valuable than Trea Turner at .328? Not when Harper also led the league in Slugging% and OBP, lists on which Turner didn’t even crack the top-25.
Modern Baseball Stats to Give You a Handicapping Edge
In our post “Sports Betting Strategy (How to Win Money Betting on Sports),” we talk about ways to gain an edge against the book and the betting public. One way to do that is to analyze games and players from angles that most people aren’t using.
When everyone else is looking at ERA to handicap pitching performances, I want you to be looking at xFIP. When everyone else is looking at batting averages to handicap hitting performances, I want you to be looking at wOBA. I’ll explain both stats, and a couple more valuable stat-based insights that are publicly-available, below.
xFIP is a modified version of FIP, which stands for Fielding Independent Pitching. This takes the success (or lack of success) of a team’s defense out of the equation for pitchers. The “x” in front of xFip indicates that this model is a perfection of the old FIP stat – xFIP takes luck out of the equation by equalizing HR/fly ball ratios across the league.
Basically, xFIP is better than ERA because it gives a purer picture of a pitcher’s real skills in a sort of defenseless vacuum. It’s also easy to use, since the numbers work just like the old ERA numbers. An xFIP below 3 is amazing, an xFIP of 4 is about average, etc.
xFIP is predictive because, when compared to ERA, it can tell you whether a pitcher has been over- or under-performing. It’s impossible for pitchers to sustain a big gap between ERA and xFIP over any period of time, so a pitcher with a big gap between the two is more likely to have a “revert to the mean” type of game. The opposite works too – most pitchers’ xFIP reverts to their ERA, but you can clearly see when a pitcher is on a hot streak when you consider both numbers.
wOBA stands for weighted On Base Average. Under wOBA scoring rules, each method of getting on base is given a weight relative to how likely that method is to lead to a run. Basically, a single is worth the least, while a HR is worth the most.
I like wOBA because its formula changes from season to season, respecting the natural variance in pitcher and hitter performances over time. I also like wOBA because hitters who lead it tend to win season awards. To me, that says this formula clings closely to real-world performance. You can also look at entire teams by their wOBA scores and do a decent job of predicting playoff positions.
Do away with the old Runs Created stat – an estimate of a player’s offensive contribution – in favor of wRC+. This is Runs Created adjusted for various in-game factors. The formula is complicated, but it includes other advanced stats as well as things like “league runs per PA” and a literal ballpark factor based on weather and average crowd sizes and such.
Any time you see “+” in an advanced stat, that tells you the average score is 100. That makes these stats really easy to interpret. If a player has a wRC+ of 110, that means they’re 10% over the league average. A score of 90 would indicate that player is 10% behind the league average. I like how easy wRC+ is to read, and I like the additional insight it gives me into batting performances by individual players and at the team level.
Look at the top five players in wRC+ for 2021:
- Bryce Harper 170
- Vlad Guerrero Jr. 166
- Juan Soto 163
- Fernando Tatis Jr. 156
- Shohei Ohtani 152
That list is literally 10% MVP candidates and includes both eventual MVP winners (Harper and Ohtani).
As the season chugs forward, watch the wRC+ stat for a preview of the best hitters in the league, a much more reliable way to judge hitting power than batting average.
The simplest of all the advanced stats, in my opinion, P/PA is pitches thrown per plate appearance. It’s elegant, in that you can explain it to a fan in a few seconds, and in that it can be used for both pitchers and hitters. You can also work this stat out on your own, though it’s publicly available, for free, all over the Internet.
You can’t get too caught up in a hitter or pitcher’s P/PA number. You have to translate it a little. Think about it this way – a hitter with a high P/PA number may not produce as many runs as one with a low one, but that hitter is going to wear out starting pitchers a lot faster, which can be a huge element over nine full innings of play.
I find myself using P/PA most often in first five innings bets, when I’m looking for situations where a starting pitcher is likely to get pulled long before the traditional fifth inning exit. This can influence me in either direction – backing or not backing an MLB F5 wager due to the likelihood of a starting pitcher’s second- or third-inning pull.
I contend that sportsbooks make more money off baseball bettors than any other sports. That’s true in Las Vegas, where annual revenue reports show that casinos have a slightly higher edge against MLB bets than any other major sport. I’m pretty sure that the betting public’s fixation on boring old-fashioned stats is partly to blame for this edge.
If you focus on new stats, advanced metrics for performance that focus better on individual player performance, you can get a leg up against most other baseball bettors. It may be enough to help you win your baseball bets a little more often.