How the Reds did it: First-half run production

Winning baseball games comes down to a simple formula. Score more runs than you allow. Teams accomplish that with different balances between hitting and pitching. For example, the Reds had excellent run production in the first half of 2021. At 4.83 runs/game (R/G), they rank third in the National League in making runs, trailing only the LA Dodgers and San Francisco Giants. The average NL R/G is 4.35. The Brewers (4.28), Cubs (4.20) and Cardinals (3.98) are below average.

What went into the Reds success in producing runs the past three-and-a-half months? The stats below isolate the run production contribution of each player broken down into the three important run production components: (1) Hit Skill, (2) On-Base Skill, and (3) Hitting for Power. We’ll conclude with analyzing a few composite stats.

Hit Skill

The first data column in the Hit Skill chart is back-of-the-baseball-card Batting Average (BA): the percentage of times a batter reaches base on a hit. BA has been criticized by the saber crowd and it’s important for context to understand the reason for that. It’s not that BA doesn’t tell us anything, it’s that it doesn’t tell us nearly as much as old-school guys usually assert. Think of the countless times someone has said “Player X is having a bad year, he’s only batting .230.” For decades, baseball commentators used BA as the be-all, end-all representation of how well a hitter performed.

But most analysts now understand how incomplete of a measurement BA is. First, it treats all hits the same, with the batter getting no credit for power. Second, it doesn’t count walks. While walks aren’t as valuable overall as singles, they are a lot closer to singles in value than zero. So while BA can tell us something useful about the difference between Joey Votto and Mario Mendoza, it’s limited.

The first column are the Reds batting averages at the All-Star break. League average BA is .240. The last time Pete Rose won the batting title in 1973, league average was .257. When the Reds won the NL Central in 2012 it was .255. Lefties are hitting .236 and right-handed batters .243. That gap is attributable to the shift’s disproportionate effectiveness against LHH.

Nick Castellanos and Jesse Winker are having great BA seasons by just about any standard. Tyler Stephenson, Jonathan India and Tucker Barnhart have also hit well above average. Eugenio Suarez is at the extreme other end.

The second column lists a more modern statistic — expected batting average (xBA). For time immemorial, baseball broadcasters have commented on good and bad luck for hitters. They’ve described “at’em” balls hit right at fielders. There were names for ground balls that snuck through the infield. They had accounts of individual plays and might remember back an at bat or two, but no one could measure and no one kept track of season-long stats for those situations.

You never heard “Gee, Davey Concepcion has had 36 balls hit hard and right at fielders this year and 21 soft grounders or bloops that fell in as hits.” I guess we assumed those good luck and bad luck events evened out over a short period of time, maybe even over a game or two. Now we know they didn’t.

In the Statcast Era (2015-present), we’ve been able to produce good estimates for that luck over time and kept a record. It turns out batters sustain good luck or bad luck for long stretches of time — maybe entire seasons — before it gets evened out.

What xBA expresses is the batting average the player would have if his batted balls fell in for hits at the rate typical for the way he struck individual baseballs. If Player A hit a ball at an exit velocity of 102 mph and a launch angle of 29º, xBA gives him a hit-probability credit for the typical outcome of that kind of struck ball. It goes a long way to neutralizes defense, park dimensions and just plain luck.

For the Reds in the first half, xBA closes the BA gap between Castellanos and Winker, but both are still having excellent seasons. Look at Nick Senzel’s xBA. Yes, we’re dealing with a small sample size (124 plate appearances), but Senzel hit the ball well (.307 xBA) when he was healthy. He deserved about 55 more points of batting average. Of all Reds hitters, he’s been the most unlucky. Both rookies at the top have been a little lucky. Tucker Barnhart has been extremely lucky. His BA is more than 10% better than average but his xBA 10% below. Mike Moustakas’ batting average was also lucky.

BA and xBA are both measures of the “hit skill” component of run production. Neither incorporate power or walks.

On-Base Skill

Beyond striking the ball for hits, batters can produce runs by drawing walks. Several stats get at this particular skill. BB% is the percentage of plate appearance that the batter walks. That’s a direct and complete measure of the on-base skill that’s in addition to the hit skill. Another way to measure on-base skill is how often a player chases pitches out of the zone. O-Swing% measures the percent of pitches out (O) of the zone the batter swings at. It’s often called the chase rate.

The OBP column is the percentage of plate appearances the batter gets on base. That’s hits plus walks plus HBP. One of the big early insights of sabermetrics and Moneyball was that OBP more closely correlated to run production than was batting average.

League average BB% is 8.9% and O-Swing% is 31.0%. India, Stephenson and Votto have been superb with on-base skills in the first half. Most of the rest of the team is either average or below. Nick Castellanos and Tyler Naquin have extra-high chase rates and their walk rates reflect it. This is one of Kyle Farmer’s weakest areas.

In terms of OBP, league average is .316. The Reds as a team rank second (.330) behind only the Dodgers.

India, Winker, Stephenson and Castellanos have put up spectacular OBP numbers. Of course, they’ve gotten there in different ways. Castellanos get on base mainly through batting average while India and Stephenson have plus walk-rates and batting average. Only one Reds player has had a horrible OBP — Eugenio Suarez.

So far, none of the statistics have given the players credit for power. None of the above stats weigh an extra-base hit more than a single. BA credits a home run the same as a single. OBP credits a home run the same as a walk. But that’s all those stats are meant to do. Other stats account for power. Let’s look at a few.

Hitting for Power

The primary old-fashioned “power” stat is Slugging Percentage (SLG). Its formula is simple. You take the batter’s total bases (single=1, double=2, triple=3, homer=4) and divide that by the number of at bats. When you see a standard “slash line” stat, the final number is SLG. So if Player A has hit .250/.350/.450, his slugging percentage is .450.

But there’s a huge weakness in slugging percentage as a measure of power hitting. It implicitly includes singles as a positive indicator of power.

There are different ways to get to a .450 SLG. Player A whose batting average is .350 and Player B whose batting average is .250 can both have SLG of .450. But Player A gets there with a bunch of singles, where player B gets there on extra-base hits. It’s not that the singles are worthless. It’s that they aren’t an indicator of power, which is what SLG purports to measure.

So, a nifty and simple way to isolate the power component of SLG is to subtract the player’s BA. That leaves extra-base hits. In other words, power. That stat is called Isolated Power (ISO). It measures how often a player hits for extra bases. Player A with a .350 BA and .450 SLG has a .100 ISO. Player B in the example above has an ISO of .200. Isolated Power makes it obvious which players have hit more often for extra bases.

League average ISO in 2021 is .162. The Reds have a bright dividing line between those who have been above and those who have been below.

The second column lists average exit velocity (EV). It’s another way to measure power. Other things equal, the harder a ball is struck, the more likely it will produce a power outcome. On the one hand, other things aren’t equal. A player might hit the ball hard, but hit too many ground balls to have a bunch of extra-base hits. On the other hand, ISO is dependent on actual results, so influenced by defense, positioning, park dimensions and luck. EV is independent of those things.

Which is better between ISO and EV? Neither. They measure different things and as long as you know what those things are and how they are different, you’re OK. Note that Joey Votto leads the team in average exit velocity.

Wouldn’t it be nice if we had a stat that took every ball struck by a player and assigned it the typical number of bases similarly struck balls achieved over the past few years? Such a stat would neutralize defense, positioning, park dimensions and even luck.

Well, that’s what the awkwardly named stat xwOBAcon does. The “x” means “expected” which how you know it assigns typical outcomes instead of specific ones. The “w” is for “weighted” which means extra base hits are given more value than singles or walks. The “con” stands for “contact” which means it looks at only plate appearances where the batter makes contact. It ignores plate appearances that ended in walks, strikeouts and HBP. League average xwOBAcon is .364.

What xwOBAcon lacks in elegance, it reaps in precision for measuring a player’s power-hitting skill.

Again, xwOBAcon isn’t meant to be a comprehensive measure of a batter’s run production performance (we’re getting to those). It isolates the batter’s skill at hitting for power. This is another metric we’ve only had since Statcast, when we’ve been able to measure exit velocity and launch angle with accuracy. As you can see with the Reds batters, it lines up well with the other power stats. Votto gets credit here for smacking the ball around the past three months. His xwOBAcon is almost as high as Nick Castellanos.

We’ve now looked at various measures for hit skill, on-base skill and hitting for power. Those are the three important components of run production. Now let’s look at stats that put it all together.

Composite Stats

Each of the three stats in this chart accounts for batting average, walks and weights for hitting for power.

wRC+ (weighted Runs Created plus) compiles all those skills and puts them on a scale where 100 is average (that’s what the plus tells us). Each point a player deviates from 100 is a percent he’s been better or worse than league average. Nick Catellanos, with a 156 wRC+has been 56% better than average in run production. Eugenio Suarez has been 32% worse. The offensive contributions of the two rookies stand out here, both 20+ percent above average.

wOBA (weighted on-base average) is exactly the same as wRC+ except it’s on a percentage scale like BA/OBA/ISO/SLG. That’s why there’s no daylight between the rankings in the first two columns. They are mathematically redundant. The reason I added wOBA to this chart was to juxtapose it to the column on the right, xwOBA (expected, weighted On Base Average).

xwOBA adds the “expected” aspect to wOBA (and wRC+). The stats in the first two columns are based on the specific outcomes the players experienced. The last column shows neutralized defense, park factors and luck. Unlike xwOBAcon, it does include a player’s walks and strikeouts.

So, the difference between the middle column and the right column is how lucky or unlucky the batter has been, both in terms of batting average and power (it’s ‘weighted’). Nick Castellanos has been about 15 points lucky. That’s a modest difference. Jesse Winker has been about the same amount unlucky. Same with Joey Votto. Mike Moustakas and Tucker Barnhart have been quite lucky and Nick Senzel quite unlucky.

Both wRC+ (you can find at FanGraphs) and xwOBA (at Baseball Savant/Statcast) are powerful composite stats. They include a huge amount of information about how a player has performed. If you’re looking for a single stat to measure a player, either would do. Which is better? Again, there’s  no reason to judge that. Just know that wRC+ (or wOBA) measures what happened without factoring luck, where xwOBA subtracts luck.

Also, while there are good composite metrics, to have an in-depth understanding of what a player has done, it’s almost always better to look at more metrics than fewer.

 

Photo: Joe Robbins (Icon Sportswire)