The well known triple slash line is a familiar starting point to talk about hitting stats. And I will compare anonymous slash lines from 2022:
- Player A: .298 BA / .343 OBP / .466 SLG
- Player B: .257 BA / .330 OBP / .476 SLG
- Which of these two players was the better offensive player in 2022?
Player A is Trea Turner and Player B is Kyle Tucker. The OPS is .809 and .808, respectively (minimal difference). Tucker leads in wRC+, 129 to 128 (also minimal difference). Tucker also leads in OPS+, 128 to 121. The wRC+ and OPS+ stats are park adjusted, and park adjustment appears to be the basis for switching the positions of Turner and Tucker.
Overall, I think the fair answer is that Turner and Tucker had approximately the same offensive value in 2022—particularly if we confine ourselves to the values in the Player A and B comparison. If we look outside those absolute values and consider park adjusted factors, it is possible that Tucker has a slightly higher value.
But some people might look at this and give the “tie” to Turner because his batting average is higher than Tucker’s. In my opinion, this would be wrong. The effect of batting average is included in OBP (on-base percent). You only need OBP and SLG to arrive at a batting value.
Batting average is an over-valued statistic and simply isn’t necessary to determine offensive value. Unlike OBP, batting average doesn’t account for Tucker’s higher walk rate (9.7% compared to Turner’s 6.4%). Batting average doesn’t account for the fact that a larger proportion of Tucker’s hits go for extra bases (9.7% to 9.0% x-base hit%) and HRs (Tucker requires 40% fewer at bats to hit an equivalent number of HRs as Turner). Batting average is so ingrained in the history of baseball that many people simply assume that the higher batting average player is the better offensive player. My contention is that some people may be undervaluing Kyle Tucker because they think his batting average is too low.
Tango (co-author of The Book: Playing the Percentages in Baseball) has tweeted similar player comparison polls and became frustrated that most of the fans would select the slash line based on batting average. He repeated the exercise on twitter with an advisory telling readers the correct answer, but some people continued to pick the higher batting average.
Let's try this one last time. Make sure to select the third option if you want to be right. Remember, the THIRD option.— Tangotiger (@tangotiger) January 9, 2023
Which is the more productive batter (all other things equal)
.315 batting average
.260 batting average
If you doubt my suggestion that batting average is over-valued, I recommend a recent Fangraphs article by Ben Clemens (“Triple Slash Line Conundrum: Voros McCracken Edition”). He ran multivariate regression analyses of team runs scored vs. batting average, OBP, SLG, and OPS. The analysis shows that batting average is not useful in explaining run scoring. As he states:
Run Expectancy 24 (RE24)
An alternative view of offensive performance takes into account the sequencing or timing of offensive actions. The Win Probability family of methods fall in this category. For example, the Win Probability Added (WPA) method would assign greater value to a home run in a late and close game than a home run in a blow out game. The counter argument is that this added value associated with timing may be largely random, rather than a reflection of the player’s skill.
However, RE24 is a win probability stat that may be more reflective of the player’s situational skill. This method measures the change in run expectancy based on the 24 base-out states. (The 24 base-out situations refer to the combination of runners on base and outs—for example, Runners on 1st and 3d with 2 outs is one of the 24 base out states.) Also RE24 does not include leverage due to the inning and score.
As an illustration of the RE24 stat, the league average run expectancy of bases loaded, 2 outs is 0.736 runs. The batter’s action is credited with adding runs above that average or debited with the decreasing the average run expectancy. All of the run expectancy changes above/below average are summed for each player to produce the RE24 statistic.
An advantage of RE24 is that it includes factors related to the batter’s situational awareness—such as moving the runner over with a productive out. A player’s RE24 “runs added” can be compared to his aggregate runs above average (wRAA). This comparison may suggest whether the player contributed more or less to run scoring than his wOBA or RC+ stats would indicate.
The 2022 wRAA and RE24 for the top Astros’ starting position players are shown below.
RUNS: wRAA / RE24 / Above wRAA
Yordan Alvarez 52.1 / 43.31/ -8.79
Jose Altuve 41.8 / 36.25 / -5.55
Alex Bregman 25 / 22.4 / -2.6
Kyle Tucker 18.3 / 33.09 /14.79
Michael Brantley 7.7 / 13.91 / 6.21
Chas McCormick 5.3 / 0.41 / -4.89
Jeremy Pena -0.3 / 4.74 / 5.04
Jose Abreu 27.8 / 14.9 / -12.9
The RE24 stats, above, support the idea that Kyle Tucker’s annual average hitting stats, like wRC+ and wOBA significantly understate his contribution to the team’s runs scored. Tucker’s contribution to run expectancy situations are 14.79 runs higher than his wRAA—essentially 1.5 wins more than his linear weights stats would indicate. This also refutes the notion that Tucker’s mediocre 2022 batting average curtails his offensive value.
Michael Brantley and Jeremy Pena also contributed more to RE24 than one would expect based on their wRAA. Notably, Pena is a negative wRAA offensive hitter, but he produces 4.74 runs above average according to RE24.
Yordan Alvarez, Jose Altuve, Alex Bregman, and Jose Abreu all produce substantial RE24 runs, but the RE24 falls short of the runs indicated by their wRAA. For Abreu and Bregman, an above average ground into double play (GIDP) rate may cut back RE24 performance. A GIDP has a significant negative impact on RE 24. As an example, a GIDP with bases loaded, 1 out, reduces the run expectancy from 1.52 runs to 0 runs. Abreu had 19 GIDP, which is tied for 10th in the majors. Bregman had 18 GIDP which is tied for 12th.
In summary, the RE24 statistics provides another perspective on Astros’ hitter performance. In particular, Kyle Tucker and Michael Brantley contributed significantly more to team offensive production that we would have expected, and rookie Jeremy Pena managed to provide a positive contribution to team offense despite some offensive struggles during the season.