Base Running (BsR) is FanGraphs’ all encompassing base running statistic that turns stolen bases, caught stealings, and other base running plays (taking extra bases, being thrown out on the bases, etc) into runs above and below average. It is the combination of Weighted Stolen Base Runs (wSB), Weighted Grounded Into Double Play Runs (wGDP), and Ultimate Base Running (UBR) which are all available on the leaderboards and player pages.
BsR serves as the base running component of Wins Above Replacement (WAR) and provides a lot more information than simply looking at a player’s stolen base total if you are interested in judging a player’s base running performance.
The basic equation for BsR is quite simple:
BsR = wSB + UBR + wGDP
wSB is Weighted Stolen Base Runs which estimates the number of runs above or below average a player contributes to his team by stealing bases and being thrown out trying to steal. You can read more about wSB specifically at the link provided, but the calculation is as follows:
wSB = SB * runSB + CS * runCS – lgwSB * (1B + BB + HBP – IBB)
League stolen base runs (lgwSB) is:
lgwSB = (SB * runSB + CS * runCS) / (1B + BB + HBP – IBB)
As with all linear weights-based metrics, the runs values are estimates. In this case, the run value of a stolen base is set at .2 runs for all seasons. The run value of a caught stealing changes from year to year to reflect the changing value of runs and outs over the season.
runCS = 2 x RunsPerOut + 0.075
Calculating Ultimate Base Running (UBR) is more difficult in practice, but it is theoretically quite easy to understand. UBR essentially takes the run expectancy of the advancement (or lack thereof) and credits that to the base runner depending the frequency with which the average runner advances in the same situation. For more specific detail about the types of plays it considers, check out the UBR Primer.
The same goes for wGDP. All you’re doing is taking the extra outs a player costs his team (or saves) by hitting into more double plays (or fewer) than average given his opportunities.
BsR is simply wSB, UBR, and wGDP added together with no further adjustments.
BsR isn’t the only way to estimate the value of a player’s base running contribution (other sites host similar metrics), but it is a significant step forward from counting up a player’s stolen base total.
First, stolen bases are valuable, but being caught trying to steal is more costly than successfully stealing is beneficial. The intuition here is pretty simple. If you steal a base, you increase the odds that your team scores because you are closer to home, but if you are caught stealing, you not only remove a base runner but you also add an out.
There are certainly situations in which that is a more worthwhile risk, but on average, you need to steal successfully about two-thirds of the time to be positively impacting your team. In other words, stolen bases are good, but being caught on the bases has a larger negative impact. Stealing 40 bases while being caught 25 times is not as valuable as stealing 20 bases and being caught twice.
Additionally, BsR provides information about base running that occurs while the ball is in play. There is value in going first to third, home to second, and being able to advance while tagging up, among other things. The UBR Primer can explain the specific situations in which runners receive credit, but the basic truth is that having a player on the bases who can advance farther than average is valuable because it either leads directly to additional runs or makes future runs more likely, which is something you want to consider when looking at a player’s total value. And while it’s a smaller factor overall, staying out of double plays with men on base is helpful, so we should count that too.
BsR allows us to capture most of a player’s value on the bases with reasonable accuracy and adds to our understanding of a player’s all-round value.
How To Use BsR:
BsR is like any other run value statistic available on FanGraphs in that it tells you the number of runs above or below average a player is at that particular aspect of the game. As usual, zero is league average for that particular year and every nine or ten runs above or below average is equal to about one win.
BsR is a measure of past value and you need more than a full season of data for it to become a reasonably strong predictor of future BsR. This is a function of the typical number of base running plays that a player can make during a season to dramatically affect their rating, but it is also important to remember that base running, like any other statistic, is susceptible to random variation and true talent fluctuation.
As a simple recommendation, it’s best to look at BsR as a pretty good measure of how much value that player has added on the bases while also recognizing that some regression to the player’s career average or league average should be included when trying to forecast future base running skill.
BsR is calculated so that league average is always equal to zero with about every ten runs is equal to one win. The exact values below will shift from season to season, but you can use these as a guide for determining how a player stacks up:
Rules of Thumb
Things to Remember:
● BsR is set with league average equal to zero, which allows comparisons among different seasons.
● Caught stealing was not reliably tracked prior to the 1950s, meaning that data prior to that is potentially inaccurate. Additionally, UBR only dates back to 2002. In other words, prior to 2002, BsR is based only on SB and CS (wSB) and prior to the 1950s that data may not be accurate. Use BsR with caution as you move back into history.
● BsR is a decent snapshot of past value but usually requires more than one year of data to become reasonably predictive of future BsR.
● BsR is the base running component of WAR at FanGraphs.
● FanGraphs also carries something called “BaseRuns,” which is a model of estimating team performance. BsR is not Base Runs.
Links to Further Reading: