The deliberate foul is not a great percentage play, despite how it first seems. But it does have its moments.

Let us be very clear about this from the beginning – we do not like watching Hackathons, regardless of who is doing the hacking and who is being hacked. It is an ugly perversion of basketball that nobody enjoys, including the hackers.

Let us also be very clear about something else – it is not a coach’s job to play aesthetically appealing basketball. It is not their job to make it pretty, not their job to please viewers, and not their job to drive ratings. Their job, magnified tremendously in the playoffs, is to win the next game and stay alive. If the Hack-a-Whomever tactic increases that likelihood by even the tiniest of margins, then it is the correct decision.

So to be absolutely clear – we are only evaluating the tactic in the context of whether or not it increases the likelihood of winning the game, and we despise it aesthetically.

With that in mind, here’s an exploration of the effectiveness of the Hack-A-Strategy, from its basic theory on upwards.

The Baseline Equation

Your opponent scores 1.10 points per possession. The player you are considering targeting shoots 40% from the foul line. Should you consider a Hack-a-Him strategy?

Awarding this player two free throw attempts projects to 0.80 points per possession, much less than the 1.10ppp they score on average. Taken independently of all other actions, the Hack-A-Strategy yields a projected benefit of 0.30 points per possession, or 3 points for every 10 possessions in which you hack.

However, no play in basketball occurs independently of other events. The most obvious related event to foul shots, particularly those attempted by a player that misses frequently, are rebounds. The above equation assumes an unrealistic 0% offensive rebounding rate. Plugging in a league average offensive rebounding percentage after free throws of 14%, and a projected second chance scoring rate of 1.10 points per chance, the margin now gets chopped in half (specifically by 0.154ppp) to a shade under 0.15ppp. To now achieve our projected three-point benefit, we will have to execute the Hack-a strategy on 20 possessions.

So to truly analyse the strategy’s effectiveness, we will have to include every possible criterion, including the less quantifiable.

The Qualitative and Quantitative Caveats

Putting aesthetic concerns aside – again – there are still qualitative issues to address from the sideline. For example, will hacking away at the opponent when playing at home take the crowd out of a close game? Conversely, will doing so on the road bring them roaring to life? In the particular case of Gregg Popovich and the San Antonio Spurs – whose current hacking of Los Angeles Clippers center DeAndre Jordan in their first round playoff series has brought the issue of the Hack-A-Strat to the fore once more – these questions are likely irrelevant due to their combined experience. For a young team like the Pelicans, however, decibel levels may matter.

There is also the issue of offensive flow and rhythm. Will frequent walks to the foul line disrupt the offensive flow of the team being hacked, perhaps by icing a shooter for several minutes without a touch? If there is research on the subject, it has escaped me (and I invite anyone to point me towards it if it exists). Or does hacking allow the team’s key players to rest and result in a higher level of play once the Hack-A-Matic machine is turned off? This is another question about which I have only read speculation and anecdote; if conclusive research exists on this, I again invite readers to direct me to it.

What can be quantified are two negative impacts the Hack-A strategy has on the fouling team.

First, each hack is acquired at the cost of one foul. It is understood that a team’s best players will not be doing the fouling, which implies that suboptimal offensive units will be on the floor while the strategy is being executed, further diminishing the projected advantage. But the exception to this issue is the player whose offensive contribution merits minutes, but whose defensive incapabilities are such that the team’s Net Margin is hurt when they are on the floor. In this case, Hack-A tactics become more profitable – the offense is not jeopardised by having a good-but-not-essential offensive player who would otherwise only be detracting from the team’s defensive effectiveness anyway.

Secondly, drawing from research I have done at the collegiate level, scoring efficiency off of possessions beginning after a free throw (made or missed) trails that of possessions beginning off a live ball turnover, blocked shot or missed shot in the paint. The potential cost of hacking goes therefore beyond the possible offensive rebound – it also likely includes a reduced offensive efficiency. And although without team-by-team origin of possession data the exact cost is unknown, there is.

While on a macro level the Hack-A-Jordan seems to deliver the benefit of roughly one point per 100 possessions, then, it is really best used by the Spurs in two distinct situations where the baseline equation is elasticized. The first situation, per the above description, can be called the Marco Belinelli clause; the second is when the Spurs have a strong halfcourt offensive lineup on the floor and want to hedge against a defensive mismatch. The Hack-A-Strat, if broadly and thoughtlessly utilised, is not the percentage play it is thought to be, even with a free throw shooter as bad as Jordan. But precisely because of how bad Jordan’s shooting really is, it has its moments.

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