Welcome back! In today's article, I wanted to look at the effects of playing nearly every minute of each game in a college season. Fortunately, there were several players who fit this criteria from last season, but we'll first narrow the focus to just the top five players with the highest minutes per game averages. All of these players played more than 38 minutes each night. With less than two minutes of rest each game, I was wondering if these players' fatigue would show itself in their shooting percentages. I thought that after around 30 minutes of action, exhaustion would set in and we'd see their shooting percentages dip a bit as a result. I was specifically thinking the 30 minute mark because the halftime rest is wearing off, and yet there's still 10 more minutes left to play (assuming no overtime). I also figured that said exhaustion would become less relevant in the final five minutes and adrenaline would take over as the players tried to mount comebacks or maintain a lead for the win. Thus, I was anticipating a noticeable decline in shooting percentage somewhere around minutes 30-35 and then an increase in the final 5 minutes.
How?
As mentioned above, I decided to test the idea on the top five players with the highest minutes per game averages last season. These ended up being George Tinsley (Binghamton), Kyle Lofton (St. Bonaventure), Nate Darling (Delaware - now in the NBA Draft), Malik Johnson (Canisius), and Jason Preston (Ohio). For each player, I created a graph of their cumulative shooting percentage for the previous five minutes. Basically, this means that you can look at say minute 25 and see the player's shooting percentage across the previous five minutes (minutes 20-25) for all games combined. It lets us pick any given minute and see how a player shot for the previous five minute interval across the entire season. Here's what this looks like for Binghamton's George Tinsley:
The first thing to emphasize is that the graph looks weird up until the 5 minute mark. This is because we're supposed to be looking at shooting percentage for the previous five minutes, but there isn't a full five minute interval to look back on yet. For instance, if a player went 0/1 in the first minute across all games, the cumulative shooting percentage would be 0% at the 1 minute mark on the graph. Similarly, if he went 1/1, the average would be 100%. The sample size of shots isn't maximized until the 5 minute mark and the graph yields relatively extreme results until then. Hence, we have to wait until this point before we get a complete sample of shots to begin analysis.
Another important aspect to point out is the red dotted line that I've included which signifies a player's average shooting percentage for the season. For the example above with George Tinsley, it's roughly 40.7%. By including the average, we can see streakiness in a shooter. In Tinsley's case, we see that his peak cumulative shooting percentage occurred around minute 32. This means that in the five minute interval between minute 27 and minute 32, Tinsley shot 60% - nearly 20% above his season-long average shooting percentage. Conversely, his low was at minute 39 and so he shot below 25% between minutes 34 and 39 which was 15% below his average shooting percentage.
Graph Results
After going through the intricacies of what Tinsley's graph is really showing, I'll just dump the rest of the players' graphs below without any more comments. Then we can dive into whether these graphs support my initial idea.
Is the Initial Idea Proven?
My original theory was that these high minutes players would start feeling the fatigue setting in around 30-35 minutes into the game. This would cause shooting percentage to drop which then would be followed by a recovery in the final 5 minutes. If this were the case, we'd expect to see a low on the above graphs at 35 minutes (since this would represent the cumulative shooting percentage for minutes 30-35). We then would expect the cumulative shooting percentage to gradually increase through minute 40. Unfortunately, this trend didn't really appear in the above five graphs. Kyle Lofton and Jason Preston were the only players who had a cumulative shooting percentage lower than their overall average shooting percentage at minute 35. If we look for the impact of fatigue slightly earlier in the game, there does appear to be some evidence that fatigue sets in between 27.5-32.5 minutes as seen on the cumulative average graphs as a low at minute 32.5. Darling and Preston both have pretty clear lows around this minute mark. Having only 2/5 players support this trend isn't strong evidence at all, but just so that we don't miss out on a key trend due to our small sample, we can increase it to ten players. To achieve this, we'll look at another five players who had the next highest minutes per game averages behind our original five. These players include Jordan Ford (St. Mary's), Michael Ertel (Louisiana-Monroe), Jermaine Marrow (Hampton), Mike Smith (Columbia), and Colbey Ross (Pepperdine). Their graphs are below:
Additional Graphs
Impact of a Larger Sample
After adding these five new graphs to our original sample of five, it doesn't appear that minute 32.5 is a common point of fatigue for these high usage players. Ertel, Marrow, and Ross all have a cumulative shooting percentage lower than their overall averages at minute 32.5, but Ertel and Marrow's cumulative shooting percentages continued to decline to significantly further lows after this point. Also, the other two players (Ford and Smith) had above average cumulative shooting percentages at this point. Ultimately, there just isn't a clear enough trend amongst these players to label a specific time point or even relatively specific range of time where fatigue seemingly causes all of these players' shooting percentages to be lower than normal.
Although these ten players had essentially the same minutes distribution since they were only off the court for about two minutes per game, the effects of fatigue on shooting seemingly were not the same. This could come down to a variety of factors including differing levels of player conditioning (one player may be impacted less or at different times by fatigue compared to another player). Another possibility is that the roughly two minutes of rest per game that these players got could have had a greater impact than the negligible one that I was assuming. For instance, I originally believed that the 35 minute mark would be a low point for most of these players. However, if a player tended to get the full amount of his minimal rest right before then (as opposed to the rest being diluted in smaller intervals across the game), it could be enough to make his level of fatigue significantly lower than it should be at this point in the game otherwise. This key timing of the small amount of rest might allow the player to shoot better than he would've without it. This would then go against the general player fatigue trend and show itself in a peak on the graph where a lot of other players had a low.
What Was the Purpose of All of This?
You might be thinking that this whole article was quite pointless if we didn't end up pinpointing a common area of low cumulative shooting percentage due to fatigue. In this sense, yes, the article failed. However, it was important in seeing that the impact of fatigue is pretty tricky to pick out, even within players who essentially played at the same times (the entire game). This article doesn't prove that fatigue has no universal impact on players' shooting percentages, it just confirms that such an impact cannot be found with this type of analysis. Another key takeaway is that there were a lot of interesting player-specific results from creating these cumulative shooting percentage graphs (See: Jordan Ford's volatile first half shooting compared to his relative consistency in the second half). I'll dive more into these other takeaways from the graphs hopefully in the near future in another article.
If you've made it this far, thank you so much! I know that this was a bit of a long and complicated one. If you enjoyed it, be sure to check out some of the other articles that I've written on this blog!
